Pass plot using lines

This example shows how to plot all passes from a team in a match as lines.

import matplotlib.pyplot as plt
from matplotlib import rcParams

from mplsoccer import Pitch, VerticalPitch, FontManager, Sbopen

rcParams['text.color'] = '#c7d5cc'  # set the default text color

# get event dataframe for game 7478
parser = Sbopen()
df, related, freeze, tactics = parser.event(7478)

Boolean mask for filtering the dataset by team

team1, team2 = df.team_name.unique()
mask_team1 = (df.type_name == 'Pass') & (df.team_name == team1)

Filter dataset to only include one teams passes and get boolean mask for the completed passes

df_pass = df.loc[mask_team1, ['x', 'y', 'end_x', 'end_y', 'outcome_name']]
mask_complete = df_pass.outcome_name.isnull()

View the pass dataframe.

df_pass.head()
x y end_x end_y outcome_name
20 11.0 80.0 29.0 68.0 NaN
22 29.0 67.0 58.0 80.0 Out
28 56.0 68.0 75.0 77.0 NaN
37 95.0 80.0 110.0 56.0 NaN
40 109.0 56.0 106.0 54.0 Incomplete


Plotting

# Setup the pitch
pitch = Pitch(pitch_type='statsbomb', pitch_color='#22312b', line_color='#c7d5cc')
fig, ax = pitch.draw(figsize=(16, 11), constrained_layout=False, tight_layout=True)
fig.set_facecolor('#22312b')

# Plot the completed passes
lc1 = pitch.lines(df_pass[mask_complete].x, df_pass[mask_complete].y,
                  df_pass[mask_complete].end_x, df_pass[mask_complete].end_y,
                  lw=5, transparent=True, comet=True, label='completed passes',
                  color='#ad993c', ax=ax)

# Plot the other passes
lc2 = pitch.lines(df_pass[~mask_complete].x, df_pass[~mask_complete].y,
                  df_pass[~mask_complete].end_x, df_pass[~mask_complete].end_y,
                  lw=5, transparent=True, comet=True, label='other passes',
                  color='#ba4f45', ax=ax)

# Plot the legend
ax.legend(facecolor='#22312b', edgecolor='None', fontsize=20, loc='upper left', handlelength=4)

# Set the title
ax_title = ax.set_title(f'{team1} passes vs {team2}', fontsize=30)
OL Reign passes vs Houston Dash

Plotting with grid. We will use mplsoccer’s grid function to plot a pitch with a title and endnote axes.

fig, axs = pitch.grid(endnote_height=0.03, endnote_space=0, figheight=12,
                      title_height=0.06, title_space=0,
                      # Turn off the endnote/title axis. I usually do this after
                      # I am happy with the chart layout and text placement
                      axis=False,
                      grid_height=0.86)
fig.set_facecolor('#22312b')

# Plot the completed passes
lc1 = pitch.lines(df_pass[mask_complete].x, df_pass[mask_complete].y,
                  df_pass[mask_complete].end_x, df_pass[mask_complete].end_y,
                  lw=5, transparent=True, comet=True, label='completed passes',
                  color='#ad993c', ax=axs['pitch'])

# Plot the other passes
lc2 = pitch.lines(df_pass[~mask_complete].x, df_pass[~mask_complete].y,
                  df_pass[~mask_complete].end_x, df_pass[~mask_complete].end_y,
                  lw=5, transparent=True, comet=True, label='other passes',
                  color='#ba4f45', ax=axs['pitch'])

# fontmanager for google font (robotto)
robotto_regular = FontManager()

# setup the legend
legend = axs['pitch'].legend(facecolor='#22312b', handlelength=5, edgecolor='None',
                             prop=robotto_regular.prop, loc='upper left')
for text in legend.get_texts():
    text.set_fontsize(25)

# endnote and title
axs['endnote'].text(1, 0.5, '@your_twitter_handle', va='center', ha='right', fontsize=20,
                    fontproperties=robotto_regular.prop, color='#dee6ea')
ax_title = axs['title'].text(0.5, 0.5, f'{team1} passes vs {team2}', color='#dee6ea',
                             va='center', ha='center',
                             fontproperties=robotto_regular.prop, fontsize=25)
plot lines

Filter datasets to only include passes leading to shots, and goals

TEAM1 = 'OL Reign'
TEAM2 = 'Houston Dash'
df_pass = df.loc[(df.pass_assisted_shot_id.notnull()) & (df.team_name == TEAM1),
                 ['x', 'y', 'end_x', 'end_y', 'pass_assisted_shot_id']]

df_shot = (df.loc[(df.type_name == 'Shot') & (df.team_name == TEAM1),
                  ['id', 'outcome_name', 'shot_statsbomb_xg']]
           .rename({'id': 'pass_assisted_shot_id'}, axis=1))

df_pass = df_pass.merge(df_shot, how='left').drop('pass_assisted_shot_id', axis=1)

mask_goal = df_pass.outcome_name == 'Goal'

This example shows how to plot all passes leading to shots from a team using a colormap (cmap).

# Setup the pitch
pitch = VerticalPitch(pitch_type='statsbomb', pitch_color='#22312b', line_color='#c7d5cc',
                      half=True, pad_top=2)
fig, axs = pitch.grid(endnote_height=0.03, endnote_space=0, figheight=12,
                      title_height=0.08, title_space=0, axis=False,
                      grid_height=0.82)
fig.set_facecolor('#22312b')

# Plot the completed passes
pitch.lines(df_pass.x, df_pass.y, df_pass.end_x, df_pass.end_y,
            lw=10, transparent=True, comet=True, cmap='jet',
            label='pass leading to shot', ax=axs['pitch'])

# Plot the goals
pitch.scatter(df_pass[mask_goal].end_x, df_pass[mask_goal].end_y, s=700,
              marker='football', edgecolors='black', c='white', zorder=2,
              label='goal', ax=axs['pitch'])
pitch.scatter(df_pass[~mask_goal].end_x, df_pass[~mask_goal].end_y,
              edgecolors='white', c='#22312b', s=700, zorder=2,
              label='shot', ax=axs['pitch'])

# endnote and title
axs['endnote'].text(1, 0.5, '@your_twitter_handle', va='center', ha='right', fontsize=25,
                    fontproperties=robotto_regular.prop, color='#dee6ea')
axs['title'].text(0.5, 0.5, f'{TEAM1} passes leading to shots \n vs {TEAM2}', color='#dee6ea',
                  va='center', ha='center',
                  fontproperties=robotto_regular.prop, fontsize=25)

# set legend
legend = axs['pitch'].legend(facecolor='#22312b', edgecolor='None',
                             loc='lower center', handlelength=4)
for text in legend.get_texts():
    text.set_fontproperties(robotto_regular.prop)
    text.set_fontsize(25)

plt.show()  # If you are using a Jupyter notebook you do not need this line
plot lines

Total running time of the script: ( 0 minutes 2.559 seconds)

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