Convex Hulls, Delaunay Triangulations and Voronoi Diagrams
In our last tutorial, we studied how to visualize a pass network for the teams from a particular match and how to analyse the networks using knowledge from complex network analysis literature. In this tutorial we will learn how to implement ideas from computational geometry on football spatial event or tracking data and generate important visualizations and analyses. This post is highly influenced by the concepts discussed in the second chapter How Slime Moulds Built Barcelona from the book Soccermatics.
First we will study how to develop a convex hull around those points (locations denoted by x- and y- coordinates) from where a player had made a pass or had taken a shot in a particular game. Mathematically, if these points are contained in a set X then the convex hull is the smallest convex set that contains X. This will help us get an idea about the optimal field coverage of a player during the match. Let us see how a convex hull for a set of points looks like:
This figure has been adapted from the wikipedia article on convex hulls.
Before we start with our data collection and analysis we need to download the scipy package which provides us with a collection of modules for working on scientific computation with Python.
Let us pip install the package:
pip install scipy
We will first import all the packages that we need in this tutorial:
from statsbombpy import sb # statsbomb api
import matplotlib.pyplot as plt # matplotlib for plotting
from mplsoccer.pitch import Pitch # for drawing the football pitch
import seaborn as sns # seaborn for plotting useful statistical graphs
import numpy as np # numerical python package
import pandas as pd # pandas for manipulating and analysing data
import networkx as nx # package for complex network analysis
Further, for this post, we need to use the scipy.spatial module that allows us to work with spatial algorithms and data structures. As we are going to work with convex hulls first, let us import the ConvexHull classes from scipy.spatial:
from scipy.spatial import ConvexHull
Next, we will collect the event data from a particular match and filter the data in such a way that the event type will be set to Pass or Shot, fetching us all the data for pass and shot events.
comp = sb.competitions()
## credentials were not supplied. open data access only
print(comp.to_markdown())
## | | competition_id | season_id | country_name | competition_name | competition_gender | season_name | match_updated | match_available |
## |---:|-----------------:|------------:|:-------------------------|:------------------------|:---------------------|:--------------|:---------------------------|:---------------------------|
## | 0 | 16 | 4 | Europe | Champions League | male | 2018/2019 | 2021-04-19T17:36:05.724116 | 2021-04-19T17:36:05.724116 |
## | 1 | 16 | 1 | Europe | Champions League | male | 2017/2018 | 2021-01-23T21:55:30.425330 | 2021-01-23T21:55:30.425330 |
## | 2 | 16 | 2 | Europe | Champions League | male | 2016/2017 | 2020-08-26T12:33:15.869622 | 2020-07-29T05:00 |
## | 3 | 16 | 27 | Europe | Champions League | male | 2015/2016 | 2020-08-26T12:33:15.869622 | 2020-07-29T05:00 |
## | 4 | 16 | 26 | Europe | Champions League | male | 2014/2015 | 2020-08-26T12:33:15.869622 | 2020-07-29T05:00 |
## | 5 | 16 | 25 | Europe | Champions League | male | 2013/2014 | 2020-08-26T12:33:15.869622 | 2020-07-29T05:00 |
## | 6 | 16 | 24 | Europe | Champions League | male | 2012/2013 | 2020-08-26T12:33:15.869622 | 2020-07-29T05:00 |
## | 7 | 16 | 23 | Europe | Champions League | male | 2011/2012 | 2020-08-26T12:33:15.869622 | 2020-07-29T05:00 |
## | 8 | 16 | 22 | Europe | Champions League | male | 2010/2011 | 2020-07-29T05:00 | 2020-07-29T05:00 |
## | 9 | 16 | 21 | Europe | Champions League | male | 2009/2010 | 2020-07-29T05:00 | 2020-07-29T05:00 |
## | 10 | 16 | 41 | Europe | Champions League | male | 2008/2009 | 2020-08-30T10:18:39.435424 | 2020-08-30T10:18:39.435424 |
## | 11 | 16 | 39 | Europe | Champions League | male | 2006/2007 | 2021-03-31T04:18:30.437060 | 2021-03-31T04:18:30.437060 |
## | 12 | 16 | 37 | Europe | Champions League | male | 2004/2005 | 2021-04-01T06:18:57.459032 | 2021-04-01T06:18:57.459032 |
## | 13 | 16 | 44 | Europe | Champions League | male | 2003/2004 | 2021-04-01T00:34:59.472485 | 2021-04-01T00:34:59.472485 |
## | 14 | 16 | 76 | Europe | Champions League | male | 1999/2000 | 2020-07-29T05:00 | 2020-07-29T05:00 |
## | 15 | 37 | 42 | England | FA Women's Super League | female | 2019/2020 | 2021-04-28T19:48:01.172671 | 2021-04-28T19:48:01.172671 |
## | 16 | 37 | 4 | England | FA Women's Super League | female | 2018/2019 | 2021-04-28T19:48:01.166958 | 2021-04-28T19:48:01.166958 |
## | 17 | 43 | 3 | International | FIFA World Cup | male | 2018 | 2020-10-25T14:03:50.263266 | 2020-10-25T14:03:50.263266 |
## | 18 | 11 | 42 | Spain | La Liga | male | 2019/2020 | 2020-12-18T12:10:38.985394 | 2020-12-18T12:10:38.985394 |
## | 19 | 11 | 4 | Spain | La Liga | male | 2018/2019 | 2021-04-20T03:24:51.029365 | 2021-04-20T03:24:51.029365 |
## | 20 | 11 | 1 | Spain | La Liga | male | 2017/2018 | 2021-04-19T17:36:05.805404 | 2021-04-19T17:36:05.805404 |
## | 21 | 11 | 2 | Spain | La Liga | male | 2016/2017 | 2021-02-02T23:24:58.985975 | 2021-02-02T23:24:58.985975 |
## | 22 | 11 | 27 | Spain | La Liga | male | 2015/2016 | 2020-07-29T05:00 | 2020-07-29T05:00 |
## | 23 | 11 | 26 | Spain | La Liga | male | 2014/2015 | 2020-07-29T05:00 | 2020-07-29T05:00 |
## | 24 | 11 | 25 | Spain | La Liga | male | 2013/2014 | 2020-07-29T05:00 | 2020-07-29T05:00 |
## | 25 | 11 | 24 | Spain | La Liga | male | 2012/2013 | 2020-07-29T05:00 | 2020-07-29T05:00 |
## | 26 | 11 | 23 | Spain | La Liga | male | 2011/2012 | 2020-07-29T05:00 | 2020-07-29T05:00 |
## | 27 | 11 | 22 | Spain | La Liga | male | 2010/2011 | 2020-07-29T05:00 | 2020-07-29T05:00 |
## | 28 | 11 | 21 | Spain | La Liga | male | 2009/2010 | 2020-07-29T05:00 | 2020-07-29T05:00 |
## | 29 | 11 | 41 | Spain | La Liga | male | 2008/2009 | 2020-07-29T05:00 | 2020-07-29T05:00 |
## | 30 | 11 | 40 | Spain | La Liga | male | 2007/2008 | 2020-07-29T05:00 | 2020-07-29T05:00 |
## | 31 | 11 | 39 | Spain | La Liga | male | 2006/2007 | 2020-07-29T05:00 | 2020-07-29T05:00 |
## | 32 | 11 | 38 | Spain | La Liga | male | 2005/2006 | 2020-07-29T05:00 | 2020-07-29T05:00 |
## | 33 | 11 | 37 | Spain | La Liga | male | 2004/2005 | 2020-07-29T05:00 | 2020-07-29T05:00 |
## | 34 | 49 | 3 | United States of America | NWSL | female | 2018 | 2020-07-29T05:00 | 2020-07-29T05:00 |
## | 35 | 2 | 44 | England | Premier League | male | 2003/2004 | 2020-08-31T20:40:28.969635 | 2020-08-31T20:40:28.969635 |
## | 36 | 72 | 30 | International | Women's World Cup | female | 2019 | 2020-07-29T05:00 | 2020-07-29T05:00 |
Next, let us decide on a competition_id and a season_id to extract matches from a particular season and competition:
mat = sb.matches(competition_id = 11, season_id = 1)
## credentials were not supplied. open data access only
print(mat.to_markdown())
## | | match_id | match_date | kick_off | competition | season | home_team | away_team | home_score | away_score | match_status | match_status_360 | last_updated | last_updated_360 | match_week | competition_stage | stadium | referee | data_version | shot_fidelity_version | xy_fidelity_version |
## |---:|-----------:|:-------------|:-------------|:----------------|:----------|:--------------------|:--------------------|-------------:|-------------:|:---------------|:-------------------|:-----------------|:-------------------|-------------:|:--------------------|:------------------------------|:------------------|:---------------|------------------------:|:----------------------|
## | 0 | 9592 | 2017-09-09 | 20:45:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Espanyol | 5 | 0 | available | unscheduled | 2020-07-29T05:00 | | 3 | Regular Season | Camp Nou | Jesús Gil | 1.1.0 | 2 | |
## | 1 | 9870 | 2018-04-07 | 20:45:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Leganés | 3 | 1 | available | unscheduled | 2020-07-29T05:00 | | 31 | Regular Season | Camp Nou | nan | 1.0.2 | 2 | |
## | 2 | 9783 | 2018-02-04 | 16:15:00.000 | Spain - La Liga | 2017/2018 | Espanyol | Barcelona | 1 | 1 | available | unscheduled | 2020-07-29T05:00 | | 22 | Regular Season | RCDE Stadium | Jesús Gil | 1.0.2 | 2 | |
## | 3 | 9700 | 2017-12-02 | 13:00:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Celta Vigo | 2 | 2 | available | unscheduled | 2020-07-29T05:00 | | 14 | Regular Season | Camp Nou | M. Melero | 1.0.2 | 2 | |
## | 4 | 9860 | 2018-03-31 | 20:45:00.000 | Spain - La Liga | 2017/2018 | Sevilla | Barcelona | 2 | 2 | available | unscheduled | 2020-07-29T05:00 | | 30 | Regular Season | Estadio Ramón Sánchez Pizjuán | José González | 1.0.2 | 2 | |
## | 5 | 9695 | 2017-11-26 | 20:45:00.000 | Spain - La Liga | 2017/2018 | Valencia | Barcelona | 1 | 1 | available | unscheduled | 2020-07-29T05:00 | | 13 | Regular Season | Estadio de Mestalla | Ignacio Iglesias | 1.0.2 | 2 | |
## | 6 | 9794 | 2018-02-11 | 16:15:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Getafe | 0 | 0 | available | unscheduled | 2020-07-29T05:00 | | 23 | Regular Season | Camp Nou | David Fernández | 1.0.2 | 2 | |
## | 7 | 9717 | 2017-12-10 | 20:45:00.000 | Spain - La Liga | 2017/2018 | Villarreal | Barcelona | 0 | 2 | available | unscheduled | 2020-07-29T05:00 | | 15 | Regular Season | Estadio de la Cerámica | R. De Burgos | 1.0.2 | 2 | |
## | 8 | 9673 | 2017-11-04 | 20:45:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Sevilla | 2 | 1 | available | unscheduled | 2020-07-29T05:00 | | 11 | Regular Season | Camp Nou | José González | 1.0.2 | 2 | |
## | 9 | 9650 | 2017-10-21 | 20:45:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Málaga | 2 | 0 | available | unscheduled | 2020-07-29T05:00 | | 9 | Regular Season | Camp Nou | P. González | 1.0.2 | 2 | |
## | 10 | 9620 | 2017-09-23 | 20:45:00.000 | Spain - La Liga | 2017/2018 | Girona | Barcelona | 0 | 3 | available | unscheduled | 2020-07-29T05:00 | | 6 | Regular Season | Estadi Municipal de Montilivi | nan | 1.0.2 | 2 | |
## | 11 | 9827 | 2018-03-01 | 21:00:00.000 | Spain - La Liga | 2017/2018 | Las Palmas | Barcelona | 1 | 1 | available | unscheduled | 2020-07-29T05:00 | | 26 | Regular Season | Estadio de Gran Canaria | Antonio Mateu | 1.0.2 | 2 | |
## | 12 | 9837 | 2018-03-04 | 16:15:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Atlético Madrid | 1 | 0 | available | unscheduled | 2020-07-29T05:00 | | 27 | Regular Season | Camp Nou | Jesús Gil | 1.0.2 | 2 | |
## | 13 | 9912 | 2018-04-29 | 20:45:00.000 | Spain - La Liga | 2017/2018 | Deportivo La Coruna | Barcelona | 2 | 4 | available | unscheduled | 2020-07-29T05:00 | | 35 | Regular Season | Estadio Abanca-Riazor | R. De Burgos | 1.0.2 | 2 | |
## | 14 | 9811 | 2018-02-24 | 20:45:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Girona | 6 | 1 | available | unscheduled | 2020-07-29T05:00 | | 25 | Regular Season | Camp Nou | J. Alberola Rojas | 1.0.2 | 2 | |
## | 15 | 9642 | 2017-10-14 | 20:45:00.000 | Spain - La Liga | 2017/2018 | Atlético Madrid | Barcelona | 1 | 1 | available | unscheduled | 2020-07-29T05:00 | | 8 | Regular Season | Estadio Wanda Metropolitano | Antonio Mateu | 1.0.2 | 2 | |
## | 16 | 9774 | 2018-01-28 | 20:45:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Deportivo Alavés | 2 | 1 | available | unscheduled | 2020-07-29T05:00 | | 21 | Regular Season | Camp Nou | Ignacio Iglesias | 1.0.2 | 2 | |
## | 17 | 9602 | 2017-09-16 | 16:15:00.000 | Spain - La Liga | 2017/2018 | Getafe | Barcelona | 1 | 2 | available | unscheduled | 2020-07-29T05:00 | | 4 | Regular Season | Coliseum Alfonso Pérez | David Fernández | 1.0.2 | 2 | |
## | 18 | 9948 | 2018-05-20 | 20:45:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Real Sociedad | 1 | 0 | available | unscheduled | 2020-07-29T05:00 | | 38 | Regular Season | Camp Nou | J. Munuera | 1.0.2 | 2 | |
## | 19 | 9682 | 2017-11-18 | 16:15:00.000 | Spain - La Liga | 2017/2018 | Leganés | Barcelona | 0 | 3 | available | unscheduled | 2020-07-29T05:00 | | 12 | Regular Season | Estadio Municipal de Butarque | Alberto Undiano | 1.0.2 | 2 | |
## | 20 | 9581 | 2017-08-26 | 18:15:00.000 | Spain - La Liga | 2017/2018 | Deportivo Alavés | Barcelona | 0 | 2 | available | unscheduled | 2020-07-29T05:00 | | 2 | Regular Season | Estadio de Mendizorroza | nan | 1.0.2 | 2 | |
## | 21 | 9726 | 2017-12-17 | 20:45:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Deportivo La Coruna | 4 | 0 | available | unscheduled | 2020-07-29T05:00 | | 16 | Regular Season | Camp Nou | Antonio Mateu | 1.0.2 | 2 | |
## | 22 | 9754 | 2018-01-14 | 20:45:00.000 | Spain - La Liga | 2017/2018 | Real Sociedad | Barcelona | 2 | 4 | available | unscheduled | 2020-07-29T05:00 | | 19 | Regular Season | Reale Arena | José González | 1.1.0 | 2 | |
## | 23 | 9575 | 2017-08-20 | 20:15:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Real Betis | 2 | 0 | available | unscheduled | 2020-07-29T05:00 | | 1 | Regular Season | Camp Nou | nan | 1.1.0 | 2 | |
## | 24 | 9765 | 2018-01-21 | 20:45:00.000 | Spain - La Liga | 2017/2018 | Real Betis | Barcelona | 0 | 5 | available | unscheduled | 2020-07-29T05:00 | | 20 | Regular Season | Estadio Benito Villamarín | S. Jaime | 1.1.0 | 2 | |
## | 25 | 9889 | 2018-04-17 | 21:00:00.000 | Spain - La Liga | 2017/2018 | Celta Vigo | Barcelona | 2 | 2 | available | unscheduled | 2020-07-29T05:00 | | 33 | Regular Season | Abanca-Balaídos | David Fernández | 1.1.0 | 2 | |
## | 26 | 9928 | 2018-05-09 | 20:00:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Villarreal | 5 | 1 | available | unscheduled | 2020-07-29T05:00 | | 34 | Regular Season | Camp Nou | nan | 1.1.0 | 2 | |
## | 27 | 9609 | 2017-09-19 | 22:00:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Eibar | 6 | 1 | available | unscheduled | 2020-07-29T05:00 | | 5 | Regular Season | Camp Nou | nan | 1.0.2 | 2 | |
## | 28 | 9636 | 2017-10-01 | 16:15:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Las Palmas | 3 | 0 | available | unscheduled | 2020-07-29T05:00 | | 7 | Regular Season | Camp Nou | nan | 1.0.2 | 2 | |
## | 29 | 9661 | 2017-10-28 | 20:45:00.000 | Spain - La Liga | 2017/2018 | Athletic Bilbao | Barcelona | 0 | 2 | available | unscheduled | 2020-07-29T05:00 | | 10 | Regular Season | San Mamés Barria | nan | 1.0.2 | 2 | |
## | 30 | 9736 | 2017-12-23 | 13:00:00.000 | Spain - La Liga | 2017/2018 | Real Madrid | Barcelona | 0 | 3 | available | unscheduled | 2020-07-29T05:00 | | 17 | Regular Season | Estadio Santiago Bernabéu | nan | 1.1.0 | 2 | |
## | 31 | 9742 | 2018-01-07 | 16:15:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Levante | 3 | 0 | available | unscheduled | 2020-07-29T05:00 | | 18 | Regular Season | Camp Nou | nan | 1.0.2 | 2 | |
## | 32 | 9799 | 2018-02-17 | 16:15:00.000 | Spain - La Liga | 2017/2018 | Eibar | Barcelona | 0 | 2 | available | unscheduled | 2020-07-29T05:00 | | 24 | Regular Season | Estadio Municipal de Ipurúa | nan | 1.0.2 | 2 | |
## | 33 | 9855 | 2018-03-18 | 16:15:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Athletic Bilbao | 2 | 0 | available | unscheduled | 2020-07-29T05:00 | | 29 | Regular Season | Camp Nou | nan | 1.0.2 | 2 | |
## | 34 | 9880 | 2018-04-14 | 16:15:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Valencia | 2 | 1 | available | unscheduled | 2020-07-29T05:00 | | 32 | Regular Season | Camp Nou | nan | 1.0.2 | 2 | |
## | 35 | 9924 | 2018-05-06 | 20:45:00.000 | Spain - La Liga | 2017/2018 | Barcelona | Real Madrid | 2 | 2 | available | unscheduled | 2020-07-29T05:00 | | 36 | Regular Season | Camp Nou | nan | 1.0.2 | 2 | |
So, we have extracted the matches from 2017-18 La Liga season. Now let us decide on a particular match to extract the event data from:
events = sb.events(match_id = 9609)
## credentials were not supplied. open data access only
print(events.head(10).to_markdown())
## | | bad_behaviour_card | ball_receipt_outcome | ball_recovery_recovery_failure | block_deflection | carry_end_location | clearance_aerial_won | counterpress | dribble_outcome | dribble_overrun | duel_outcome | duel_type | duration | foul_committed_advantage | foul_committed_penalty | foul_committed_type | foul_won_advantage | foul_won_defensive | foul_won_penalty | goalkeeper_body_part | goalkeeper_end_location | goalkeeper_outcome | goalkeeper_position | goalkeeper_technique | goalkeeper_type | id | index | interception_outcome | location | match_id | minute | pass_aerial_won | pass_angle | pass_assisted_shot_id | pass_backheel | pass_body_part | pass_cross | pass_cut_back | pass_deflected | pass_end_location | pass_goal_assist | pass_height | pass_length | pass_outcome | pass_recipient | pass_shot_assist | pass_switch | pass_type | period | play_pattern | player | position | possession | possession_team | related_events | second | shot_aerial_won | shot_body_part | shot_end_location | shot_freeze_frame | shot_key_pass_id | shot_one_on_one | shot_outcome | shot_redirect | shot_statsbomb_xg | shot_technique | shot_type | substitution_outcome | substitution_replacement | tactics | team | timestamp | type | under_pressure |
## |---:|---------------------:|-----------------------:|---------------------------------:|-------------------:|---------------------:|-----------------------:|---------------:|------------------:|------------------:|---------------:|------------:|-----------:|---------------------------:|-------------------------:|----------------------:|---------------------:|---------------------:|-------------------:|-----------------------:|--------------------------:|---------------------:|----------------------:|-----------------------:|------------------:|:-------------------------------------|--------:|-----------------------:|:-------------|-----------:|---------:|------------------:|-------------:|------------------------:|----------------:|:-----------------|-------------:|----------------:|-----------------:|:--------------------|-------------------:|:--------------|--------------:|---------------:|:----------------------------|-------------------:|--------------:|:------------|---------:|:---------------|:-------------------------------|:---------------------|-------------:|:------------------|:-----------------------------------------|---------:|------------------:|-----------------:|--------------------:|--------------------:|-------------------:|------------------:|---------------:|----------------:|--------------------:|-----------------:|------------:|-----------------------:|---------------------------:|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------|:-------------|:------------|-----------------:|
## | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 2fc157ab-bb2c-48f7-a099-45411bc6d7db | 1 | nan | nan | 9609 | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 1 | Regular Play | nan | nan | 1 | Barcelona | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | {'formation': 4321, 'lineup': [{'player': {'id': 20055, 'name': 'Marc-André ter Stegen'}, 'position': {'id': 1, 'name': 'Goalkeeper'}, 'jersey_number': 1}, {'player': {'id': 6374, 'name': 'Nélson Cabral Semedo'}, 'position': {'id': 2, 'name': 'Right Back'}, 'jersey_number': 2}, {'player': {'id': 5213, 'name': 'Gerard Piqué Bernabéu'}, 'position': {'id': 3, 'name': 'Right Center Back'}, 'jersey_number': 3}, {'player': {'id': 5506, 'name': 'Javier Alejandro Mascherano'}, 'position': {'id': 5, 'name': 'Left Center Back'}, 'jersey_number': 14}, {'player': {'id': 6849, 'name': 'Lucas Digne'}, 'position': {'id': 6, 'name': 'Left Back'}, 'jersey_number': 19}, {'player': {'id': 5542, 'name': 'José Paulo Bezzera Maciel Júnior'}, 'position': {'id': 13, 'name': 'Right Center Midfield'}, 'jersey_number': 15}, {'player': {'id': 5203, 'name': 'Sergio Busquets i Burgos'}, 'position': {'id': 14, 'name': 'Center Midfield'}, 'jersey_number': 5}, {'player': {'id': 5216, 'name': 'Andrés Iniesta Luján'}, 'position': {'id': 15, 'name': 'Left Center Midfield'}, 'jersey_number': 8}, {'player': {'id': 3726, 'name': 'Gerard Deulofeu Lázaro'}, 'position': {'id': 17, 'name': 'Right Wing'}, 'jersey_number': 16}, {'player': {'id': 6609, 'name': 'Denis Suárez Fernández'}, 'position': {'id': 21, 'name': 'Left Wing'}, 'jersey_number': 6}, {'player': {'id': 5503, 'name': 'Lionel Andrés Messi Cuccittini'}, 'position': {'id': 23, 'name': 'Center Forward'}, 'jersey_number': 10}]} | Barcelona | 00:00:00.000 | Starting XI | nan |
## | 1 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 57eb014c-03f7-4f4d-a759-1515ea7d97b3 | 2 | nan | nan | 9609 | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 1 | Regular Play | nan | nan | 1 | Barcelona | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | {'formation': 4231, 'lineup': [{'player': {'id': 6698, 'name': 'Marko Dmitrović'}, 'position': {'id': 1, 'name': 'Goalkeeper'}, 'jersey_number': 25}, {'player': {'id': 6709, 'name': 'Anaitz Arbilla Zabala'}, 'position': {'id': 2, 'name': 'Right Back'}, 'jersey_number': 18}, {'player': {'id': 6708, 'name': 'Paulo André Rodrigues de Oliveira'}, 'position': {'id': 3, 'name': 'Right Center Back'}, 'jersey_number': 12}, {'player': {'id': 6924, 'name': 'Alejandro Gálvez Jimena'}, 'position': {'id': 5, 'name': 'Left Center Back'}, 'jersey_number': 3}, {'player': {'id': 6776, 'name': 'David Juncà Reñé'}, 'position': {'id': 6, 'name': 'Left Back'}, 'jersey_number': 23}, {'player': {'id': 6775, 'name': 'Daniel García Carrillo'}, 'position': {'id': 13, 'name': 'Right Center Midfield'}, 'jersey_number': 14}, {'player': {'id': 6712, 'name': 'Gonzalo Escalante'}, 'position': {'id': 15, 'name': 'Left Center Midfield'}, 'jersey_number': 5}, {'player': {'id': 6699, 'name': 'Ander Capa Rodríguez'}, 'position': {'id': 17, 'name': 'Right Wing'}, 'jersey_number': 7}, {'player': {'id': 6701, 'name': 'Joan Jordán Moreno'}, 'position': {'id': 19, 'name': 'Center Attacking Midfield'}, 'jersey_number': 24}, {'player': {'id': 5687, 'name': 'Takashi Inui'}, 'position': {'id': 21, 'name': 'Left Wing'}, 'jersey_number': 8}, {'player': {'id': 6700, 'name': 'Sergio Enrich Ametller'}, 'position': {'id': 23, 'name': 'Center Forward'}, 'jersey_number': 9}]} | Eibar | 00:00:00.000 | Starting XI | nan |
## | 2 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 94e0c664-c1e9-4ee7-881e-d81124f3836a | 3 | nan | nan | 9609 | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 1 | Regular Play | nan | nan | 1 | Barcelona | ['55c6967a-18cc-4ff8-a4be-d0e3915fc22d'] | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | Eibar | 00:00:00.000 | Half Start | nan |
## | 3 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 55c6967a-18cc-4ff8-a4be-d0e3915fc22d | 4 | nan | nan | 9609 | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 1 | Regular Play | nan | nan | 1 | Barcelona | ['94e0c664-c1e9-4ee7-881e-d81124f3836a'] | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | Barcelona | 00:00:00.000 | Half Start | nan |
## | 4 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | aa8d3682-d03c-4948-99c5-d9120d8d0555 | 1850 | nan | nan | 9609 | 45 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 2 | Regular Play | nan | nan | 92 | Eibar | ['bb6b9211-45dd-4305-b0a3-d0244deeab04'] | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | Barcelona | 00:00:00.000 | Half Start | nan |
## | 5 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | bb6b9211-45dd-4305-b0a3-d0244deeab04 | 1851 | nan | nan | 9609 | 45 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 2 | Regular Play | nan | nan | 92 | Eibar | ['aa8d3682-d03c-4948-99c5-d9120d8d0555'] | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | Eibar | 00:00:00.000 | Half Start | nan |
## | 6 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 1.07 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 3f6b644f-5ce2-4b89-a912-bfbc05475cbb | 5 | nan | [60.0, 40.0] | 9609 | 0 | nan | -2.79282 | nan | nan | Left Foot | nan | nan | nan | [49.0, 36.0] | nan | Ground Pass | 11.7047 | nan | Sergio Busquets i Burgos | nan | nan | Kick Off | 1 | From Kick Off | Lionel Andrés Messi Cuccittini | Center Forward | 2 | Barcelona | ['b8523951-7a5b-4304-a768-cca7c751a9be'] | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | Barcelona | 00:00:00.480 | Pass | nan |
## | 7 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0.924 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 8c147c94-859d-446a-9bdf-1d2cd2307007 | 8 | nan | [46.0, 36.0] | 9609 | 0 | nan | -0.628796 | nan | nan | Right Foot | nan | nan | nan | [57.0, 28.0] | nan | Ground Pass | 13.6015 | nan | Andrés Iniesta Luján | nan | nan | nan | 1 | From Kick Off | Sergio Busquets i Burgos | Center Midfield | 2 | Barcelona | ['1e11a8d0-7beb-446c-9352-7f336b1703b5'] | 3 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | Barcelona | 00:00:03.252 | Pass | nan |
## | 8 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 1.48 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | e7a83277-0098-460b-9116-4550784f5382 | 11 | nan | [56.0, 28.0] | 9609 | 0 | nan | -3.02216 | nan | nan | Right Foot | nan | nan | nan | [31.0, 25.0] | nan | Ground Pass | 25.1794 | nan | Javier Alejandro Mascherano | nan | nan | nan | 1 | From Kick Off | Andrés Iniesta Luján | Left Center Midfield | 2 | Barcelona | ['5a1cf3a1-6c31-4780-9cb0-84af87189db6'] | 4 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | Barcelona | 00:00:04.213 | Pass | nan |
## | 9 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 1.379 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 32ff139c-0932-48c1-9ab5-b392cde31db0 | 14 | nan | [31.0, 27.0] | 9609 | 0 | nan | 1.72945 | nan | nan | Right Foot | nan | nan | nan | [27.0, 52.0] | nan | Ground Pass | 25.318 | nan | Gerard Piqué Bernabéu | nan | nan | nan | 1 | From Kick Off | Javier Alejandro Mascherano | Left Center Back | 2 | Barcelona | ['88bfdb69-91a4-491c-8866-f49ec1b701d1'] | 7 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | Barcelona | 00:00:07.225 | Pass | nan |
print(events.tail(10).to_markdown())
## | | bad_behaviour_card | ball_receipt_outcome | ball_recovery_recovery_failure | block_deflection | carry_end_location | clearance_aerial_won | counterpress | dribble_outcome | dribble_overrun | duel_outcome | duel_type | duration | foul_committed_advantage | foul_committed_penalty | foul_committed_type | foul_won_advantage | foul_won_defensive | foul_won_penalty | goalkeeper_body_part | goalkeeper_end_location | goalkeeper_outcome | goalkeeper_position | goalkeeper_technique | goalkeeper_type | id | index | interception_outcome | location | match_id | minute | pass_aerial_won | pass_angle | pass_assisted_shot_id | pass_backheel | pass_body_part | pass_cross | pass_cut_back | pass_deflected | pass_end_location | pass_goal_assist | pass_height | pass_length | pass_outcome | pass_recipient | pass_shot_assist | pass_switch | pass_type | period | play_pattern | player | position | possession | possession_team | related_events | second | shot_aerial_won | shot_body_part | shot_end_location | shot_freeze_frame | shot_key_pass_id | shot_one_on_one | shot_outcome | shot_redirect | shot_statsbomb_xg | shot_technique | shot_type | substitution_outcome | substitution_replacement | tactics | team | timestamp | type | under_pressure |
## |-----:|:---------------------|-----------------------:|---------------------------------:|-------------------:|---------------------:|-----------------------:|---------------:|------------------:|------------------:|---------------:|------------:|-----------:|---------------------------:|-------------------------:|----------------------:|---------------------:|---------------------:|-------------------:|-----------------------:|--------------------------:|---------------------:|----------------------:|-----------------------:|------------------:|:-------------------------------------|--------:|-----------------------:|:-------------|-----------:|---------:|------------------:|-------------:|------------------------:|----------------:|-----------------:|-------------:|----------------:|-----------------:|--------------------:|-------------------:|--------------:|--------------:|---------------:|-----------------:|-------------------:|--------------:|------------:|---------:|:---------------|:-------------------------|:----------------------|-------------:|:------------------|:-----------------------------------------|---------:|------------------:|-----------------:|--------------------:|--------------------:|-------------------:|------------------:|---------------:|----------------:|--------------------:|-----------------:|------------:|:-----------------------|:---------------------------------|----------:|:----------|:-------------|:--------------|-----------------:|
## | 3663 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | efd13f52-219f-44ca-8c7a-18d1aa5829e7 | 3672 | nan | nan | 9609 | 92 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 2 | Regular Play | nan | nan | 185 | Barcelona | ['fbb9e4ec-27b5-47d0-af0d-f3cdef18cbd7'] | 5 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | Barcelona | 00:47:05.183 | Half End | nan |
## | 3664 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | fbb9e4ec-27b5-47d0-af0d-f3cdef18cbd7 | 3673 | nan | nan | 9609 | 92 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 2 | Regular Play | nan | nan | 185 | Barcelona | ['efd13f52-219f-44ca-8c7a-18d1aa5829e7'] | 5 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | Eibar | 00:47:05.183 | Half End | nan |
## | 3665 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 42bb2ab4-6a90-47c6-8c21-f0ef00301612 | 2602 | nan | nan | 9609 | 62 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 2 | From Kick Off | Andrés Iniesta Luján | Left Center Midfield | 126 | Eibar | nan | 44 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | Tactical | Sergi Roberto Carnicer | nan | Barcelona | 00:17:44.157 | Substitution | nan |
## | 3666 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 7dbbf40f-3042-4f82-80ba-8d33299a5df0 | 2674 | nan | nan | 9609 | 64 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 2 | From Throw In | Ander Capa Rodríguez | Right Wing | 129 | Barcelona | nan | 27 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | Tactical | Rubén Peña Jiménez | nan | Eibar | 00:19:27.420 | Substitution | nan |
## | 3667 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 9eb5f156-f572-4e63-bb81-8b7908b42a90 | 2675 | nan | nan | 9609 | 64 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 2 | From Throw In | Sergio Busquets i Burgos | Center Midfield | 129 | Barcelona | nan | 38 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | Tactical | Ivan Rakitić | nan | Barcelona | 00:19:38.805 | Substitution | nan |
## | 3668 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | d2179ee6-e381-4c3a-8c20-d858497b329e | 2906 | nan | nan | 9609 | 71 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 2 | Regular Play | Sergio Enrich Ametller | Center Forward | 144 | Eibar | nan | 25 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | Tactical | Charles Días Barbosa de Oliveira | nan | Eibar | 00:26:25.986 | Substitution | nan |
## | 3669 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | b30c240b-74ee-4a8e-a8f8-6e335605024b | 2993 | nan | nan | 9609 | 73 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 2 | From Throw In | Gerard Deulofeu Lázaro | Right Wing | 149 | Eibar | nan | 44 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | Tactical | Aleix Vidal Parreu | nan | Barcelona | 00:28:44.106 | Substitution | nan |
## | 3670 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | bb629ec7-c862-4ae7-a4b1-177cdeacf14a | 3078 | nan | nan | 9609 | 76 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 2 | Regular Play | Daniel García Carrillo | Right Center Midfield | 152 | Barcelona | nan | 43 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | Tactical | Christian Rivera Hernández | nan | Eibar | 00:31:43.301 | Substitution | nan |
## | 3671 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 3144c78c-751b-4f18-a143-6a6f8bb45856 | 2902 | nan | [15.0, 36.0] | 9609 | 70 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 2 | From Counter | Alejandro Gálvez Jimena | Left Center Back | 143 | Barcelona | nan | 41 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | Eibar | 00:25:41.224 | Error | nan |
## | 3672 | Yellow Card | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | d1e5f981-ed16-46bd-ae46-a164f2ab4eed | 3218 | nan | nan | 9609 | 79 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 2 | Regular Play | Alejandro Gálvez Jimena | Left Center Back | 158 | Barcelona | nan | 52 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | Eibar | 00:34:52.199 | Bad Behaviour | nan |
We have extracted the event data from the Barcelona vs. Eibar match, which Barcelona won 6-1 at home (Camp Nou). Interesting!
Let us now look into the column names of events, such that we can only extract appropriate columns for visualizing and analyzing our convex hulls.
print(events.columns)
## Index(['bad_behaviour_card', 'ball_receipt_outcome',
## 'ball_recovery_recovery_failure', 'block_deflection',
## 'carry_end_location', 'clearance_aerial_won', 'counterpress',
## 'dribble_outcome', 'dribble_overrun', 'duel_outcome', 'duel_type',
## 'duration', 'foul_committed_advantage', 'foul_committed_penalty',
## 'foul_committed_type', 'foul_won_advantage', 'foul_won_defensive',
## 'foul_won_penalty', 'goalkeeper_body_part', 'goalkeeper_end_location',
## 'goalkeeper_outcome', 'goalkeeper_position', 'goalkeeper_technique',
## 'goalkeeper_type', 'id', 'index', 'interception_outcome', 'location',
## 'match_id', 'minute', 'pass_aerial_won', 'pass_angle',
## 'pass_assisted_shot_id', 'pass_backheel', 'pass_body_part',
## 'pass_cross', 'pass_cut_back', 'pass_deflected', 'pass_end_location',
## 'pass_goal_assist', 'pass_height', 'pass_length', 'pass_outcome',
## 'pass_recipient', 'pass_shot_assist', 'pass_switch', 'pass_type',
## 'period', 'play_pattern', 'player', 'position', 'possession',
## 'possession_team', 'related_events', 'second', 'shot_aerial_won',
## 'shot_body_part', 'shot_end_location', 'shot_freeze_frame',
## 'shot_key_pass_id', 'shot_one_on_one', 'shot_outcome', 'shot_redirect',
## 'shot_statsbomb_xg', 'shot_technique', 'shot_type',
## 'substitution_outcome', 'substitution_replacement', 'tactics', 'team',
## 'timestamp', 'type', 'under_pressure'],
## dtype='object')
Now let us pick the important columns from the events dataset:
events_hull = events[['team', 'location', 'type', 'player']]
print(events_hull.head(10).to_markdown())
## | | team | location | type | player |
## |---:|:----------|:-------------|:------------|:-------------------------------|
## | 0 | Barcelona | nan | Starting XI | nan |
## | 1 | Eibar | nan | Starting XI | nan |
## | 2 | Eibar | nan | Half Start | nan |
## | 3 | Barcelona | nan | Half Start | nan |
## | 4 | Barcelona | nan | Half Start | nan |
## | 5 | Eibar | nan | Half Start | nan |
## | 6 | Barcelona | [60.0, 40.0] | Pass | Lionel Andrés Messi Cuccittini |
## | 7 | Barcelona | [46.0, 36.0] | Pass | Sergio Busquets i Burgos |
## | 8 | Barcelona | [56.0, 28.0] | Pass | Andrés Iniesta Luján |
## | 9 | Barcelona | [31.0, 27.0] | Pass | Javier Alejandro Mascherano |
Seems like we only need four columns for now. As we are only focusing on pass and shot events, we will first filter the dataset by setting type to Pass or Shot.
events_hull = events_hull[(events_hull['type'] == 'Pass') | (events_hull['type'] == 'Shot')].reset_index()
print(events_hull.head(10).to_markdown())
## | | index | team | location | type | player |
## |---:|--------:|:----------|:-------------|:-------|:-------------------------------|
## | 0 | 6 | Barcelona | [60.0, 40.0] | Pass | Lionel Andrés Messi Cuccittini |
## | 1 | 7 | Barcelona | [46.0, 36.0] | Pass | Sergio Busquets i Burgos |
## | 2 | 8 | Barcelona | [56.0, 28.0] | Pass | Andrés Iniesta Luján |
## | 3 | 9 | Barcelona | [31.0, 27.0] | Pass | Javier Alejandro Mascherano |
## | 4 | 10 | Barcelona | [32.0, 60.0] | Pass | Gerard Piqué Bernabéu |
## | 5 | 11 | Barcelona | [37.0, 74.0] | Pass | Nélson Cabral Semedo |
## | 6 | 12 | Barcelona | [5.0, 60.0] | Pass | Gerard Piqué Bernabéu |
## | 7 | 13 | Barcelona | [3.0, 37.0] | Pass | Marc-André ter Stegen |
## | 8 | 14 | Barcelona | [9.0, 20.0] | Pass | Javier Alejandro Mascherano |
## | 9 | 15 | Barcelona | [3.0, 39.0] | Pass | Marc-André ter Stegen |
Then, we will split the location column into location_x and location_y columns:
Loc = events_hull['location']
Loc = pd.DataFrame(Loc.to_list(), columns=['location_x', 'location_y'])
events_hull['location_x'] = Loc['location_x']
events_hull['location_y'] = Loc['location_y']
print(events_hull.head(10).to_markdown())
## | | index | team | location | type | player | location_x | location_y |
## |---:|--------:|:----------|:-------------|:-------|:-------------------------------|-------------:|-------------:|
## | 0 | 6 | Barcelona | [60.0, 40.0] | Pass | Lionel Andrés Messi Cuccittini | 60 | 40 |
## | 1 | 7 | Barcelona | [46.0, 36.0] | Pass | Sergio Busquets i Burgos | 46 | 36 |
## | 2 | 8 | Barcelona | [56.0, 28.0] | Pass | Andrés Iniesta Luján | 56 | 28 |
## | 3 | 9 | Barcelona | [31.0, 27.0] | Pass | Javier Alejandro Mascherano | 31 | 27 |
## | 4 | 10 | Barcelona | [32.0, 60.0] | Pass | Gerard Piqué Bernabéu | 32 | 60 |
## | 5 | 11 | Barcelona | [37.0, 74.0] | Pass | Nélson Cabral Semedo | 37 | 74 |
## | 6 | 12 | Barcelona | [5.0, 60.0] | Pass | Gerard Piqué Bernabéu | 5 | 60 |
## | 7 | 13 | Barcelona | [3.0, 37.0] | Pass | Marc-André ter Stegen | 3 | 37 |
## | 8 | 14 | Barcelona | [9.0, 20.0] | Pass | Javier Alejandro Mascherano | 9 | 20 |
## | 9 | 15 | Barcelona | [3.0, 39.0] | Pass | Marc-André ter Stegen | 3 | 39 |
we can discard the location column:
events_hull = events_hull[['team', 'type', 'player', 'location_x', 'location_y']]
We will next split the data into two datasets, one for Barcelona and the other for Eibar:
events_hull_Barca = events_hull[events_hull['team'] == 'Barcelona'].reset_index()
events_hull_Eibar = events_hull[events_hull['team'] == 'Eibar'].reset_index()
Let us look into the first 10 rows of these datasets:
print(events_hull_Barca.head(10).to_markdown())
## | | index | team | type | player | location_x | location_y |
## |---:|--------:|:----------|:-------|:-------------------------------|-------------:|-------------:|
## | 0 | 0 | Barcelona | Pass | Lionel Andrés Messi Cuccittini | 60 | 40 |
## | 1 | 1 | Barcelona | Pass | Sergio Busquets i Burgos | 46 | 36 |
## | 2 | 2 | Barcelona | Pass | Andrés Iniesta Luján | 56 | 28 |
## | 3 | 3 | Barcelona | Pass | Javier Alejandro Mascherano | 31 | 27 |
## | 4 | 4 | Barcelona | Pass | Gerard Piqué Bernabéu | 32 | 60 |
## | 5 | 5 | Barcelona | Pass | Nélson Cabral Semedo | 37 | 74 |
## | 6 | 6 | Barcelona | Pass | Gerard Piqué Bernabéu | 5 | 60 |
## | 7 | 7 | Barcelona | Pass | Marc-André ter Stegen | 3 | 37 |
## | 8 | 8 | Barcelona | Pass | Javier Alejandro Mascherano | 9 | 20 |
## | 9 | 9 | Barcelona | Pass | Marc-André ter Stegen | 3 | 39 |
print(events_hull_Eibar.head(10).to_markdown())
## | | index | team | type | player | location_x | location_y |
## |---:|--------:|:-------|:-------|:----------------------------------|-------------:|-------------:|
## | 0 | 15 | Eibar | Pass | Daniel García Carrillo | 74 | 30 |
## | 1 | 16 | Eibar | Pass | Gonzalo Escalante | 68 | 28 |
## | 2 | 17 | Eibar | Pass | Joan Jordán Moreno | 77 | 30 |
## | 3 | 18 | Eibar | Pass | Daniel García Carrillo | 69 | 42 |
## | 4 | 26 | Eibar | Pass | Gonzalo Escalante | 71 | 13 |
## | 5 | 27 | Eibar | Pass | Sergio Enrich Ametller | 86 | 11 |
## | 6 | 28 | Eibar | Pass | Joan Jordán Moreno | 92 | 6 |
## | 7 | 29 | Eibar | Pass | Takashi Inui | 80 | 10 |
## | 8 | 30 | Eibar | Pass | Daniel García Carrillo | 68 | 31 |
## | 9 | 31 | Eibar | Pass | Paulo André Rodrigues de Oliveira | 48 | 43 |
Next, we will list down the name of the players from both the teams:
players_Barca = events_hull_Barca.player.unique()
players_Eibar = events_hull_Eibar.player.unique()
print(players_Barca)
## ['Lionel Andrés Messi Cuccittini' 'Sergio Busquets i Burgos'
## 'Andrés Iniesta Luján' 'Javier Alejandro Mascherano'
## 'Gerard Piqué Bernabéu' 'Nélson Cabral Semedo' 'Marc-André ter Stegen'
## 'Gerard Deulofeu Lázaro' 'Lucas Digne' 'Denis Suárez Fernández'
## 'José Paulo Bezzera Maciel Júnior' 'Sergi Roberto Carnicer'
## 'Ivan Rakitić' 'Aleix Vidal Parreu']
print(players_Eibar)
## ['Daniel García Carrillo' 'Gonzalo Escalante' 'Joan Jordán Moreno'
## 'Sergio Enrich Ametller' 'Takashi Inui'
## 'Paulo André Rodrigues de Oliveira' 'Anaitz Arbilla Zabala'
## 'Alejandro Gálvez Jimena' 'David Juncà Reñé' 'Marko Dmitrović'
## 'Ander Capa Rodríguez' 'Rubén Peña Jiménez'
## 'Charles Días Barbosa de Oliveira' 'Christian Rivera Hernández']
First we will focus on computing and visualizing the convex hull for a particular player. What can be a better way to pay respect 🙌 🙌 to one of the greatest midfielders of all time 'Andrés Iniesta Luján' than picking him up for the analysis?
We will now extract the event data for Iniesta from events_hull_Barca.
events_hull_iniesta = events_hull_Barca[events_hull_Barca['player'] == 'Andrés Iniesta Luján']
print(events_hull_iniesta.to_markdown())
## | | index | team | type | player | location_x | location_y |
## |----:|--------:|:----------|:-------|:---------------------|-------------:|-------------:|
## | 2 | 2 | Barcelona | Pass | Andrés Iniesta Luján | 56 | 28 |
## | 24 | 35 | Barcelona | Pass | Andrés Iniesta Luján | 53 | 21 |
## | 31 | 42 | Barcelona | Pass | Andrés Iniesta Luján | 72 | 19 |
## | 33 | 44 | Barcelona | Pass | Andrés Iniesta Luján | 84 | 19 |
## | 38 | 53 | Barcelona | Pass | Andrés Iniesta Luján | 52 | 28 |
## | 47 | 66 | Barcelona | Pass | Andrés Iniesta Luján | 52 | 31 |
## | 49 | 74 | Barcelona | Pass | Andrés Iniesta Luján | 64 | 29 |
## | 67 | 103 | Barcelona | Pass | Andrés Iniesta Luján | 66 | 8 |
## | 90 | 154 | Barcelona | Pass | Andrés Iniesta Luján | 54 | 28 |
## | 99 | 167 | Barcelona | Pass | Andrés Iniesta Luján | 70 | 4 |
## | 106 | 174 | Barcelona | Pass | Andrés Iniesta Luján | 56 | 24 |
## | 110 | 178 | Barcelona | Pass | Andrés Iniesta Luján | 79 | 2 |
## | 120 | 189 | Barcelona | Pass | Andrés Iniesta Luján | 40 | 36 |
## | 128 | 199 | Barcelona | Pass | Andrés Iniesta Luján | 87 | 7 |
## | 130 | 201 | Barcelona | Pass | Andrés Iniesta Luján | 80 | 8 |
## | 139 | 225 | Barcelona | Pass | Andrés Iniesta Luján | 37 | 23 |
## | 140 | 240 | Barcelona | Pass | Andrés Iniesta Luján | 48 | 23 |
## | 145 | 245 | Barcelona | Pass | Andrés Iniesta Luján | 97 | 50 |
## | 151 | 259 | Barcelona | Pass | Andrés Iniesta Luján | 42 | 13 |
## | 153 | 261 | Barcelona | Pass | Andrés Iniesta Luján | 66 | 26 |
## | 157 | 266 | Barcelona | Pass | Andrés Iniesta Luján | 44 | 25 |
## | 178 | 301 | Barcelona | Pass | Andrés Iniesta Luján | 90 | 23 |
## | 182 | 311 | Barcelona | Pass | Andrés Iniesta Luján | 34 | 28 |
## | 185 | 315 | Barcelona | Pass | Andrés Iniesta Luján | 60 | 10 |
## | 210 | 375 | Barcelona | Pass | Andrés Iniesta Luján | 54 | 5 |
## | 212 | 377 | Barcelona | Pass | Andrés Iniesta Luján | 34 | 14 |
## | 226 | 413 | Barcelona | Pass | Andrés Iniesta Luján | 39 | 21 |
## | 232 | 419 | Barcelona | Pass | Andrés Iniesta Luján | 69 | 18 |
## | 248 | 435 | Barcelona | Pass | Andrés Iniesta Luján | 92 | 12 |
## | 263 | 459 | Barcelona | Pass | Andrés Iniesta Luján | 64 | 4 |
## | 290 | 499 | Barcelona | Pass | Andrés Iniesta Luján | 44 | 9 |
## | 304 | 536 | Barcelona | Pass | Andrés Iniesta Luján | 62 | 6 |
## | 314 | 546 | Barcelona | Pass | Andrés Iniesta Luján | 71 | 26 |
## | 316 | 548 | Barcelona | Pass | Andrés Iniesta Luján | 68 | 16 |
## | 331 | 574 | Barcelona | Pass | Andrés Iniesta Luján | 49 | 20 |
## | 337 | 581 | Barcelona | Pass | Andrés Iniesta Luján | 50 | 14 |
## | 345 | 589 | Barcelona | Pass | Andrés Iniesta Luján | 51 | 15 |
## | 391 | 680 | Barcelona | Pass | Andrés Iniesta Luján | 52 | 25 |
## | 399 | 688 | Barcelona | Pass | Andrés Iniesta Luján | 101 | 36 |
## | 408 | 699 | Barcelona | Pass | Andrés Iniesta Luján | 81 | 47 |
## | 410 | 701 | Barcelona | Pass | Andrés Iniesta Luján | 83 | 49 |
Before computing and visualizing the convex hull, it is a good practice to discard the outliers from the datasets. A common method that researchers use is the Inter Quartile Range. We will find the inter quartile ranges for the columns location_x and location_y from events_hull_iniesta and then compute the upper and lower bounds of the data. Any points lying beyond these bounds, i.e any point lying above the lower bound and any point lying below the upper bound, are decided to be outliers and are discarded. We use box plots and whisker plots to visualize the interquartile range for the datapoints:
e_box = pd.DataFrame(data = events_hull_iniesta, columns = ["location_x", "location_y"])
boxplot = sns.boxplot(x = "variable", y ="value", data=pd.melt(e_box), order = ["location_x", "location_y"])
boxplot = sns.stripplot(x = "variable", y = "value", data = pd.melt(e_box), marker="o", color="red", order = ["location_x", "location_y"])
boxplot.axes.set_title("Boxplot for Iniesta's location conditions")
plt.show()
We will next compute the quartiles, the inter quartile range and the minimum and maximum values:
Q1 = np.percentile(events_hull_iniesta['location_x'], 25, interpolation='midpoint')
Q3 = np.percentile(events_hull_iniesta['location_x'], 75, interpolation='midpoint')
IQR_x = Q3 - Q1
minimum_x = Q1 - 1.5*IQR_x
maximum_x = Q3 + 1.5*IQR_x
Q1, Q3, IQR_x, minimum_x, maximum_x
## (50.0, 72.0, 22.0, 17.0, 105.0)
Q1 = np.percentile(events_hull_iniesta['location_y'], 25, interpolation='midpoint')
Q3 = np.percentile(events_hull_iniesta['location_y'], 75, interpolation='midpoint')
IQR_y = Q3 - Q1
minimum_y = Q1 - 1.5*IQR_y
maximum_y = Q3 + 1.5*IQR_y
Q1, Q3, IQR_y, minimum_y, maximum_y
## (12.0, 28.0, 16.0, -12.0, 52.0)
upper = np.where((events_hull_iniesta['location_x'] >= maximum_x) & (events_hull_iniesta['location_y'] >= maximum_y))
lower = np.where((events_hull_iniesta['location_x'] <= minimum_x) & (events_hull_iniesta['location_y'] <= minimum_y))
Finally, we will drop the outliers if present:
events_hull_iniesta.drop(upper[0], inplace = True)
events_hull_iniesta.drop(lower[0], inplace = True)
Let us again print the top 10 rows of the events_hull_iniesta dataset:
events_hull_iniesta = events_hull_iniesta.reset_index()
events_hull_iniesta = events_hull_iniesta[['team', 'type', 'player', 'location_x', 'location_y']]
print(events_hull_iniesta.to_markdown())
## | | team | type | player | location_x | location_y |
## |---:|:----------|:-------|:---------------------|-------------:|-------------:|
## | 0 | Barcelona | Pass | Andrés Iniesta Luján | 56 | 28 |
## | 1 | Barcelona | Pass | Andrés Iniesta Luján | 53 | 21 |
## | 2 | Barcelona | Pass | Andrés Iniesta Luján | 72 | 19 |
## | 3 | Barcelona | Pass | Andrés Iniesta Luján | 84 | 19 |
## | 4 | Barcelona | Pass | Andrés Iniesta Luján | 52 | 28 |
## | 5 | Barcelona | Pass | Andrés Iniesta Luján | 52 | 31 |
## | 6 | Barcelona | Pass | Andrés Iniesta Luján | 64 | 29 |
## | 7 | Barcelona | Pass | Andrés Iniesta Luján | 66 | 8 |
## | 8 | Barcelona | Pass | Andrés Iniesta Luján | 54 | 28 |
## | 9 | Barcelona | Pass | Andrés Iniesta Luján | 70 | 4 |
## | 10 | Barcelona | Pass | Andrés Iniesta Luján | 56 | 24 |
## | 11 | Barcelona | Pass | Andrés Iniesta Luján | 79 | 2 |
## | 12 | Barcelona | Pass | Andrés Iniesta Luján | 40 | 36 |
## | 13 | Barcelona | Pass | Andrés Iniesta Luján | 87 | 7 |
## | 14 | Barcelona | Pass | Andrés Iniesta Luján | 80 | 8 |
## | 15 | Barcelona | Pass | Andrés Iniesta Luján | 37 | 23 |
## | 16 | Barcelona | Pass | Andrés Iniesta Luján | 48 | 23 |
## | 17 | Barcelona | Pass | Andrés Iniesta Luján | 97 | 50 |
## | 18 | Barcelona | Pass | Andrés Iniesta Luján | 42 | 13 |
## | 19 | Barcelona | Pass | Andrés Iniesta Luján | 66 | 26 |
## | 20 | Barcelona | Pass | Andrés Iniesta Luján | 44 | 25 |
## | 21 | Barcelona | Pass | Andrés Iniesta Luján | 90 | 23 |
## | 22 | Barcelona | Pass | Andrés Iniesta Luján | 34 | 28 |
## | 23 | Barcelona | Pass | Andrés Iniesta Luján | 60 | 10 |
## | 24 | Barcelona | Pass | Andrés Iniesta Luján | 54 | 5 |
## | 25 | Barcelona | Pass | Andrés Iniesta Luján | 34 | 14 |
## | 26 | Barcelona | Pass | Andrés Iniesta Luján | 39 | 21 |
## | 27 | Barcelona | Pass | Andrés Iniesta Luján | 69 | 18 |
## | 28 | Barcelona | Pass | Andrés Iniesta Luján | 92 | 12 |
## | 29 | Barcelona | Pass | Andrés Iniesta Luján | 64 | 4 |
## | 30 | Barcelona | Pass | Andrés Iniesta Luján | 44 | 9 |
## | 31 | Barcelona | Pass | Andrés Iniesta Luján | 62 | 6 |
## | 32 | Barcelona | Pass | Andrés Iniesta Luján | 71 | 26 |
## | 33 | Barcelona | Pass | Andrés Iniesta Luján | 68 | 16 |
## | 34 | Barcelona | Pass | Andrés Iniesta Luján | 49 | 20 |
## | 35 | Barcelona | Pass | Andrés Iniesta Luján | 50 | 14 |
## | 36 | Barcelona | Pass | Andrés Iniesta Luján | 51 | 15 |
## | 37 | Barcelona | Pass | Andrés Iniesta Luján | 52 | 25 |
## | 38 | Barcelona | Pass | Andrés Iniesta Luján | 101 | 36 |
## | 39 | Barcelona | Pass | Andrés Iniesta Luján | 81 | 47 |
## | 40 | Barcelona | Pass | Andrés Iniesta Luján | 83 | 49 |
First we collect all the points from the two columns as a 2-D matrix. This comes in aid while drawing the convex hull.
points_hull = events_hull_iniesta[['location_x', 'location_y']].values
print(points_hull)
## [[ 56. 28.]
## [ 53. 21.]
## [ 72. 19.]
## [ 84. 19.]
## [ 52. 28.]
## [ 52. 31.]
## [ 64. 29.]
## [ 66. 8.]
## [ 54. 28.]
## [ 70. 4.]
## [ 56. 24.]
## [ 79. 2.]
## [ 40. 36.]
## [ 87. 7.]
## [ 80. 8.]
## [ 37. 23.]
## [ 48. 23.]
## [ 97. 50.]
## [ 42. 13.]
## [ 66. 26.]
## [ 44. 25.]
## [ 90. 23.]
## [ 34. 28.]
## [ 60. 10.]
## [ 54. 5.]
## [ 34. 14.]
## [ 39. 21.]
## [ 69. 18.]
## [ 92. 12.]
## [ 64. 4.]
## [ 44. 9.]
## [ 62. 6.]
## [ 71. 26.]
## [ 68. 16.]
## [ 49. 20.]
## [ 50. 14.]
## [ 51. 15.]
## [ 52. 25.]
## [101. 36.]
## [ 81. 47.]
## [ 83. 49.]]
Now, let us use the ConvexHull() function from scipy.spatial:
convex_hull_iniesta = ConvexHull(events_hull_iniesta[['location_x', 'location_y']])
This convex hull is represented by the vertices, i.e the coordinate points that make the vertices of the convex hull and the simplices, i.e the stratight line in case of a 2-D plane that connects the vertices of the the convex hull. The vertices attribute consists of the indices of the points in points_hull that make up the convex hull, and the simplices attribute too consists of the indices of the points in points_hull. The simplices are a list of 1-D simplices of a particular length, representing line segments in 2-D. Let us print the indices:
print(convex_hull_iniesta.vertices)
## [22 25 30 24 11 13 28 38 17 40 12]
print(convex_hull_iniesta.simplices)
## [[25 22]
## [28 38]
## [12 22]
## [12 40]
## [17 38]
## [17 40]
## [24 11]
## [13 11]
## [13 28]
## [30 25]
## [30 24]]
Now we have collected all the useful information and will visualize the convex hull on a football pitch:
pitch = Pitch(pitch_color='black', line_color='white', goal_type='box',
constrained_layout=True, tight_layout=False)
fig, ax = pitch.draw()
plt.scatter(events_hull_iniesta.location_x, events_hull_iniesta.location_y, color='red')
for i in convex_hull_iniesta.simplices:
plt.plot(points_hull[i, 0], points_hull[i, 1], 'white')
plt.fill(points_hull[convex_hull_iniesta.vertices, 0], points_hull[convex_hull_iniesta.vertices, 1], c='white', alpha=0.1)
plt.title("Convex Hull for Iniesta's field coverage against Eibar")
So, we see that Iniesta mostly covered the left side of Barcelona’s attack on the field. That speaks a lot! Now let us go ahead and compute and visualize the convex hull for all the players in a team
ccodes = ['#FAEBD7', '#66CDAA', '#E3CF57', '#8A2BE2', '#EE3B3B', '#66CD00', '#DC143C', '#FFB90F', '#A9A9A9', '#B23AEE', '#CD1076',
'#8B6914', '#BFEFFF', '#EED2EE', '#C6E2FF', '#C67171']
fig, axes = plt.subplots(6, 3, figsize = (20, 25))
axes = axes.ravel()
for idx, p in enumerate(players_Barca):
pitch = Pitch(pitch_color='black', line_color='white', goal_type='box',
constrained_layout=True, tight_layout=False)
pitch.draw(axes[idx])
xmin, xmax, ymin, ymax = pitch.extent
axes[idx].xaxis.set_ticks([xmin, xmax])
axes[idx].yaxis.set_ticks([ymin, ymax])
axes[idx].tick_params(labelsize=15)
axes[idx].set_title(p, fontsize=20, pad=8)
Eh = events_hull_Barca[events_hull_Barca['player'] == p].reset_index()
Q1 = np.percentile(Eh['location_x'], 25, interpolation='midpoint')
Q3 = np.percentile(Eh['location_x'], 75, interpolation='midpoint')
IQR_x = Q3 - Q1
minimum_x = Q1 - 1.5*IQR_x
maximum_x = Q3 + 1.5*IQR_x
Q1 = np.percentile(Eh['location_y'], 25, interpolation='midpoint')
Q3 = np.percentile(Eh['location_y'], 75, interpolation='midpoint')
IQR_y = Q3 - Q1
minimum_y = Q1 - 1.5*IQR_y
maximum_y = Q3 + 1.5*IQR_y
upper = np.where((Eh['location_x'] >= maximum_x) & (Eh['location_y'] >= maximum_y))
lower = np.where((Eh['location_x'] <= minimum_x) & (Eh['location_y'] <= minimum_y))
Eh.drop(upper[0], inplace = True)
Eh.drop(lower[0], inplace = True)
points_Barca = Eh[['location_x', 'location_y']].values
convex_hull_Barca = ConvexHull(Eh[['location_x', 'location_y']])
axes[idx].scatter(Eh.location_x, Eh.location_y, color='red')
for i in convex_hull_Barca.simplices:
axes[idx].plot(points_Barca[i, 0], points_Barca[i, 1], 'white')
axes[idx].fill(points_Barca[convex_hull_Barca.vertices, 0], points_Barca[convex_hull_Barca.vertices, 1], c=ccodes[idx], alpha=0.1)
title = fig.suptitle("Convex Hulls for Barcelona players' field coverage vs Eibar [La Liga 2017-18]", fontsize=33)
for j in range(len(players_Barca) - 18, 0):
axes[j].remove()
plt.show()
Now, we will compute for Eibar’s team players:
ccodes = ['#FAEBD7', '#66CDAA', '#E3CF57', '#8A2BE2', '#EE3B3B', '#66CD00', '#DC143C', '#FFB90F', '#A9A9A9', '#B23AEE', '#CD1076',
'#8B6914', '#BFEFFF', '#EED2EE', '#C6E2FF', '#C67171']
fig, axes = plt.subplots(6, 3, figsize = (20, 25))
axes = axes.ravel()
for idx, p in enumerate(players_Eibar):
pitch = Pitch(pitch_color='black', line_color='white', goal_type='box',
constrained_layout=True, tight_layout=False)
pitch.draw(axes[idx])
xmin, xmax, ymin, ymax = pitch.extent
axes[idx].xaxis.set_ticks([xmin, xmax])
axes[idx].yaxis.set_ticks([ymin, ymax])
axes[idx].tick_params(labelsize=15)
axes[idx].set_title(p, fontsize=20, pad=8)
Eh = events_hull_Eibar[events_hull_Eibar['player'] == p].reset_index()
Eh['location_x'] = 120 - Eh['location_x']
Q1 = np.percentile(Eh['location_x'], 25, interpolation='midpoint')
Q3 = np.percentile(Eh['location_x'], 75, interpolation='midpoint')
IQR_x = Q3 - Q1
minimum_x = Q1 - 1.5*IQR_x
maximum_x = Q3 + 1.5*IQR_x
Q1 = np.percentile(Eh['location_y'], 25, interpolation='midpoint')
Q3 = np.percentile(Eh['location_y'], 75, interpolation='midpoint')
IQR_y = Q3 - Q1
minimum_y = Q1 - 1.5*IQR_y
maximum_y = Q3 + 1.5*IQR_y
upper = np.where((Eh['location_x'] >= maximum_x) & (Eh['location_y'] >= maximum_y))
lower = np.where((Eh['location_x'] <= minimum_x) & (Eh['location_y'] <= minimum_y))
Eh.drop(upper[0], inplace = True)
Eh.drop(lower[0], inplace = True)
points_Eibar = Eh[['location_x', 'location_y']].values
convex_hull_Eibar = ConvexHull(Eh[['location_x', 'location_y']])
axes[idx].scatter(Eh.location_x, Eh.location_y, color='red')
for i in convex_hull_Eibar.simplices:
axes[idx].plot(points_Eibar[i, 0], points_Eibar[i, 1], 'white')
axes[idx].fill(points_Eibar[convex_hull_Eibar.vertices, 0], points_Eibar[convex_hull_Eibar.vertices, 1], c=ccodes[idx], alpha=0.1)
title = fig.suptitle("Convex Hulls for Eiber players' field coverage vs Barcelona [La Liga 2017-18]", fontsize=33)
for j in range(len(players_Eibar) - 18, 0):
axes[j].remove()
plt.show()
So, we have been able to compute and visualize the convex hulls for players from a particular game. Next, we will try to understand how to get tracking data from a particular game using statsbomb api. We need tracking data to compute Delaunay triangulations and Voronoi diagrams.
Now we need to have access to tracking data which means those data that give us information about the coordinates of all the players on a pitch at a particular instance. It is different to an event data where we only track the coordinate of the ball not all the players. We will use the tracking data from the same game that we have been using in this post for computing Delaunay triangulations and Voronoi diagrams.
Let us remember the match id for the game between Barcelona and Eibar. It was 9609. We need to first import useful classes from the mplsoccer.statsbomb module:
from mplsoccer.statsbomb import read_event, EVENT_SLUG
Next, we will use the code from here to extract the tracking data for the match:
event_json = read_event(f'{EVENT_SLUG}/9609.json', related_event_df = False, tactics_lineup_df = False, warn = False)
event = event_json['event']
tracking = event_json['shot_freeze_frame']
Let us look at the event and tracking datasets:
print(event.head(10).to_markdown())
## | | match_id | id | index | period | timestamp_minute | timestamp_second | timestamp_millisecond | minute | second | type_id | type_name | sub_type_id | sub_type_name | outcome_id | outcome_name | play_pattern_id | play_pattern_name | possession_team_id | possession | possession_team_name | team_id | team_name | player_id | player_name | position_id | position_name | duration | x | y | z | end_x | end_y | end_z | body_part_id | body_part_name | technique_id | technique_name | under_pressure | counterpress | pass_length | pass_angle | pass_recipient_id | pass_recipient_name | pass_height_id | pass_height_name | pass_assisted_shot_id | pass_shot_assist | pass_cross | pass_switch | pass_goal_assist | pass_backheel | pass_cut_back | pass_deflected | bad_behaviour_card_id | bad_behaviour_card_name | ball_recovery_recovery_failure | block_deflection | dribble_overrun | foul_committed_advantage | foul_committed_penalty | foul_committed_type_id | foul_committed_type_name | foul_won_advantage | foul_won_penalty | foul_won_defensive | goalkeeper_position_id | goalkeeper_position_name | shot_one_on_one | shot_statsbomb_xg | shot_key_pass_id | shot_redirect | substitution_replacement_id | substitution_replacement_name | tactics_formation | aerial_won |
## |---:|-----------:|:-------------------------------------|--------:|---------:|-------------------:|-------------------:|------------------------:|---------:|---------:|----------:|:-------------|--------------:|:----------------|-------------:|---------------:|------------------:|:--------------------|---------------------:|-------------:|:-----------------------|----------:|:------------|------------:|:-------------------------------|--------------:|:---------------------|-----------:|----:|----:|----:|--------:|--------:|--------:|---------------:|:-----------------|---------------:|-----------------:|-----------------:|---------------:|--------------:|-------------:|--------------------:|:-------------------------|-----------------:|:-------------------|------------------------:|-------------------:|-------------:|--------------:|-------------------:|----------------:|----------------:|-----------------:|------------------------:|--------------------------:|---------------------------------:|-------------------:|------------------:|---------------------------:|-------------------------:|-------------------------:|---------------------------:|---------------------:|-------------------:|---------------------:|-------------------------:|---------------------------:|------------------:|--------------------:|-------------------:|----------------:|------------------------------:|--------------------------------:|--------------------:|-------------:|
## | 0 | 9609 | 2fc157ab-bb2c-48f7-a099-45411bc6d7db | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 35 | Starting XI | nan | nan | nan | nan | 1 | Regular Play | 217 | 1 | Barcelona | 217 | Barcelona | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 4321 | nan |
## | 1 | 9609 | 57eb014c-03f7-4f4d-a759-1515ea7d97b3 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 35 | Starting XI | nan | nan | nan | nan | 1 | Regular Play | 217 | 1 | Barcelona | 322 | Eibar | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 4231 | nan |
## | 2 | 9609 | 94e0c664-c1e9-4ee7-881e-d81124f3836a | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 18 | Half Start | nan | nan | nan | nan | 1 | Regular Play | 217 | 1 | Barcelona | 322 | Eibar | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
## | 3 | 9609 | 55c6967a-18cc-4ff8-a4be-d0e3915fc22d | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 18 | Half Start | nan | nan | nan | nan | 1 | Regular Play | 217 | 1 | Barcelona | 217 | Barcelona | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
## | 4 | 9609 | 3f6b644f-5ce2-4b89-a912-bfbc05475cbb | 5 | 1 | 0 | 0 | 480 | 0 | 0 | 30 | Pass | 65 | Kick Off | nan | nan | 9 | From Kick Off | 217 | 2 | Barcelona | 217 | Barcelona | 5503 | Lionel Andrés Messi Cuccittini | 23 | Center Forward | 1.07 | 60 | 40 | nan | 49 | 36 | nan | 38 | Left Foot | nan | nan | nan | nan | 11.7047 | -2.79282 | 5203 | Sergio Busquets i Burgos | 1 | Ground Pass | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
## | 5 | 9609 | b8523951-7a5b-4304-a768-cca7c751a9be | 6 | 1 | 0 | 1 | 550 | 0 | 1 | 42 | Ball Receipt | nan | nan | nan | nan | 9 | From Kick Off | 217 | 2 | Barcelona | 217 | Barcelona | 5203 | Sergio Busquets i Burgos | 14 | Center Midfield | nan | 49 | 36 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
## | 6 | 9609 | 20a8f549-ada7-4c9d-9aca-5c49c39dd982 | 7 | 1 | 0 | 1 | 550 | 0 | 1 | 43 | Carry | nan | nan | nan | nan | 9 | From Kick Off | 217 | 2 | Barcelona | 217 | Barcelona | 5203 | Sergio Busquets i Burgos | 14 | Center Midfield | 1.702 | 49 | 36 | nan | 46 | 36 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
## | 7 | 9609 | 8c147c94-859d-446a-9bdf-1d2cd2307007 | 8 | 1 | 0 | 3 | 252 | 0 | 3 | 30 | Pass | nan | nan | nan | nan | 9 | From Kick Off | 217 | 2 | Barcelona | 217 | Barcelona | 5203 | Sergio Busquets i Burgos | 14 | Center Midfield | 0.924 | 46 | 36 | nan | 57 | 28 | nan | 40 | Right Foot | nan | nan | nan | nan | 13.6015 | -0.628796 | 5216 | Andrés Iniesta Luján | 1 | Ground Pass | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
## | 8 | 9609 | 1e11a8d0-7beb-446c-9352-7f336b1703b5 | 9 | 1 | 0 | 4 | 176 | 0 | 4 | 42 | Ball Receipt | nan | nan | nan | nan | 9 | From Kick Off | 217 | 2 | Barcelona | 217 | Barcelona | 5216 | Andrés Iniesta Luján | 15 | Left Center Midfield | nan | 57 | 28 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
## | 9 | 9609 | 464d8065-f758-4b61-b21f-bcebf05fae2f | 10 | 1 | 0 | 4 | 176 | 0 | 4 | 43 | Carry | nan | nan | nan | nan | 9 | From Kick Off | 217 | 2 | Barcelona | 217 | Barcelona | 5216 | Andrés Iniesta Luján | 15 | Left Center Midfield | 0.037 | 57 | 28 | nan | 56 | 28 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
print(event.tail(10).to_markdown())
## | | match_id | id | index | period | timestamp_minute | timestamp_second | timestamp_millisecond | minute | second | type_id | type_name | sub_type_id | sub_type_name | outcome_id | outcome_name | play_pattern_id | play_pattern_name | possession_team_id | possession | possession_team_name | team_id | team_name | player_id | player_name | position_id | position_name | duration | x | y | z | end_x | end_y | end_z | body_part_id | body_part_name | technique_id | technique_name | under_pressure | counterpress | pass_length | pass_angle | pass_recipient_id | pass_recipient_name | pass_height_id | pass_height_name | pass_assisted_shot_id | pass_shot_assist | pass_cross | pass_switch | pass_goal_assist | pass_backheel | pass_cut_back | pass_deflected | bad_behaviour_card_id | bad_behaviour_card_name | ball_recovery_recovery_failure | block_deflection | dribble_overrun | foul_committed_advantage | foul_committed_penalty | foul_committed_type_id | foul_committed_type_name | foul_won_advantage | foul_won_penalty | foul_won_defensive | goalkeeper_position_id | goalkeeper_position_name | shot_one_on_one | shot_statsbomb_xg | shot_key_pass_id | shot_redirect | substitution_replacement_id | substitution_replacement_name | tactics_formation | aerial_won |
## |-----:|-----------:|:-------------------------------------|--------:|---------:|-------------------:|-------------------:|------------------------:|---------:|---------:|----------:|:-------------|--------------:|----------------:|-------------:|:---------------|------------------:|:--------------------|---------------------:|-------------:|:-----------------------|----------:|:------------|------------:|:-------------------------------|--------------:|:---------------------|-----------:|----:|----:|----:|--------:|--------:|--------:|---------------:|:-----------------|---------------:|-----------------:|-----------------:|---------------:|--------------:|-------------:|--------------------:|:-------------------------------|-----------------:|:-------------------|------------------------:|-------------------:|-------------:|--------------:|-------------------:|----------------:|----------------:|-----------------:|------------------------:|--------------------------:|---------------------------------:|-------------------:|------------------:|---------------------------:|-------------------------:|-------------------------:|---------------------------:|---------------------:|-------------------:|---------------------:|-------------------------:|---------------------------:|------------------:|--------------------:|-------------------:|----------------:|------------------------------:|--------------------------------:|--------------------:|-------------:|
## | 3663 | 9609 | a54f7cea-ad06-4a77-bb69-9948fc59e018 | 3664 | 2 | 46 | 53 | 679 | 91 | 53 | 30 | Pass | nan | nan | nan | nan | 1 | Regular Play | 217 | 185 | Barcelona | 217 | Barcelona | 6400 | Aleix Vidal Parreu | 17 | Right Wing | 0.971 | 40 | 62 | nan | 52 | 55 | nan | 40 | Right Foot | nan | nan | nan | nan | 13.8924 | -0.528074 | 5503 | Lionel Andrés Messi Cuccittini | 1 | Ground Pass | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
## | 3664 | 9609 | c28bdd12-4fc7-4727-8d2f-d48f968b5254 | 3665 | 2 | 46 | 54 | 650 | 91 | 54 | 42 | Ball Receipt | nan | nan | nan | nan | 1 | Regular Play | 217 | 185 | Barcelona | 217 | Barcelona | 5503 | Lionel Andrés Messi Cuccittini | 23 | Center Forward | nan | 52 | 55 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
## | 3665 | 9609 | 57a83e09-611d-406d-9a1f-06d815f8617b | 3666 | 2 | 46 | 54 | 650 | 91 | 54 | 43 | Carry | nan | nan | nan | nan | 1 | Regular Play | 217 | 185 | Barcelona | 217 | Barcelona | 5503 | Lionel Andrés Messi Cuccittini | 23 | Center Forward | 4.614 | 52 | 55 | nan | 87 | 29 | nan | nan | nan | nan | nan | 1 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
## | 3666 | 9609 | 6206f189-ee80-41d2-b068-29f29f2f7243 | 3667 | 2 | 46 | 55 | 126 | 91 | 55 | 17 | Pressure | nan | nan | nan | nan | 1 | Regular Play | 217 | 185 | Barcelona | 322 | Eibar | 6712 | Gonzalo Escalante | 15 | Left Center Midfield | 3.615 | 72 | 26 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
## | 3667 | 9609 | f324c3f1-2c28-44f9-a0b8-21c68b3300d0 | 3668 | 2 | 46 | 59 | 264 | 91 | 59 | 30 | Pass | nan | nan | nan | nan | 1 | Regular Play | 217 | 185 | Barcelona | 217 | Barcelona | 5503 | Lionel Andrés Messi Cuccittini | 23 | Center Forward | 3.154 | 87 | 29 | nan | 117 | 14 | nan | 38 | Left Foot | nan | nan | nan | nan | 33.541 | -0.463648 | 6609 | Denis Suárez Fernández | 1 | Ground Pass | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
## | 3668 | 9609 | 7727f912-ccc9-44d3-bfbe-22c36e699152 | 3669 | 2 | 47 | 2 | 418 | 92 | 2 | 42 | Ball Receipt | nan | nan | nan | nan | 1 | Regular Play | 217 | 185 | Barcelona | 217 | Barcelona | 6609 | Denis Suárez Fernández | 21 | Left Wing | nan | 117 | 14 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
## | 3669 | 9609 | 9f82e809-2e1f-4101-aaf8-a359991c5143 | 3670 | 2 | 47 | 2 | 418 | 92 | 2 | 43 | Carry | nan | nan | nan | nan | 1 | Regular Play | 217 | 185 | Barcelona | 217 | Barcelona | 6609 | Denis Suárez Fernández | 21 | Left Wing | 2.248 | 117 | 14 | nan | 116 | 13 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
## | 3670 | 9609 | 22a34ab3-d961-451a-aed9-8f31cfd5e9cb | 3671 | 2 | 47 | 4 | 666 | 92 | 4 | 30 | Pass | nan | nan | 77 | Unknown | 1 | Regular Play | 217 | 185 | Barcelona | 217 | Barcelona | 6609 | Denis Suárez Fernández | 21 | Left Wing | 0.517 | 116 | 13 | nan | 104 | 13 | nan | 40 | Right Foot | nan | nan | nan | nan | 12 | 3.14159 | nan | nan | 1 | Ground Pass | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
## | 3671 | 9609 | efd13f52-219f-44ca-8c7a-18d1aa5829e7 | 3672 | 2 | 47 | 5 | 183 | 92 | 5 | 34 | Half End | nan | nan | nan | nan | 1 | Regular Play | 217 | 185 | Barcelona | 217 | Barcelona | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
## | 3672 | 9609 | fbb9e4ec-27b5-47d0-af0d-f3cdef18cbd7 | 3673 | 2 | 47 | 5 | 183 | 92 | 5 | 34 | Half End | nan | nan | nan | nan | 1 | Regular Play | 217 | 185 | Barcelona | 322 | Eibar | nan | nan | nan | nan | 0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
print(tracking.head(10).to_markdown())
## | | id | event_freeze_id | player_teammate | player_id | player_name | player_position_id | player_position_name | x | y | match_id |
## |---:|:-------------------------------------|------------------:|:------------------|------------:|:-------------------------------|---------------------:|:--------------------------|------:|-----:|-----------:|
## | 0 | 96b9f6dc-1110-4324-b1e5-0bcad3fc19fc | 1 | False | 5203 | Sergio Busquets i Burgos | 14 | Center Midfield | 78.3 | 31.1 | 9609 |
## | 1 | 8a1f787a-6d25-4d3c-9176-f6ef98f6e76d | 1 | True | 6701 | Joan Jordán Moreno | 19 | Center Attacking Midfield | 100.6 | 61.2 | 9609 |
## | 2 | 5824445f-46d1-48db-bc58-e5fa74df6ede | 1 | False | 5203 | Sergio Busquets i Burgos | 14 | Center Midfield | 108 | 44.3 | 9609 |
## | 3 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | 1 | True | 5216 | Andrés Iniesta Luján | 15 | Left Center Midfield | 103.7 | 37.4 | 9609 |
## | 4 | 3d8e877d-7f5b-4073-a192-ea302d6d0f83 | 1 | True | 6712 | Gonzalo Escalante | 15 | Left Center Midfield | 94.7 | 49.3 | 9609 |
## | 5 | c548cbd5-638f-4d40-8793-1fe238ff1114 | 1 | False | 5503 | Lionel Andrés Messi Cuccittini | 23 | Center Forward | 87 | 23.8 | 9609 |
## | 6 | 63b47db1-1681-4749-b6f7-da9748509280 | 1 | False | 5203 | Sergio Busquets i Burgos | 14 | Center Midfield | 95.9 | 52.6 | 9609 |
## | 7 | f4ccfd85-b02a-45b2-8082-207c851c3465 | 1 | True | 6609 | Denis Suárez Fernández | 21 | Left Wing | 102.1 | 27 | 9609 |
## | 8 | ec1db9ef-3db5-4bc5-a80f-0b4cdbded29e | 1 | True | 6609 | Denis Suárez Fernández | 21 | Left Wing | 119 | 3.1 | 9609 |
## | 9 | 5edaf6e5-441c-49e6-9229-e6ad2f0e78a0 | 1 | True | 6701 | Joan Jordán Moreno | 19 | Center Attacking Midfield | 100.7 | 41.5 | 9609 |
print(tracking.tail(10).to_markdown())
## | | id | event_freeze_id | player_teammate | player_id | player_name | player_position_id | player_position_name | x | y | match_id |
## |----:|:-------------------------------------|------------------:|:------------------|------------:|:---------------------------------|---------------------:|:-----------------------|------:|-----:|-----------:|
## | 297 | 81613e34-69c2-42de-a5d5-f180ec5d9d92 | 16 | False | 6698 | Marko Dmitrović | 1 | Goalkeeper | 118.9 | 41.2 | 9609 |
## | 298 | cb6d5031-1551-4557-bee5-4ea238a3ac77 | 16 | False | 6609 | Denis Suárez Fernández | 21 | Left Wing | 100.6 | 53.7 | 9609 |
## | 299 | 5824445f-46d1-48db-bc58-e5fa74df6ede | 17 | False | 6609 | Denis Suárez Fernández | 21 | Left Wing | 103.8 | 34.1 | 9609 |
## | 300 | c548cbd5-638f-4d40-8793-1fe238ff1114 | 17 | True | 6712 | Gonzalo Escalante | 15 | Left Center Midfield | 107.3 | 41.7 | 9609 |
## | 301 | 5edaf6e5-441c-49e6-9229-e6ad2f0e78a0 | 17 | False | 5542 | José Paulo Bezzera Maciel Júnior | 13 | Right Center Midfield | 99.9 | 42.5 | 9609 |
## | 302 | 94f9a7b0-a14b-49be-901f-46ee13531f90 | 17 | False | 5470 | Ivan Rakitić | 14 | Center Midfield | 111.3 | 47 | 9609 |
## | 303 | 81613e34-69c2-42de-a5d5-f180ec5d9d92 | 17 | True | 6849 | Lucas Digne | 6 | Left Back | 91.9 | 17.4 | 9609 |
## | 304 | c548cbd5-638f-4d40-8793-1fe238ff1114 | 18 | False | 5542 | José Paulo Bezzera Maciel Júnior | 13 | Right Center Midfield | 107.5 | 42.4 | 9609 |
## | 305 | 5edaf6e5-441c-49e6-9229-e6ad2f0e78a0 | 18 | False | 5213 | Gerard Piqué Bernabéu | 3 | Right Center Back | 99.9 | 44.1 | 9609 |
## | 306 | 81613e34-69c2-42de-a5d5-f180ec5d9d92 | 18 | False | 5687 | Takashi Inui | 21 | Left Wing | 100.4 | 21.2 | 9609 |
Looking at the two datasets event and tracking, we understand that, the former represents the event data and the later represents the tracking data. Let us look into the columns of the tracking dataset:
print(tracking.columns)
## Index(['id', 'event_freeze_id', 'player_teammate', 'player_id', 'player_name',
## 'player_position_id', 'player_position_name', 'x', 'y', 'match_id'],
## dtype='object')
If we look closely into the tracking dataset, we understand that the column id represents an unique id for a shot freeze frame, i.e, it gives the unique id for the moment when a particular player was taking a shot along with the information about locations of the other players. Looking at the player_name column, we need to add a column team to the tracking dataset, giving us information about which team the shot taker belongs to.
tracking['team'] = 0
for i in range(len(tracking)):
if tracking['player_name'][i] in players_Barca:
tracking['team'][i] = 'Barcelona'
else:
tracking['team'][i] = 'Eibar'
print(tracking.head(10).to_markdown())
## | | id | event_freeze_id | player_teammate | player_id | player_name | player_position_id | player_position_name | x | y | match_id | team |
## |---:|:-------------------------------------|------------------:|:------------------|------------:|:-------------------------------|---------------------:|:--------------------------|------:|-----:|-----------:|:----------|
## | 0 | 96b9f6dc-1110-4324-b1e5-0bcad3fc19fc | 1 | False | 5203 | Sergio Busquets i Burgos | 14 | Center Midfield | 78.3 | 31.1 | 9609 | Barcelona |
## | 1 | 8a1f787a-6d25-4d3c-9176-f6ef98f6e76d | 1 | True | 6701 | Joan Jordán Moreno | 19 | Center Attacking Midfield | 100.6 | 61.2 | 9609 | Eibar |
## | 2 | 5824445f-46d1-48db-bc58-e5fa74df6ede | 1 | False | 5203 | Sergio Busquets i Burgos | 14 | Center Midfield | 108 | 44.3 | 9609 | Barcelona |
## | 3 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | 1 | True | 5216 | Andrés Iniesta Luján | 15 | Left Center Midfield | 103.7 | 37.4 | 9609 | Barcelona |
## | 4 | 3d8e877d-7f5b-4073-a192-ea302d6d0f83 | 1 | True | 6712 | Gonzalo Escalante | 15 | Left Center Midfield | 94.7 | 49.3 | 9609 | Eibar |
## | 5 | c548cbd5-638f-4d40-8793-1fe238ff1114 | 1 | False | 5503 | Lionel Andrés Messi Cuccittini | 23 | Center Forward | 87 | 23.8 | 9609 | Barcelona |
## | 6 | 63b47db1-1681-4749-b6f7-da9748509280 | 1 | False | 5203 | Sergio Busquets i Burgos | 14 | Center Midfield | 95.9 | 52.6 | 9609 | Barcelona |
## | 7 | f4ccfd85-b02a-45b2-8082-207c851c3465 | 1 | True | 6609 | Denis Suárez Fernández | 21 | Left Wing | 102.1 | 27 | 9609 | Barcelona |
## | 8 | ec1db9ef-3db5-4bc5-a80f-0b4cdbded29e | 1 | True | 6609 | Denis Suárez Fernández | 21 | Left Wing | 119 | 3.1 | 9609 | Barcelona |
## | 9 | 5edaf6e5-441c-49e6-9229-e6ad2f0e78a0 | 1 | True | 6701 | Joan Jordán Moreno | 19 | Center Attacking Midfield | 100.7 | 41.5 | 9609 | Eibar |
Now, we will only extract the relevant columns:
tracking = tracking[['id', 'player_name', 'x', 'y', 'team']]
print(tracking.head(10).to_markdown())
## | | id | player_name | x | y | team |
## |---:|:-------------------------------------|:-------------------------------|------:|-----:|:----------|
## | 0 | 96b9f6dc-1110-4324-b1e5-0bcad3fc19fc | Sergio Busquets i Burgos | 78.3 | 31.1 | Barcelona |
## | 1 | 8a1f787a-6d25-4d3c-9176-f6ef98f6e76d | Joan Jordán Moreno | 100.6 | 61.2 | Eibar |
## | 2 | 5824445f-46d1-48db-bc58-e5fa74df6ede | Sergio Busquets i Burgos | 108 | 44.3 | Barcelona |
## | 3 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Andrés Iniesta Luján | 103.7 | 37.4 | Barcelona |
## | 4 | 3d8e877d-7f5b-4073-a192-ea302d6d0f83 | Gonzalo Escalante | 94.7 | 49.3 | Eibar |
## | 5 | c548cbd5-638f-4d40-8793-1fe238ff1114 | Lionel Andrés Messi Cuccittini | 87 | 23.8 | Barcelona |
## | 6 | 63b47db1-1681-4749-b6f7-da9748509280 | Sergio Busquets i Burgos | 95.9 | 52.6 | Barcelona |
## | 7 | f4ccfd85-b02a-45b2-8082-207c851c3465 | Denis Suárez Fernández | 102.1 | 27 | Barcelona |
## | 8 | ec1db9ef-3db5-4bc5-a80f-0b4cdbded29e | Denis Suárez Fernández | 119 | 3.1 | Barcelona |
## | 9 | 5edaf6e5-441c-49e6-9229-e6ad2f0e78a0 | Joan Jordán Moreno | 100.7 | 41.5 | Eibar |
Now, let us try collecting the jersey numbers of the players from both the teams. We will use a different and easier approach from the one we have done here. To get the player information, use the following command, py passing the match id:
player_info = sb.lineups(match_id = 9609)
## credentials were not supplied. open data access only
print(player_info)
## {'Barcelona': player_id player_name ... jersey_number country
## 0 3726 Gerard Deulofeu Lázaro ... 16 Spain
## 1 5203 Sergio Busquets i Burgos ... 5 Spain
## 2 5211 Jordi Alba Ramos ... 18 Spain
## 3 5213 Gerard Piqué Bernabéu ... 3 Spain
## 4 5216 Andrés Iniesta Luján ... 8 Spain
## 5 5246 Luis Alberto Suárez Díaz ... 9 Uruguay
## 6 5470 Ivan Rakitić ... 4 Croatia
## 7 5503 Lionel Andrés Messi Cuccittini ... 10 Argentina
## 8 5506 Javier Alejandro Mascherano ... 14 Argentina
## 9 5542 José Paulo Bezzera Maciel Júnior ... 15 Brazil
## 10 6332 Thomas Vermaelen ... 25 Belgium
## 11 6374 Nélson Cabral Semedo ... 2 Portugal
## 12 6379 Sergi Roberto Carnicer ... 20 Spain
## 13 6400 Aleix Vidal Parreu ... 22 Spain
## 14 6609 Denis Suárez Fernández ... 6 Spain
## 15 6849 Lucas Digne ... 19 France
## 16 8652 Jasper Cillessen ... 13 Netherlands
## 17 20055 Marc-André ter Stegen ... 1 Germany
##
## [18 rows x 5 columns], 'Eibar': player_id player_name ... jersey_number country
## 0 5687 Takashi Inui ... 8 Japan
## 1 6698 Marko Dmitrović ... 25 Serbia
## 2 6699 Ander Capa Rodríguez ... 7 Spain
## 3 6700 Sergio Enrich Ametller ... 9 Spain
## 4 6701 Joan Jordán Moreno ... 24 Spain
## 5 6702 David Rodríguez Lombán ... 22 Spain
## 6 6703 Christian Rivera Hernández ... 6 Spain
## 7 6705 José Ángel Valdés Díaz ... 15 Spain
## 8 6707 Charles Días Barbosa de Oliveira ... 19 Brazil
## 9 6708 Paulo André Rodrigues de Oliveira ... 12 Portugal
## 10 6709 Anaitz Arbilla Zabala ... 18 Spain
## 11 6710 Rubén Peña Jiménez ... 11 Spain
## 12 6712 Gonzalo Escalante ... 5 Argentina
## 13 6775 Daniel García Carrillo ... 14 Spain
## 14 6776 David Juncà Reñé ... 23 Spain
## 15 6924 Alejandro Gálvez Jimena ... 3 Spain
## 16 7900 Tiago Manuel Dias Correia ... 10 Portugal
## 17 10763 Asier Riesgo Unamuno ... 13 Spain
##
## [18 rows x 5 columns]}
We see that player_info has information about both the teams. Let us fetch for Barcelona first:
info_Barca = player_info['Barcelona']
print(info_Barca.to_markdown())
## | | player_id | player_name | player_nickname | jersey_number | country |
## |---:|------------:|:---------------------------------|:----------------------|----------------:|:------------|
## | 0 | 3726 | Gerard Deulofeu Lázaro | Gerard Deulofeu | 16 | Spain |
## | 1 | 5203 | Sergio Busquets i Burgos | Sergio Busquets | 5 | Spain |
## | 2 | 5211 | Jordi Alba Ramos | Jordi Alba | 18 | Spain |
## | 3 | 5213 | Gerard Piqué Bernabéu | Gerard Piqué | 3 | Spain |
## | 4 | 5216 | Andrés Iniesta Luján | Andrés Iniesta | 8 | Spain |
## | 5 | 5246 | Luis Alberto Suárez Díaz | Luis Suárez | 9 | Uruguay |
## | 6 | 5470 | Ivan Rakitić | | 4 | Croatia |
## | 7 | 5503 | Lionel Andrés Messi Cuccittini | Lionel Messi | 10 | Argentina |
## | 8 | 5506 | Javier Alejandro Mascherano | Javier Mascherano | 14 | Argentina |
## | 9 | 5542 | José Paulo Bezzera Maciel Júnior | Paulinho | 15 | Brazil |
## | 10 | 6332 | Thomas Vermaelen | | 25 | Belgium |
## | 11 | 6374 | Nélson Cabral Semedo | Nélson Semedo | 2 | Portugal |
## | 12 | 6379 | Sergi Roberto Carnicer | Sergi Roberto | 20 | Spain |
## | 13 | 6400 | Aleix Vidal Parreu | Aleix Vidal | 22 | Spain |
## | 14 | 6609 | Denis Suárez Fernández | Denis Suárez | 6 | Spain |
## | 15 | 6849 | Lucas Digne | | 19 | France |
## | 16 | 8652 | Jasper Cillessen | | 13 | Netherlands |
## | 17 | 20055 | Marc-André ter Stegen | Marc-André ter Stegen | 1 | Germany |
Let us only consider the player_name and jersey_number columns and build a dictionary:
info_Barca = info_Barca[['player_name', 'jersey_number']]
jerseys_Barca = {}
for i in range(len(info_Barca)):
jerseys_Barca[info_Barca.player_name[i]] = str(info_Barca.jersey_number[i])
print(jerseys_Barca)
## {'Gerard Deulofeu Lázaro': '16', 'Sergio Busquets i Burgos': '5', 'Jordi Alba Ramos': '18', 'Gerard Piqué Bernabéu': '3', 'Andrés Iniesta Luján': '8', 'Luis Alberto Suárez Díaz': '9', 'Ivan Rakitić': '4', 'Lionel Andrés Messi Cuccittini': '10', 'Javier Alejandro Mascherano': '14', 'José Paulo Bezzera Maciel Júnior': '15', 'Thomas Vermaelen': '25', 'Nélson Cabral Semedo': '2', 'Sergi Roberto Carnicer': '20', 'Aleix Vidal Parreu': '22', 'Denis Suárez Fernández': '6', 'Lucas Digne': '19', 'Jasper Cillessen': '13', 'Marc-André ter Stegen': '1'}
Let us perform the same operations on Eibar:
info_Eibar= player_info['Eibar']
print(info_Eibar.to_markdown())
## | | player_id | player_name | player_nickname | jersey_number | country |
## |---:|------------:|:----------------------------------|:------------------|----------------:|:----------|
## | 0 | 5687 | Takashi Inui | | 8 | Japan |
## | 1 | 6698 | Marko Dmitrović | | 25 | Serbia |
## | 2 | 6699 | Ander Capa Rodríguez | Ander Capa | 7 | Spain |
## | 3 | 6700 | Sergio Enrich Ametller | Sergi Enrich | 9 | Spain |
## | 4 | 6701 | Joan Jordán Moreno | Joan Jordán | 24 | Spain |
## | 5 | 6702 | David Rodríguez Lombán | David Lombán | 22 | Spain |
## | 6 | 6703 | Christian Rivera Hernández | Christian Rivera | 6 | Spain |
## | 7 | 6705 | José Ángel Valdés Díaz | Cote | 15 | Spain |
## | 8 | 6707 | Charles Días Barbosa de Oliveira | Charles | 19 | Brazil |
## | 9 | 6708 | Paulo André Rodrigues de Oliveira | Paulo Oliveira | 12 | Portugal |
## | 10 | 6709 | Anaitz Arbilla Zabala | Anaitz Arbilla | 18 | Spain |
## | 11 | 6710 | Rubén Peña Jiménez | Rubén Peña | 11 | Spain |
## | 12 | 6712 | Gonzalo Escalante | | 5 | Argentina |
## | 13 | 6775 | Daniel García Carrillo | Dani García | 14 | Spain |
## | 14 | 6776 | David Juncà Reñé | David Juncà | 23 | Spain |
## | 15 | 6924 | Alejandro Gálvez Jimena | Alejandro Gálvez | 3 | Spain |
## | 16 | 7900 | Tiago Manuel Dias Correia | Bebé | 10 | Portugal |
## | 17 | 10763 | Asier Riesgo Unamuno | Asier Riesgo | 13 | Spain |
info_Eibar = info_Eibar[['player_name', 'jersey_number']]
jerseys_Eibar = {}
for i in range(len(info_Eibar)):
jerseys_Eibar[info_Eibar.player_name[i]] = str(info_Eibar.jersey_number[i])
print(jerseys_Eibar)
## {'Takashi Inui': '8', 'Marko Dmitrović': '25', 'Ander Capa Rodríguez': '7', 'Sergio Enrich Ametller': '9', 'Joan Jordán Moreno': '24', 'David Rodríguez Lombán': '22', 'Christian Rivera Hernández': '6', 'José Ángel Valdés Díaz': '15', 'Charles Días Barbosa de Oliveira': '19', 'Paulo André Rodrigues de Oliveira': '12', 'Anaitz Arbilla Zabala': '18', 'Rubén Peña Jiménez': '11', 'Gonzalo Escalante': '5', 'Daniel García Carrillo': '14', 'David Juncà Reñé': '23', 'Alejandro Gálvez Jimena': '3', 'Tiago Manuel Dias Correia': '10', 'Asier Riesgo Unamuno': '13'}
Now let us select a particular id from the tracking dataset, representing an instance when a particular shot was taken. We will filter tracking by a id value which will give us the information of the locations of the players on the pitch at that moment. We can view the unique id values:
print(tracking.id.unique())
## ['96b9f6dc-1110-4324-b1e5-0bcad3fc19fc'
## '8a1f787a-6d25-4d3c-9176-f6ef98f6e76d'
## '5824445f-46d1-48db-bc58-e5fa74df6ede'
## 'c3ce55fe-26f8-4e63-b269-ea01f99ff438'
## '3d8e877d-7f5b-4073-a192-ea302d6d0f83'
## 'c548cbd5-638f-4d40-8793-1fe238ff1114'
## '63b47db1-1681-4749-b6f7-da9748509280'
## 'f4ccfd85-b02a-45b2-8082-207c851c3465'
## 'ec1db9ef-3db5-4bc5-a80f-0b4cdbded29e'
## '5edaf6e5-441c-49e6-9229-e6ad2f0e78a0'
## '9dd385a8-05be-4c8a-af1a-909b9680c861'
## '083f5ff5-10ed-4a80-8e33-da20d60d3050'
## '6fedebfb-1dcc-4433-b4c3-4014776c0c31'
## 'bfc236db-10d8-45cc-b558-f46e0bb79150'
## 'cce4b5bd-1621-4e3c-b6e5-c4b372ef43bf'
## 'b04ab23d-f5db-4f7b-8185-24f6e85c027d'
## 'deb8da4c-d3b8-4890-8a2f-53d3665a2436'
## '94f9a7b0-a14b-49be-901f-46ee13531f90'
## '81613e34-69c2-42de-a5d5-f180ec5d9d92'
## '8d160e73-12d8-46b4-a862-0ab0cda437d5'
## '21c8df3d-7144-4248-86b2-dbd566f589fa'
## 'cb6d5031-1551-4557-bee5-4ea238a3ac77'
## 'dffb74af-f4de-4576-995b-8918ab485a18'
## '412d1446-58bc-4e5f-9843-157591657f2e'
## '55010d43-f0df-48cc-a6de-ffa30d31dbd1']
Let us filter the dataset now:
shot_id = 'c3ce55fe-26f8-4e63-b269-ea01f99ff438' # select a particular value from the id column
#shot_id = 'ec1db9ef-3db5-4bc5-a80f-0b4cdbded29e'
tracking_filtered = tracking[tracking['id'] == shot_id] # filter by the shot_id
event_filtered = event[event['id'] == shot_id]
print(tracking_filtered.to_markdown())
## | | id | player_name | x | y | team |
## |----:|:-------------------------------------|:----------------------------------|------:|-----:|:----------|
## | 3 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Andrés Iniesta Luján | 103.7 | 37.4 | Barcelona |
## | 28 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | José Paulo Bezzera Maciel Júnior | 103.1 | 23.5 | Barcelona |
## | 53 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Gonzalo Escalante | 102.9 | 32.4 | Eibar |
## | 78 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Ander Capa Rodríguez | 98.8 | 42 | Eibar |
## | 103 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Paulo André Rodrigues de Oliveira | 102.6 | 41.2 | Eibar |
## | 128 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Daniel García Carrillo | 98.6 | 44.6 | Eibar |
## | 153 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Takashi Inui | 93.5 | 56.2 | Eibar |
## | 177 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Denis Suárez Fernández | 103.7 | 48.5 | Barcelona |
## | 199 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | David Juncà Reñé | 103.8 | 51.4 | Eibar |
## | 221 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Alejandro Gálvez Jimena | 102.7 | 44.5 | Eibar |
## | 242 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Marko Dmitrović | 118.4 | 39.7 | Eibar |
## | 257 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Gerard Deulofeu Lázaro | 103.8 | 56.4 | Barcelona |
event_filtered = event_filtered[['id', 'player_name', 'x', 'y', 'team_name']]
event_filtered = event_filtered.rename(columns = {'team_name':'team'})
print(event_filtered.to_markdown())
## | | id | player_name | x | y | team |
## |-----:|:-------------------------------------|:-------------------------------|----:|-----:|:----------|
## | 1094 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Lionel Andrés Messi Cuccittini | 97 | 45.4 | Barcelona |
data_filtered = pd.concat([event_filtered, tracking_filtered])
print(data_filtered.to_markdown())
## | | id | player_name | x | y | team |
## |-----:|:-------------------------------------|:----------------------------------|------:|-----:|:----------|
## | 1094 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Lionel Andrés Messi Cuccittini | 97 | 45.4 | Barcelona |
## | 3 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Andrés Iniesta Luján | 103.7 | 37.4 | Barcelona |
## | 28 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | José Paulo Bezzera Maciel Júnior | 103.1 | 23.5 | Barcelona |
## | 53 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Gonzalo Escalante | 102.9 | 32.4 | Eibar |
## | 78 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Ander Capa Rodríguez | 98.8 | 42 | Eibar |
## | 103 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Paulo André Rodrigues de Oliveira | 102.6 | 41.2 | Eibar |
## | 128 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Daniel García Carrillo | 98.6 | 44.6 | Eibar |
## | 153 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Takashi Inui | 93.5 | 56.2 | Eibar |
## | 177 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Denis Suárez Fernández | 103.7 | 48.5 | Barcelona |
## | 199 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | David Juncà Reñé | 103.8 | 51.4 | Eibar |
## | 221 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Alejandro Gálvez Jimena | 102.7 | 44.5 | Eibar |
## | 242 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Marko Dmitrović | 118.4 | 39.7 | Eibar |
## | 257 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Gerard Deulofeu Lázaro | 103.8 | 56.4 | Barcelona |
So, we notice that, tracking_filtered is a tracking data from the instance when Messi was taking a shot. We will compute the Delaunay triangulations from Barcelona’s players' locations to get an idea about the possible links created among the teammates by the placement of the players from Barcelona.
This
wikipedia article states that for a set X consisting of points on a 2-D Euclidean surface, a Delaunay triangulation is a type of geometric triangulation such that no points in X lies inside the circum-circle of any triangle in the triangulation. A representation of the Delaunay triangle from the same wikipedia article:
We also need to import Delaunay from scipy.spatial to compute the triangulation:
from scipy.spatial import Delaunay
Next, let us separate the data_filtered for the teams:
tracking_Barca = data_filtered[data_filtered['team'] == 'Barcelona'].reset_index()
tracking_Eibar = data_filtered[data_filtered['team'] == 'Eibar'].reset_index()
print(tracking_Barca.to_markdown())
## | | index | id | player_name | x | y | team |
## |---:|--------:|:-------------------------------------|:---------------------------------|------:|-----:|:----------|
## | 0 | 1094 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Lionel Andrés Messi Cuccittini | 97 | 45.4 | Barcelona |
## | 1 | 3 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Andrés Iniesta Luján | 103.7 | 37.4 | Barcelona |
## | 2 | 28 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | José Paulo Bezzera Maciel Júnior | 103.1 | 23.5 | Barcelona |
## | 3 | 177 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Denis Suárez Fernández | 103.7 | 48.5 | Barcelona |
## | 4 | 257 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Gerard Deulofeu Lázaro | 103.8 | 56.4 | Barcelona |
print(tracking_Eibar.to_markdown())
## | | index | id | player_name | x | y | team |
## |---:|--------:|:-------------------------------------|:----------------------------------|------:|-----:|:-------|
## | 0 | 53 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Gonzalo Escalante | 102.9 | 32.4 | Eibar |
## | 1 | 78 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Ander Capa Rodríguez | 98.8 | 42 | Eibar |
## | 2 | 103 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Paulo André Rodrigues de Oliveira | 102.6 | 41.2 | Eibar |
## | 3 | 128 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Daniel García Carrillo | 98.6 | 44.6 | Eibar |
## | 4 | 153 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Takashi Inui | 93.5 | 56.2 | Eibar |
## | 5 | 199 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | David Juncà Reñé | 103.8 | 51.4 | Eibar |
## | 6 | 221 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Alejandro Gálvez Jimena | 102.7 | 44.5 | Eibar |
## | 7 | 242 | c3ce55fe-26f8-4e63-b269-ea01f99ff438 | Marko Dmitrović | 118.4 | 39.7 | Eibar |
Now, we are going to build the Delaunay triangulations for Barcelona’s attack at the particular instance. Similar to the one we did for Convex hulls, we will first convert the locations of the players into a 2-D matrix:
points_Barca = tracking_Barca[['x', 'y']].values
print(points_Barca)
## [[ 97. 45.4]
## [103.7 37.4]
## [103.1 23.5]
## [103.7 48.5]
## [103.8 56.4]]
Then, we compute the triangulations:
del_Barca = Delaunay(tracking_Barca[['x', 'y']])
We will create two more datasets for aiding us with annotating the jersey number of the players on their respective nodes while visualizing the players on the pitch
loc_Barca = tracking_Barca[['player_name','x', 'y']].reset_index()
loc_Eibar = tracking_Eibar[['player_name','x', 'y']].reset_index()
print(loc_Barca.to_markdown())
## | | index | player_name | x | y |
## |---:|--------:|:---------------------------------|------:|-----:|
## | 0 | 0 | Lionel Andrés Messi Cuccittini | 97 | 45.4 |
## | 1 | 1 | Andrés Iniesta Luján | 103.7 | 37.4 |
## | 2 | 2 | José Paulo Bezzera Maciel Júnior | 103.1 | 23.5 |
## | 3 | 3 | Denis Suárez Fernández | 103.7 | 48.5 |
## | 4 | 4 | Gerard Deulofeu Lázaro | 103.8 | 56.4 |
print(loc_Eibar.to_markdown())
## | | index | player_name | x | y |
## |---:|--------:|:----------------------------------|------:|-----:|
## | 0 | 0 | Gonzalo Escalante | 102.9 | 32.4 |
## | 1 | 1 | Ander Capa Rodríguez | 98.8 | 42 |
## | 2 | 2 | Paulo André Rodrigues de Oliveira | 102.6 | 41.2 |
## | 3 | 3 | Daniel García Carrillo | 98.6 | 44.6 |
## | 4 | 4 | Takashi Inui | 93.5 | 56.2 |
## | 5 | 5 | David Juncà Reñé | 103.8 | 51.4 |
## | 6 | 6 | Alejandro Gálvez Jimena | 102.7 | 44.5 |
## | 7 | 7 | Marko Dmitrović | 118.4 | 39.7 |
Finally, we visualize the triangulations and the players' positions at that instance on the pitch:
pitch = Pitch(pitch_color='grass', stripe=True, line_color='white', view = 'half', figsize=(15,16),
constrained_layout=True, tight_layout=False, goal_type='box')
fig, ax = pitch.draw()
plt.scatter(tracking_Barca.x, tracking_Barca.y, color='red', s = 850, edgecolors='black', zorder=2)
plt.scatter(tracking_Eibar.x, tracking_Eibar.y, color='blue', edgecolors='black', s = 850)
plt.triplot(points_Barca[:, 0], points_Barca[:, 1], del_Barca.simplices.copy(), 'k-', lw = 4)
for index, row in loc_Barca.iterrows():
pitch.annotate(jerseys_Barca[loc_Barca['player_name'][row.name]], xy=(row.x, row.y), c ='black', va = 'center', ha = 'center', size = 15, ax = ax)
for index, row in loc_Eibar.iterrows():
pitch.annotate(jerseys_Eibar[loc_Eibar['player_name'][row.name]], xy=(row.x, row.y), c ='black', va = 'center', ha = 'center', size = 15, ax = ax)
plt.show()
The red nodes indicate locations of Barcelona’s players and the blue nodes indicate that of Eibar’s. The black lines indicate the direct links between the players from a particular team at a particular moment, forming the Delaunay triangulations, also called the pass triangulations. In his book Soccematics, Dr. Sumpter mentions that these lines have two useful indications: first, they portray the availability of passes among the players from a particular team, and second, they also indicate the “no man’s lines” for the players from the opposition team, meaning, if an opposition player is on one of these linking lines, then they are at a disadvantage. Beautiful implementation of computational geometry, isn’t it?
In the last part of this tutorial, we will compute the Voronoi diagrams for the players at the same instance on which we have just computed the Delaunay triangulations. The Voronoi diagrams help us visualize the zones of each player on the pitch at a particular moment of gameplay. Mathematically, Voronoi diagrams for a set X of points, denote the partitions of a 2-D Euclidean space into regions that are close to each of these points. Look at this wikipedia article to study more on Voronoi diagrams. The Delaunay triangulation and the Voronoi diagrams are inter-related in the way that they are dual to each other, i.e, the circum-centers of of Delaunay triangles are the vertices of the Voronoi diagram for the set of points X. Look at the image of a Voronoi diagram (taken from here), which is the dual of the Delaunay triangulation that is shown above.
For computing the Voronoi diagrams, remember to use the data_filtered dataset, because we need the location of all the players on the pitch. To compute and visualize the Voronoi diagrams, we need to import Voronoi for computing the Voronoi diagrams and voronoi_plot_2d to plot the diagrams on a pitch.
from scipy.spatial import Voronoi, voronoi_plot_2d
Next we extract the locations as points from data_filtered and compute the Voronoi diagrams:
data_filtered['y'] = 80 - data_filtered['y']
points = data_filtered[['x', 'y']].values
vor = Voronoi(points)
Finally, we visualize the computed diagrams:
pitch = Pitch(pitch_color='grass', stripe=True, line_color='white', view = 'half', figsize=(15,16),
constrained_layout=True, tight_layout=False, goal_type='box')
fig, ax = pitch.draw()
plt.scatter(tracking_Barca.x, 80 - tracking_Barca.y, color='red', s = 1050, edgecolors='black', zorder=2)
plt.scatter(tracking_Eibar.x, 80 -tracking_Eibar.y, color='blue', edgecolors='black', s = 1050)
pl = voronoi_plot_2d(vor, ax=ax, show_vertices=False, line_width = 8, line_alpha = 0.3)
for index, row in loc_Barca.iterrows():
pitch.annotate(jerseys_Barca[loc_Barca['player_name'][row.name]], xy=(row.x, 80 - row.y), c ='black', va = 'center', ha = 'center', size = 15, ax = ax)
for index, row in loc_Eibar.iterrows():
pitch.annotate(jerseys_Eibar[loc_Eibar['player_name'][row.name]], xy=(row.x, 80 - row.y), c ='black', va = 'center', ha = 'center', size = 15, ax = ax)
plt.show()
So, the Voronoi diagrams give us the zones of each and every player on the pitch at a particular moment by breaking the pitch into distinct regions belonging to the players indicating the field covergae of each player at that moment. This completes our tutorial on implementational of computational geometric concepts on football event and tracking data.
Next post, we will learn how to access football statistical and historical data from FBREF.
