figsize=(16, 9),
ncols=3,
nrows=1,
)
# heatmap specified by (nx, ny) for horizontal pitch
bins = [(6, 5), (1, 5), (6, 1)]
for i, bin_dimension in enumerate(bins):
bin_statistic = pitch.bin_statistic(df.x,
df.y,
statistic='count',
bins=bin_dimension)
# draw
pitch.heatmap(bin_statistic,
ax=ax[i],
cmap='coolwarm',
edgecolors='#22312b')
pitch.scatter(df.x, df.y, c='white', s=2, ax=ax[i])
# replace raw counts with percentages and add percentage sign
# (note immutable named tuple so used _replace)
bin_statistic['statistic'] = ((pd.DataFrame(
(bin_statistic['statistic'] / bin_statistic['statistic'].sum()
))).applymap(lambda x: '{:.0%}'.format(x)).values)
pitch.label_heatmap(bin_statistic,
color='white',
fontsize=18,
ax=ax[i],
ha='center',
va='bottom')
TITLE_STR = 'Location of pressure events - 3 home games for Chelsea FC Women'
title = fig.suptitle(TITLE_STR, x=0.5, y=0.98, fontsize=30)
SHOT_ID = '8bb8bbc2-68a6-4c01-93de-53a194e7a1cf'
df_freeze_frame = df_freeze[df_freeze.id == SHOT_ID].copy()
df_shot_event = df_event[df_event.id == SHOT_ID].dropna(axis=1,
how='all').copy()
##############################################################################
# Location dataset
df = pd.concat([df_shot_event[['x', 'y']], df_freeze_frame[['x', 'y']]])
x = df.x.values
y = df.y.values
teams = np.concatenate([[True], df_freeze_frame.player_teammate.values])
##############################################################################
# Plotting
# draw plot
pitch = VerticalPitch(half=True)
fig, ax = pitch.draw(figsize=(8, 6.2))
# Plot Voronoi
team1, team2 = pitch.voronoi(x, y, teams)
t1 = pitch.polygon(team1, ax=ax, fc='#c34c45', ec='white', lw=3, alpha=0.4)
t2 = pitch.polygon(team2, ax=ax, fc='#6f63c5', ec='white', lw=3, alpha=0.4)
# Plot players
sc1 = pitch.scatter(x[teams], y[teams], ax=ax, c='#c34c45', s=150)
sc2 = pitch.scatter(x[~teams], y[~teams], ax=ax, c='#6f63c5', s=150)
custom_pitch = VerticalPitch(pitch_type='custom',
line_color='black',
half=True,
pitch_length=105,
pitch_width=68,
line_zorder=3)
ax_custom = fig.add_axes(
(0.55, 0.05, 0.4, 0.4 * FIGWIDTH / FIGHEIGHT / custom_pitch.ax_aspect))
custom_pitch.draw(ax=ax_custom)
# draw the original event points
fm = FontManager() # a mplsoccer fontmanager with the default Robotto font
opta_pitch.scatter(x,
y,
s=250,
marker='x',
alpha=0.8,
edgecolor='black',
facecolor='#6778d0',
ax=ax_opta)
TEXT = ('The initial points are inside\n'
'the penalty area, six yard box,\n'
'and on the penalty-spot')
_ = ax_text(50,
70,
TEXT,
va='center',
ha='center',
fontproperties=fm.prop,
fontsize=20,
ax=ax_opta)
grid_height=0.7,
marginal=0.1,
# plot without endnote/ title axes
endnote_height=0,
title_height=0,
# here we filter out the left and top marginal axes
ax_top=False,
ax_bottom=True,
ax_left=False,
ax_right=True)
# typical shot map where the scatter points vary by the expected goals value
# using alpha for transparency as there are a lot of shots stacked around the six-yard box
sc_team2 = vertical_pitch.scatter(df_team2.x,
df_team2.y,
s=df_team2.shot_statsbomb_xg * 700,
alpha=0.5,
ec='black',
color='#697cd4',
ax=axes[0])
# kdeplots on the marginals
# remember to flip the coordinates y=x, x=y for the marginals when using vertical orientation
team2_hist_x = sns.kdeplot(y=df_team2.x,
ax=axes[3],
color='#697cd4',
shade=True)
team2_hist_y = sns.kdeplot(x=df_team2.y,
ax=axes[4],
color='#697cd4',
shade=True)
txt1 = axes[0].text(x=40,
y=80,
# By multiplying the expected goals amount by 900 and adding 100
# we essentially get a size that varies between 100 and 1000.
# For choosing color schemes, I really like this website
# `iWantHue <https://medialab.github.io/iwanthue/>`_.
pitch = VerticalPitch(
pad_bottom=0.5, # pitch extends slightly below halfway line
half=True, # half of a pitch
goal_type='box',
goal_alpha=0.8) # control the goal transparency
fig, ax = pitch.draw(figsize=(12, 10))
sc = pitch.scatter(
df_shots_barca.x,
df_shots_barca.y,
# size varies between 100 and 1000 (points squared)
s=(df_shots_barca.shot_statsbomb_xg * 900) + 100,
c='#b94b75', # color for scatter in hex format
edgecolors='#383838', # give the markers a charcoal border
# for other markers types see: https://matplotlib.org/api/markers_api.html
marker='h',
ax=ax)
txt = ax.text(
x=40,
y=80,
s='Barcelona shots\nversus Sevilla',
size=30,
# here i am using a downloaded font from google fonts instead of passing a fontdict
fontproperties=fm_rubik.prop,
color=pitch.line_color,
va='center',
ha='center')
fig, ax = pitch.draw(figsize=(16, 9))
fm = FontManager() # a mplsoccer fontmanager with the default Robotto font
# subset portugals shots for both data providers
mask_portugal_sb = df_statsbomb.team_name == 'Portugal'
mask_shot_sb = df_statsbomb.type_name == 'Shot'
mask_portugal_wyscout = df_wyscout.team_name == 'Portugal'
mask_shot_wyscout = df_wyscout.event_type == 'SHOT'
df_wyscout_portugal = df_wyscout[mask_shot_wyscout
& mask_portugal_wyscout].copy()
df_statsbomb_portugal = df_statsbomb[mask_shot_sb & mask_portugal_sb].copy()
# plotting the shots as a scatter plot with a legend
pitch.scatter(df_wyscout_portugal.coordinates_x,
df_wyscout_portugal.coordinates_y,
ax=ax,
color='#56ae6c',
label='wyscout',
s=250)
pitch.scatter(df_statsbomb_portugal.x,
df_statsbomb_portugal.y,
ax=ax,
color='#7f63b8',
label='statsbomb',
s=250)
# plotting the text and using adjust text so it doesn't overlap
texts = []
for i in range(len(df_wyscout_portugal)):
text = ax.text(df_wyscout_portugal['coordinates_y'].iloc[i],
df_wyscout_portugal['coordinates_x'].iloc[i],
df_wyscout_portugal['last_name'].iloc[i],
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=ax)
# 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=ax)
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=ax)
# Set the title
ax.set_title(f'{TEAM1} passes leading to shots \n vs {TEAM2}', fontsize=30)
# We will use mplsoccer's grid function to plot a pitch with a title axis.
fig, axs = pitch.grid(
figheight=8,
endnote_height=0, # no endnote
title_height=0.1,
title_space=0.02,
# 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=0.83)
# Plot the players
sc1 = pitch.scatter(df_team1.x,
df_team1.y,
s=600,
c='#727cce',
label='Attacker',
ax=axs['pitch'])
sc2 = pitch.scatter(df_team2_other.x,
df_team2_other.y,
s=600,
c='#5ba965',
label='Defender',
ax=axs['pitch'])
sc4 = pitch.scatter(df_team2_goal.x,
df_team2_goal.y,
s=600,
ax=axs['pitch'],
c='#c15ca5',
label='Goalkeeper')