Animation

This example shows how to animate tracking data from metricasports.

import numpy as np
import pandas as pd
from matplotlib import animation
from matplotlib import pyplot as plt

from mplsoccer import Pitch

Load the data

# load away data
LINK1 = ('https://raw.githubusercontent.com/metrica-sports/sample-data/master/'
         'data/Sample_Game_1/Sample_Game_1_RawTrackingData_Away_Team.csv')
df_away = pd.read_csv(LINK1, skiprows=2)
df_away.sort_values('Time [s]', inplace=True)

# load home data
LINK2 = ('https://raw.githubusercontent.com/metrica-sports/sample-data/master/'
         'data/Sample_Game_1/Sample_Game_1_RawTrackingData_Home_Team.csv')
df_home = pd.read_csv(LINK2, skiprows=2)
df_home.sort_values('Time [s]', inplace=True)

Reset the column names

# column names aren't great so this sets the player ones with _x and _y suffixes


def set_col_names(df):
    """ Renames the columns to have x and y suffixes."""
    cols = list(np.repeat(df.columns[3::2], 2))
    cols = [col+'_x' if i % 2 == 0 else col+'_y' for i, col in enumerate(cols)]
    cols = np.concatenate([df.columns[:3], cols])
    df.columns = cols


set_col_names(df_away)
set_col_names(df_home)

Subset 2 seconds of data

# get a subset of the data (10 seconds)
df_away = df_away[(df_away['Time [s]'] >= 815) & (df_away['Time [s]'] < 825)].copy()
df_home = df_home[(df_home['Time [s]'] >= 815) & (df_home['Time [s]'] < 825)].copy()

Split off the ball data, and drop the ball columns from the df_away/ df_home dataframes

# split off a df_ball dataframe and drop the ball columns from the player dataframes
df_ball = df_away[['Period', 'Frame', 'Time [s]', 'Ball_x', 'Ball_y']].copy()
df_home.drop(['Ball_x', 'Ball_y'], axis=1, inplace=True)
df_away.drop(['Ball_x', 'Ball_y'], axis=1, inplace=True)
df_ball.rename({'Ball_x': 'x', 'Ball_y': 'y'}, axis=1, inplace=True)

Convert to long form. So each row is a single player’s coordinates for a single frame

# convert to long form from wide form
def to_long_form(df):
    """ Pivots a dataframe from wide-form (each player as a separate column) to long form (rows)"""
    df = pd.melt(df, id_vars=df.columns[:3], value_vars=df.columns[3:], var_name='player')
    df.loc[df.player.str.contains('_x'), 'coordinate'] = 'x'
    df.loc[df.player.str.contains('_y'), 'coordinate'] = 'y'
    df = df.dropna(axis=0, how='any')
    df['player'] = df.player.str[6:-2]
    df = (df.set_index(['Period', 'Frame', 'Time [s]', 'player', 'coordinate'])['value']
          .unstack()
          .reset_index()
          .rename_axis(None, axis=1))
    return df


df_away = to_long_form(df_away)
df_home = to_long_form(df_home)

Show the away data

df_away.head()
Period Frame Time [s] player x y
0 1 20375 815.0 15 0.52333 0.15093
1 1 20375 815.0 16 0.52972 0.31205
2 1 20375 815.0 17 0.48127 0.45092
3 1 20375 815.0 18 0.38463 0.04628
4 1 20375 815.0 19 0.25890 0.07167


Show the home data

df_home.head()
Period Frame Time [s] player x y
0 1 20375 815.0 1 0.18914 0.51216
1 1 20375 815.0 10 0.39725 0.27164
2 1 20375 815.0 11 0.05056 0.44912
3 1 20375 815.0 2 0.18825 0.38918
4 1 20375 815.0 3 0.21617 0.21615


Show the ball data

df_ball.head()
Period Frame Time [s] x y
20374 1 20375 815.00 0.24042 0.11311
20375 1 20376 815.04 0.23729 0.11115
20376 1 20377 815.08 0.23415 0.10919
20377 1 20378 815.12 0.23102 0.10723
20378 1 20379 815.16 0.22789 0.10528


Plot the animation

# First set up the figure, the axis
pitch = Pitch(pitch_type='metricasports', goal_type='line', pitch_width=68, pitch_length=105)
fig, ax = pitch.draw(figsize=(16, 10.4))

# then setup the pitch plot markers we want to animate
marker_kwargs = {'marker': 'o', 'markeredgecolor': 'black', 'linestyle': 'None'}
ball, = ax.plot([], [], ms=6, markerfacecolor='w', zorder=3, **marker_kwargs)
away, = ax.plot([], [], ms=10, markerfacecolor='#b94b75', **marker_kwargs)  # red/maroon
home, = ax.plot([], [], ms=10, markerfacecolor='#7f63b8', **marker_kwargs)  # purple


# animation function
def animate(i):
    """ Function to animate the data. Each frame it sets the data for the players and the ball."""
    # set the ball data with the x and y positions for the ith frame
    ball.set_data(df_ball.iloc[i, [3]], df_ball.iloc[i, [4]])
    # get the frame id for the ith frame
    frame = df_ball.iloc[i, 1]
    # set the player data using the frame id
    away.set_data(df_away.loc[df_away.Frame == frame, 'x'],
                  df_away.loc[df_away.Frame == frame, 'y'])
    home.set_data(df_home.loc[df_home.Frame == frame, 'x'],
                  df_home.loc[df_home.Frame == frame, 'y'])
    return ball, away, home


# call the animator, animate so 25 frames per second
anim = animation.FuncAnimation(fig, animate, frames=len(df_ball), interval=50, blit=True)
plt.show()

# note that its hard to get the ffmpeg requirements right.
# I installed from conda-forge: see the environment.yml file in the docs folder
# how to save animation - commented out for example
# anim.save('example.mp4', dpi=150, fps=25,
#          extra_args=['-vcodec', 'libx264'],
#          savefig_kwargs={'pad_inches':0, 'facecolor':'#457E29'})