tight_layout=True)
# Now lets plot the shots
for i, shot in shots.iterrows():
x = shot['location'][0]
y = shot['location'][1]
goal = shot['shot_outcome_name'] == 'Goal'
team_name = shot['team_name']
circleSize = 2
#circleSize=np.sqrt(shot['shot_statsbomb_xg'])*12
if (team_name == team1):
if goal:
# shotCircle=plt.Circle((x,pitchWidthY-y),circleSize,color="red")
shotCircle = pitch.scatter(x,
pitchWidthY - y,
marker='football',
ax=ax)
# plt.text((x+1),pitchWidthY-y+1,shot['player_name'])
else:
shotCircle = pitch.scatter(x, pitchWidthY - y, ax=ax)
# shotCircle=plt.Circle((x,pitchWidthY-y),circleSize,color="red")
elif (team_name == team2):
if goal:
shotCircle = pitch.scatter(pitchLengthX - x,
y,
marker='football',
ax=ax)
# shotCircle=plt.Circle((pitchLengthX-x,y),circleSize,color="blue")
# plt.text((pitchLengthX-x+1),y+1,shot['player_name'])
else:
shotCircle = pitch.scatter(pitchLengthX - x, y, ax=ax)
)
fig, ax = pitch.draw(figsize=(16, 11),
constrained_layout=True,
tight_layout=False)
pass_lines = pitch.lines(passes_between.x,
passes_between.y,
passes_between.x_end,
passes_between.y_end,
lw=passes_between.width,
color=color,
zorder=1,
ax=ax)
pass_nodes = pitch.scatter(average_locs_and_count.x,
average_locs_and_count.y,
s=average_locs_and_count.marker_size,
color='red',
edgecolors='black',
linewidth=1,
alpha=1,
ax=ax)
for index, row in average_locs_and_count.iterrows():
pitch.annotate(row.name,
xy=(row.x, row.y),
c='white',
va='center',
ha='center',
size=16,
weight='bold',
ax=ax)
title = ax.set_title("{} {} Formation vs {}".format(TEAM, FORMATION, OPPONENT),
size=28,
y=0.97,
fig, axes, _, _ = pitch.jointgrid(
figheight=10, # the figure is 10 inches high
left=None, # joint grid center-aligned
bottom=0.075, # grid starts 7.5% in from the bottom of the figure
marginal=0.1, # marginal axes heights are 10% of grid height
space=0, # 0% of the grid height reserved for space between axes
grid_width=0.9, # the grid width takes up 90% of the figure width
title_height=0, # plot without a title axes
endnote_height=0, # plot without an endnote axes
grid_height=0.8) # grid takes up 80% of the figure height
# we plot a usual scatter plot but the scatter size is based on expected goals
# note that the size is the expected goals * 700
# so any shots with an expected goals = 1 would take a size of 700 (points**2)
sc_team1 = pitch.scatter(df_team1.x,
df_team1.y,
s=df_team1.shot_statsbomb_xg * 700,
ec='black',
color='#ba495c',
ax=axes[0])
sc_team2 = pitch.scatter(df_team2.x,
df_team2.y,
s=df_team1.shot_statsbomb_xg * 700,
ec='black',
color='#697cd4',
ax=axes[0])
# (step) histograms on each of the left, top, and right marginal axes
team1_hist_y = sns.histplot(y=df_team1.y,
ax=axes[1],
element='step',
color='#ba495c')
team1_hist_x = sns.histplot(x=df_team1.x,
ax=axes[2],
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,
import matplotlib.pyplot as plt
# read data
df = read_event(f'{EVENT_SLUG}/7478.json',
related_event_df=False,
shot_freeze_frame_df=False,
tactics_lineup_df=False)['event']
##############################################################################
# Filter passes by Jodie Taylor
df = df[(df.player_name == 'Jodie Taylor') & (df.type_name == 'Pass')].copy()
##############################################################################
# Plotting
pitch = Pitch()
fig, ax = pitch.draw(figsize=(8, 6))
hull = pitch.convexhull(df.x, df.y)
poly = pitch.polygon(hull,
ax=ax,
edgecolor='cornflowerblue',
facecolor='cornflowerblue',
alpha=0.3)
scatter = pitch.scatter(df.x,
df.y,
ax=ax,
edgecolor='black',
facecolor='cornflowerblue')
plt.show(
) # if you are not using a Jupyter notebook this is necessary to show the plot
