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PitchProphet Accuracy Tracker

Every projection is logged and auto-graded against the final box score. No cherry-picking — this is the full record across 285 graded starts (1140 decided calls).

285
Starts graded
2.1
K avg miss (MAE)
+0.5
K bias (proj − actual)
51%
Directional hit rate · ties excluded

By Metric (all-time)

Skill lives in MAE (average miss) and bias (systematic over/under) — lower and nearer zero is better. The W-L / Hit % columns are directional-vs-our-own-line with exact ties scored as pushes (P, excluded from the record) — shown for context, not as a skill score.

MetricMAEBiasRecord (W-L·P)Hit %
Strikeouts (over)2.09+0.45123-16243%
Outs / IP (over)4.02+1.86126-15944%
Earned Runs (under)1.70-0.11154-13154%
Walks (under)1.12+0.35179-10663%

Self-Calibration

The engine re-fits its own weights from graded results under bounded guardrails, then syncs the update to the shared ledger. This is that loop's live state — so a weight that drifts far from the calibrated baseline shows up here instead of silently skewing projections.

v10
Weights version
42d
Last retune
327
Trained on (starts)
Watch
Drift status
WeightBaselineActiveΔ vs baseStatus
split_k_sensitivity0.50.749+50%watch
park_k_sensitivity0.150.082-45%watch
split_er_sensitivity0.40.220-45%watch
split_bb_sensitivity0.30.167-44%watch
park_er_sensitivity0.70.404-42%watch
sfm_penalty_per_rv0.030.022-26%watch

0 railed / 6 watch — flagged for a human look. Every weight is still clamped in the projection math, so a flag is a review trigger, not a live error.

Recent Form

0-0
All calls 7d · 0%
0-0
Strikeouts 7d · 0%
0-0
Strikeouts 30d · 0%
123-162
All-time K · 43%

How to read this: the directional hit rate scores each start against our own projection (K/Outs win when the pitcher tops it; ER/BB win when under it), and an exact tie is a push — excluded from the record, sportsbook-style, so projections that land on round numbers can't pad the rate. Even so it is not a pure skill score: its baseline still shifts with each metric's distribution shape. Judge the model by MAE (average miss) and bias (systematic over/under) above. Overall MAE across all metric calls: 2.23.

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