def print_closenesses(match_OPTA, formation, home_or_away_string, half=0):
pass_map = onet.get_all_pass_destinations(match_OPTA,
team=home_or_away_string,
exclude_subs=False,
half=half)
player_times = formation.team_object.get_on_pitch_periods()
graphs = centrality.get_directed_graphs(pass_map,
player_times,
formation.team_object,
role_grouped=True)
closeness = centrality.current_flow_closeness_directed(
graphs['scaled_graph'],
start_node=1 # goalkeeper role
)
print("Match {}.{}:\t {}".format(
match_id, half,
[r_id for r_id, _ in sorted(closeness.items(), key=lambda t: -t[1])]))
def plot_closeness_vs_betweenness(match_OPTA, team_id, match_id=None, half=0):
"""
For a single team in a single match, closeness on the x-axis
and betweenness on the y-axis
"""
team_object = match_OPTA.team_map.get(team_id)
if team_object is None:
print("Team not in match")
return
home_or_away = "home" if team_object == match_OPTA.hometeam else "away"
player_times = team_object.get_on_pitch_periods()
# role_grouped = True
# for period in [0, 1, 2]:
pass_map = onet.get_all_pass_destinations(match_OPTA, team=home_or_away, exclude_subs=False, half=half)
graphs = centrality.get_directed_graphs(
pass_map,
player_times,
team_object,
role_grouped=True,
period=half
)
betweenness = centrality.current_flow_betweenness_directed(
graphs['scaled_graph'],
start_node=1
)
closeness = centrality.current_flow_closeness_directed(
graphs['scaled_graph'],
start_node=1
)
players = graphs['scaled_graph'].nodes()
x = [closeness[p] for p in players]
y = [betweenness[p] for p in players]
fig, ax = plt.subplots()
ax.set_xlabel("closeness")
ax.set_ylabel("betweenness")
title = "Match {} Team {}".format(match_id, team_id)
if half != 0:
title = "{} - Half {}".format(title, half)
ax.set_title(title)
ax.set_xlim([0, 3])
ax.set_ylim([0, 0.8])
colors = []
for i, p_id in enumerate(players):
if p_id in offense:
colors.append('#28b463')
elif p_id in midfield:
colors.append('#f4d03f')
elif p_id in defense:
colors.append('#ec7063')
else:
colors.append('#85c1e9')
ax.scatter(x, y, c=colors)
for i, p_id in enumerate(players):
ax.annotate(p_id, (x[i], y[i]))
plt.show()
def plot_cross_half_centrality(match, team_id, metric="closeness"):
"""
Plot one centrality measure of two matches against each other on
opposing axes.
Args:
matches (matchOPTA): match to evaluate centrality measures
team_id (int): ID for the team in question
Kwargs:
metric (string): the metric used for the match-to-match comparison
"""
allowed_metrics = {
"closeness": centrality.current_flow_closeness_directed,
"betweenness": centrality.current_flow_betweenness_directed,
"pagerank": onet.get_pagerank
}
metric_function = allowed_metrics.get(metric)
if metric_function is None:
raise("Unallowed metric")
metric_results = {}
players = set()
for half in [0,1]:
team_object = match.team_map.get(team_id)
if team_object is None:
raise("Team not in match")
home_or_away = "home" if team_object == match.hometeam else "away"
player_times = team_object.get_on_pitch_periods()
pass_map = onet.get_all_pass_destinations(match, team=home_or_away, exclude_subs=False, half=half)
graphs = centrality.get_directed_graphs(
pass_map,
player_times,
team_object,
role_grouped=True,
period=half
)
players = players.union(set(graphs['scaled_graph'].nodes()))
if metric != "pagerank":
metric_results[half] = metric_function(
graphs['scaled_graph'],
start_node=1
)
else:
metric_results[half] = metric_function(
match_OPTA,
team=home_or_away,
half=half,
role_grouped=True
)
print(metric_results[half])
players = list(players)
x = [metric_results[0].get(p) if p in metric_results[0].keys() else 0 for p in players]
y = [metric_results[1].get(p) if p in metric_results[1].keys() else 0 for p in players]
fig, ax = plt.subplots()
ax.set_xlabel("First Half {}".format(metric))
ax.set_ylabel("Second Half {}".format(metric))
ax.set_title("Team {}".format(team_id))
if metric == "closeness":
ax.set_xlim([0, 3])
ax.set_ylim([0, 3])
elif metric == "betweenness":
ax.set_xlim([0, 0.8])
ax.set_ylim([0, 0.8])
elif metric == "pagerank":
ax.set_xlim([0.085, 0.098])
ax.set_ylim([0.085, 0.098])
# draw center line
line_x_vals = [
min(set(x).union(set(y))),
max(set(x).union(set(y)))
]
line_y_vals = line_x_vals
plt.plot(line_x_vals, line_y_vals, '--', color='r')
colors = []
for i, p_id in enumerate(players):
if p_id in offense:
colors.append('#28b463')
elif p_id in midfield:
colors.append('#f4d03f')
elif p_id in defense:
colors.append('#ec7063')
else:
colors.append('#85c1e9')
ax.scatter(x, y, c=colors)
for i, p_id in enumerate(players):
ax.annotate(p_id, (x[i], y[i]))
plt.show()
formation = formations[match_id]
print("Against {} Score {}-{}".format(
opposing_team_object.team_id, match_OPTA.homegoals
if home_or_away_string == "home" else match_OPTA.awaygoals,
match_OPTA.awaygoals
if home_or_away_string == "home" else match_OPTA.homegoals))
for half in [0, 1, 2]:
pass_map = onet.get_all_pass_destinations(
match_OPTA,
team=home_or_away_string,
exclude_subs=False,
half=half)
player_times = team_object.get_on_pitch_periods()
graphs = centrality.get_directed_graphs(pass_map,
player_times,
team_object,
role_grouped=True)
betweenness = centrality.current_flow_betweenness_directed(
graphs['scaled_graph'],
start_node=1 # goalkeeper role
)
print("Match {}.{}, Opposing Formation {}:\t {}".format(
match_id, half, formation.opp_formation_1
if half == 1 else formation.opp_formation_2, [
r_id for r_id, _ in sorted(betweenness.items(),
key=lambda t: -t[1])
]))
print()