Update models/pitch_model.py

models/pitch_model.py

@@ -64,6 +64,28 @@ def predict_pitch_outcome(
         "ball_in_play_prob": float(min(1.0, ball_in_play_prob)),
     }
 
+def blend_pitch_outcome_probabilities(
+    baseline_probs: dict[str, float],
+    live_probs: dict[str, float],
+    baseline_weight: float,
+    live_weight: float,
+) -> dict[str, float]:
+    """
+    Blend baseline and live pitch-outcome probabilities at the probability layer.
+    This is stronger than only blending raw inputs.
+    """
+    keys = ["strike_prob", "whiff_prob", "damage_prob", "ball_in_play_prob"]
+
+    out: dict[str, float] = {}
+
+    for key in keys:
+        base_val = float(baseline_probs.get(key, 0.0) or 0.0)
+        live_val = float(live_probs.get(key, base_val) or base_val)
+
+        blended = (base_val * baseline_weight) + (live_val * live_weight)
+        out[key] = float(max(0.0, min(1.0, blended)))
+
+    return out
 
 def pitcher_baseline_from_events(df: pd.DataFrame) -> dict[str, float]:
     if df.empty: