Sonar Zones

The bin_statistic_sonar_zones method bins angles within any rectangular tiling and sonar_zones plots a sonar at the centre of each zone. Here we use the Juego de Posición zones.

More information is available on how to customize the segments in Bin Statistic Sonar and on the zone layouts in Heatmap custom zones.

import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap

from mplsoccer import Pitch, Sbopen

Load the first game that Messi played as a false-9.

parser = Sbopen()
df = parser.event(69249)[0]  # 0 index is the event file
df_pass = df[(df.type_name == 'Pass') & (df.team_name == 'Barcelona') &
             (~df.sub_type_name.isin(['Free Kick', 'Throw-in',
                                      'Goal Kick', 'Kick Off', 'Corner']))].copy()
df_pass['success'] = df_pass['outcome_name'].isnull()

Calculate the angle and distance and create the zone statistics

pitch = Pitch(line_color='#f0eded', line_zorder=2)
angle, distance = pitch.calculate_angle_and_distance(df_pass.x, df_pass.y, df_pass.end_x,
                                                     df_pass.end_y)
zones, names = pitch.positional_zones('full')
bs_count = pitch.bin_statistic_sonar_zones(df_pass.x, df_pass.y, angle, zones,
                                           names=names, angle_bins=5, center=True)
bs_success = pitch.bin_statistic_sonar_zones(df_pass.x, df_pass.y, angle, zones,
                                             values=df_pass.success, statistic='mean',
                                             names=names, angle_bins=5, center=True)

Plot a sonar in each Juego de Posición zone with the number of passes as the slice length and the success rate of the passes for the color.

fig, ax = pitch.draw(figsize=(8, 5.5))
axs = pitch.sonar_zones(bs_count,
                        # here we set the color of the slices based on the % success
                        stats_color=bs_success, cmap='viridis', ec='#202020',
                        # we set the color map to be mapped from 0% to 100%
                        # rather than the default min/max of the values
                        vmin=0, vmax=1,
                        zorder=3,  # slices appear above the axis lines
                        # the size of the sonar axis in data coordinates
                        width=13,
                        ax=ax)

The zone statistics also work with heatmap_zones, so you can shade each zone by its total number of passes underneath the sonars.

pearl_earring_cmap = LinearSegmentedColormap.from_list("Pearl Earring - 10 colors",
                                                       ['#15242e', '#4393c4'], N=10)
fig, ax = pitch.draw(figsize=(8, 5.5))
zones_count = pitch.bin_statistic_zones(df_pass.x, df_pass.y, zones)
pc = pitch.heatmap_zones(zones_count, ax=ax, cmap=pearl_earring_cmap, edgecolor='#202020')
axs = pitch.sonar_zones(bs_count, ec='#202020', fc='cornflowerblue',
                        zorder=3, width=13, ax=ax)

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