File size: 9,079 Bytes
c6abe34 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 | """
Transition Effort Engine - Analyzes player effort during transition phases.
Tracks player speeds during the 3 seconds after possession changes and
classifies effort as sprint, jog, or walk.
"""
from typing import Dict, Any, List
import numpy as np
from .base import BaseAnalyticsModule
class TransitionEffortEngine(BaseAnalyticsModule):
"""Analyzes player effort during offensive/defensive transitions."""
def __init__(
self,
sprint_threshold_mps: float = 5.5,
jog_threshold_mps: float = 3.0,
transition_duration_seconds: float = 3.0,
):
"""
Initialize transition effort engine.
Args:
sprint_threshold_mps: Speed threshold for sprint classification
jog_threshold_mps: Speed threshold for jog classification
transition_duration_seconds: How long to track after possession change
"""
super().__init__("transition_effort")
self.sprint_threshold = sprint_threshold_mps
self.jog_threshold = jog_threshold_mps
self.transition_duration = transition_duration_seconds
def process(
self,
video_frames: List[Any],
player_tracks: List[Dict],
ball_tracks: List[Dict],
tactical_positions: List[Dict],
player_assignment: List[Dict],
ball_possession: List[int],
events: List[Dict],
shots: List[Dict],
court_keypoints: List[Dict],
speeds: List[Dict],
video_path: str,
fps: float,
**kwargs
) -> Dict[str, Any]:
"""
Analyze transition effort for all possession changes.
Returns:
Dictionary with transition effort metrics
"""
transition_efforts = []
# Detect possession changes
possession_changes = self._detect_possession_changes(
ball_possession,
player_assignment
)
transition_window_frames = int(self.transition_duration * fps)
for change in possession_changes:
frame = change["frame"]
old_team = change["old_team"]
new_team = change["new_team"]
# Analyze effort for both teams
# Team gaining possession: offense transition
# Team losing possession: defense transition
end_frame = min(frame + transition_window_frames, len(speeds))
for analyze_frame in range(frame, end_frame):
if analyze_frame >= len(player_assignment) or analyze_frame >= len(speeds):
break
assignment = player_assignment[analyze_frame]
frame_speeds = speeds[analyze_frame]
for player_id, team_id in assignment.items():
if player_id not in frame_speeds:
continue
speed = frame_speeds[player_id]
# Classify effort
if speed >= self.sprint_threshold:
effort_type = "sprint"
effort_score = 100
elif speed >= self.jog_threshold:
effort_type = "jog"
effort_score = 60
else:
effort_type = "walk"
effort_score = 20
# Determine transition type
if team_id == new_team:
transition_type = "defense_to_offense"
else:
transition_type = "offense_to_defense"
transition_efforts.append({
"possession_change_frame": frame,
"player_track_id": player_id,
"team_id": team_id,
"transition_type": transition_type,
"effort_type": effort_type,
"max_speed_mps": float(speed),
"effort_score": effort_score,
"frame": analyze_frame,
"timestamp": self._get_frame_time(analyze_frame, fps)
})
# Aggregate by possession change
aggregated_efforts = []
for change in possession_changes:
frame = change["frame"]
change_efforts = [e for e in transition_efforts if e["possession_change_frame"] == frame]
if change_efforts:
# Group by player
player_efforts = {}
for effort in change_efforts:
pid = effort["player_track_id"]
if pid not in player_efforts:
player_efforts[pid] = []
player_efforts[pid].append(effort)
# Calculate max speed and avg effort for each player
for pid, efforts in player_efforts.items():
max_speed = max(e["max_speed_mps"] for e in efforts)
avg_speed = np.mean([e["max_speed_mps"] for e in efforts])
avg_effort_score = np.mean([e["effort_score"] for e in efforts])
# Determine overall effort type based on max speed
if max_speed >= self.sprint_threshold:
overall_effort = "sprint"
elif max_speed >= self.jog_threshold:
overall_effort = "jog"
else:
overall_effort = "walk"
aggregated_efforts.append({
"possession_change_frame": frame,
"player_track_id": pid,
"team_id": efforts[0]["team_id"],
"transition_type": efforts[0]["transition_type"],
"effort_type": overall_effort,
"max_speed_mps": float(max_speed),
"avg_speed_mps": float(avg_speed),
"effort_score": float(avg_effort_score),
"duration_seconds": self.transition_duration
})
# Calculate summary statistics
if aggregated_efforts:
sprint_count = sum(1 for e in aggregated_efforts if e["effort_type"] == "sprint")
jog_count = sum(1 for e in aggregated_efforts if e["effort_type"] == "jog")
walk_count = sum(1 for e in aggregated_efforts if e["effort_type"] == "walk")
total = len(aggregated_efforts)
summary = {
"total_transition_events": total,
"sprint_count": sprint_count,
"jog_count": jog_count,
"walk_count": walk_count,
"sprint_rate": (sprint_count / total * 100) if total > 0 else 0,
"avg_effort_score": float(np.mean([e["effort_score"] for e in aggregated_efforts])),
"avg_max_speed_mps": float(np.mean([e["max_speed_mps"] for e in aggregated_efforts])),
}
else:
summary = {
"total_transition_events": 0,
"sprint_count": 0,
"jog_count": 0,
"walk_count": 0,
"sprint_rate": 0,
"avg_effort_score": 0,
"avg_max_speed_mps": 0,
}
return {
"transition_efforts": aggregated_efforts,
"summary": summary,
"status": "success"
}
def _detect_possession_changes(
self,
ball_possession: List[int],
player_assignment: List[Dict]
) -> List[Dict]:
"""
Detect frames where possession changes between teams.
Args:
ball_possession: Per-frame possession (track_id or -1)
player_assignment: Per-frame team assignments
Returns:
List of possession change events
"""
changes = []
prev_team = None
for frame_idx in range(len(ball_possession)):
if frame_idx >= len(player_assignment):
break
possession_player = ball_possession[frame_idx]
if possession_player == -1:
continue
assignment = player_assignment[frame_idx]
if possession_player not in assignment:
continue
current_team = assignment[possession_player]
if prev_team is not None and current_team != prev_team:
changes.append({
"frame": frame_idx,
"old_team": prev_team,
"new_team": current_team
})
prev_team = current_team
return changes
|