📊 Baseline Predictions Explorer

End-of-period win probabilities. Both Raw and Model adjust for rest days. Raw = historical counting data (rest_30s lookup). Model = XGBoost trained on same inputs.

ℹ️ Rest days → model: 0 days = B2B, 1 day = one-day rest, 2+ days = rested. Model uses XGBoost (non-linear, captures B2B jump vs diminishing returns).

Score Diff (Home)	Raw % (Home)	Model % (Home)	Away Raw %	Visual (Raw)

Raw: historical counting data from 13K+ games, win_prob_lookup_rest_30s.json.
Model: XGBoost trained on 758K shots with features: elapsed, goal_diff, home_rest (0/1/2), away_rest (0/1/2).
Both columns reflect rest-day adjustments. Rest=0 = B2B (played yesterday or same day).