Deep slate report — 20261007

Generated · schema deep_slate_diagnosis_v3 · fuses prediction review + forensic deep audit + official starter lines, with a Luna post-mortem.

Slate summary

Games
4
Hits
3
Misses
1
Winner accuracy
75%
Mean Brier (losses)
0.296
Mean total-run bias (losses)
0

What drove the losses

Several errors of similar size: 1

Source coverage receipt

Which reports actually fed the diagnosis. A source shown as missing was not silently assumed.

SourceStatusEvidence suppliedPathBytes
prediction reviewloadedofficial outcomes and scoring errors/app/output/reports/prediction_review_20261007.jsonn/a
forensic deep auditloadedprobability, provenance, starter and decision contracts/app/output/reports/PREDICTION_SYSTEM_DEEP_AUDIT_20261007.jsonn/a
continuous learningloadedpipeline-stage quality, calibration, probability lineage/app/output/learning/continuous_learning_daily_20261007.jsonn/a
game artifactsloadedper-game model trace and structural audit source/app/output/gamesn/a

High-level causal issue register

Deterministic findings across data integrity, model validation, calibration, score distribution, pipeline stages, simulation, and coverage. Critical is reserved for broken evidence or an unexplained contract violation; high marks material model/process risk. Each row pairs the action to take (Do this) with the wrong conclusion to avoid (Don't conclude).

SeverityDomainFinding and evidenceAffectedAction & guardrail
HIGHpipeline_stagesAn intermediate stage materially degraded winner direction
historical_ml → variance_applied changed winner accuracy by -0.2500 (-1 hits)
MIL@SD
Do thisList the exact games whose winner flipped at this stage, and keep both the before-stage and after-stage picks in the trace.
Don't concludeEven if a later stage recovers the pick, this unstable step is still a risk; do not treat it as harmless.
HIGHcalibrationPublished confidence buckets were poorly aligned on this slate
weighted absolute calibration error 0.2272 across 4 games
CLE@CHW, LAD@ATL, MIL@SD, TB@NYY
Do thisWatch the same confidence buckets over the full rolling window before changing any calibration weight.
Don't concludeA single slate has far too few games to establish a stable calibration curve.
HIGHmodel_validationValidated run models explain very little holdout variance
home/away/total R² = 0.0021/0.0309/0.0024
CLE@CHW, LAD@ATL, MIL@SD, TB@NYY
Do thisTreat exact run scores as low-confidence estimates, and look for stronger features or a better target before tuning the score tails.
Don't concludeA small positive R² only means the model beats guessing the average; it does not make the exact scores reliable.
INFOcoverageEvery settled game received structural QA
4/4 games structurally audited
CLE@CHW, LAD@ATL, MIL@SD, TB@NYY
Do thisKeep the per-game audit receipt in every report.
Don't concludeFull audit coverage does not cancel the findings raised inside the audited games.
INFOprobability_lineageMaterial calibrated-to-published movements have recorded lineage
1 material movement(s), all explained by named score-coherence and/or recency transformations
TB@NYY
Do thisKeep showing every probability layer and the named transformation between them.
Don't concludeA published probability above the calibrated one is not a governor bypass when a recorded transformation explains it.
INFOsimulationSimulation produced no winner-direction intervention on this slate
flip candidates 0; published flips 0
CLE@CHW, LAD@ATL, MIL@SD, TB@NYY
Do thisMeasure the simulation's contribution across rolling slates, separating score realization from winner flipping.
Don't concludeZero winner flips is not a defect and does not mean the simulation did no score-reconciliation work.

Cross-slate trends (persistent-pattern memory)

Window: 20260927, , 20260929, 20260930, 20261001, , 20261003, 20261004, 20261005, 20261006, 20261007 (10 prior slates loaded). Highest-confidence pick loss streak: 1 slate(s). Actionable pattern detected.

Escalated persistent patterns

A finding that has repeated at or beyond the escalation streak is no longer single-slate noise. It carries its target registered lever and an action-oriented guardrail.

FindingPersistenceTarget lever(s)DirectionGuardrail
simulation_inert_on_slate11 consecutive · 11 in windowsimulation.allow_scoreconfirm the simulation module is running, not silently no-opingsimulation_inert_on_slate has persisted 11 consecutive slates; this is no longer single-slate noise. Treat it as an actionable pattern and raise the code/diagnostic action named; do not force a parameter move.
single_slate_calibration_instability5 consecutive · 8 in windowconfidence.empirical_max_weight, confidence.base_cap, confidence.moderate_capincrease empirical shrinkagesingle_slate_calibration_instability has persisted 5 consecutive slates; this is no longer single-slate noise. Treat it as an actionable pattern and propose a bounded shadow experiment against a target lever.
weak_run_model_signal5 consecutive · 9 in windowtraining.xgb.n_estimators, training.xgb.max_depth, training.xgb.learning_rateinvestigate features/target via isolated training backtest (manual)weak_run_model_signal has persisted 5 consecutive slates; this is no longer single-slate noise. Treat it as an actionable pattern and raise the code/diagnostic action named; do not force a parameter move.

Finding streaks across the window

FindingConsecutive slatesIncidencePresent nowFix type
pipeline_winner_instability13/11yescode/diagnostic
score_margin_compression04/11noparam
simulation_inert_on_slate1111/11yescode/diagnostic
single_slate_calibration_instability58/11yesparam
weak_run_model_signal59/11yescode/diagnostic

Metric direction across the window

MetricDirectionSeries (old → new)
winner_accuracyflat0.6429, –, 1.0, 0.75, 1.0, –, 1.0, 0.5, 0.0, 1.0, 0.75
weighted_calibration_errorimproving0.1031, –, 0.4792, 0.2317, 0.4832, –, 0.4705, 0.4806, 0.5291, 0.4642, 0.2272
margin_biasregressing-1.571, –, -4.25, -2.75, -3.0, –, -0.25, 0.0, -0.5, -0.5, -1.75
team_run_error_on_lossesimproving4.8, –, –, 2.0, –, –, –, 2.0, 3.5, –, 2.0

Pipeline stage regression

Every stored stage is scored against the same official finals. A later recovery remains visible; it does not erase an unstable intermediate flip.

StageWinner hitsAccuracyTeam-run MAETotal-run MAEMargin MAE
historical_ml3/475%1.893.7592.675
variance_applied2/450%1.8753.752.75
enhanced_prediction2/450%233
kpi_layer2/450%233
embedded_savant_run_environment2/450%2.1253.252.75
fundamental_edge_target_review3/475%2.3753.752.25
capped_target3/475%2.3753.752.25
simulation_result3/475%2.3753.752.25
published_final3/475%2.3753.752.25
TransitionΔ accuracyΔ hitsΔ team-run MAEΔ margin MAEGames whose winner/tie changed
historical_ml → variance_applied-0.25-1-0.01480.0755MIL@SD: MIL → TIE
variance_applied → enhanced_prediction000.1250.25MIL@SD: TIE → SD
enhanced_prediction → kpi_layer0000
kpi_layer → embedded_savant_run_environment000.125-0.25
embedded_savant_run_environment → fundamental_edge_target_review0.2510.25-0.5MIL@SD: SD → MIL
fundamental_edge_target_review → capped_target0000
capped_target → simulation_result0000
simulation_result → published_final0000

Probability lineage and calibration

All columns are pick-side probabilities, so away favorites are not accidentally compared using home-side semantics.

GameOutcomeRaw modelCalibratedGovernorScore coherencePublishedExplanation
CLE@CHWhit0.58460.54860.54860.54860.5351score coherence followed by matchup-recency guardrail
LAD@ATLhit0.50970.50840.50840.50840.5072published probability matches the calibrated/governed value
MIL@SDhit0.50.5050.5050.5050.505published probability matches the calibrated/governed value
TB@NYYmiss0.61850.56650.56650.56650.544score coherence followed by matchup-recency guardrail
Pitcher versus batter: patterns across the whole slate

One blown start is noise. The same failure repeating across the slate is a model problem. These are the repeats.

Sides analyzedBroke on pitchingBroke on offenseBothVarianceMean starter ERA errorMean lineup runs vs proj
812050.85-0.38
Trained winner blend: does it reach the published number?

The blend mixes the trained win classifier with the margin-derived probability. It is only worth its weight if its decision survives the downstream reconciliation to the projected score.

On all 4 games with an applied blend, the blend's side and the published side agree.

Blend side survived on 4 of 4 games; the blend flagged a winner change on 1.

Repeated bias across slates, and the lever that moves it

A bias on one slate is noise. The same sign across slates, large relative to how much it moves between them, is a model defect. Only the ones that pass both tests are turned into a named parameter change; the rest are held deliberately.

starter ERA error (actual minus projected)

Mean 0.03 over 10 slates (sign shared by 0.30 of them, z = 0.04).

starters were hit harder than projected: the run model under-credits opposing offenses.

Hold: no change: this bias is not separable from slate-to-slate noise yet

3 of 10 slates share the sign, mean 0.03 +/- 0.8 standard error: not separable from noise

lineup runs actual minus projected

Mean -0.41 over 10 slates (sign shared by 0.60 of them, z = -1.07).

lineups scored below projection: the run environment is set too high.

Hold: no change: this bias is not separable from slate-to-slate noise yet

6 of 10 slates share the sign, mean -0.41 +/- 0.38 standard error: not separable from noise

SlateGamesWinner accMean starter ERA errorMean lineup runs vs projSides broke on pitchingSides broke on offense
2026100740.7506.751.501
2026100621.000-1.40-1.251
2026100520.000-1.11-0.752
2026100420.500-1.24-2.002
2026100341.000-0.95-2.254
20261002———
2026100111.0000.000.50
2026093040.7500.780.121
2026092941.000-0.76-0.503
20260928———
20260927140.643-2.33-0.1125
20260926130.5380.550.6934

Score distribution and margin compression

Narrow predicted margins next to wide actual margins is the signature the score-variance tail is too tight.

Predicted margins ≤2: 4 · Actual margins ≥4: 1
GamePred marginActual marginPred − actual
CLE@CHW16-5
LAD@ATL23-1
MIL@SD12-1
TB@NYY110

Per-game evidence coverage

Expected games
4
Artifacts loaded
4
Structural audits
4
Deep-audit games
4
Learning rows
4
Starter comparisons
4

Every game, in depth (4)

CLE@CHWHIT

Predicted: CLE 5-4 (conf -0.07, lean)Actual: CLE 9-3Brier 0.216total bias -3
Root cause: Right winner, wrong score
Evidence-backed diagnosis
Quantified contributing factors
TeamStarterProjectedActualER err
CLEDaniel Espino3 ER / 12 outs1 ER / 2 outs-2
CHWSean Newcomb2 ER / 10 outs0 ER / 6 outs-2
Decision internals: run factors home×0.983 / away×0.991; savant lineup adjustment applied

Player-level breakdown (projected vs actual)

Every value is actual / projected. Run impact approximates how far each hitter's real line moved run expectancy from its projection; it orders the movers and is not a published stat.

Top deviations that drove the game:

Starter miss: Daniel Espino (CLE) posted 13.50 ERA vs projected 6.75 (1 ER in 2 outs); no credible venue, opponent-strength or experience signal explains it — an outlier start (variance).

What to do: Variance — no model change is warranted for this start.

Pitcher versus batter: what actually broke this game

Per-pitch matchup fields are not populated in the current feeds, so this is reconstructed from the settled box: each starter's workload-adjusted ERA, the bullpen share behind him, and the opposing lineup's real production against its projection, with the hitters who beat that projection named.

AWAY pitching

Daniel Espino (CLE) threw 2 outs, 1 ER = 13.5 ERA against a projected 6.75 ERA (6.75 ERA error)

Bullpen behind him: 0 ER over 5 outs.

The HOME lineup he faced produced 2 runs on 4 hits and 0 HR, against a projected 2 runs / 5 hits (0 runs vs projection).

Who did the damage to him:

  • Kyle Teel: 1-for-4, 0 HR, 1 RBI [+0.78 runs vs projection] season xwOBA 0.321, above average - real projection error
  • Braden Montgomery: 0-for-3, 0 HR, 0 RBI [+0.33 runs vs projection] season xwOBA 0.325, above average - a good day, not a model error
  • Chase Meidroth: 1-for-4, 0 HR, 0 RBI [+0.31 runs vs projection] season xwOBA 0.301, below average - a good day, not a model error

Verdict: pitching: the starter gave up runs at a far worse rate than projected

HOME pitching

No settled pitching line for this club. The forecast named Sean Newcomb (CHW) at a projected 5.4 ERA, but the per-player feed carries no pitching row for him in this game, so the actual-versus-projected comparison cannot be made on this side. That is a source-coverage gap in the settled box, not a forecasting failure.

Bullpen behind him: 1 ER over 2 outs.

The AWAY lineup he faced produced 8 runs on 10 hits and 0 HR, against a projected 5 runs / 9 hits (3 runs vs projection).

Who did the damage to him:

  • Jo Adell: 2-for-4, 0 HR, 3 RBI [+1.42 runs vs projection] season xwOBA 0.329, above average - real projection error
  • Patrick Bailey: 2-for-4, 0 HR, 0 RBI [+0.8 runs vs projection] season xwOBA 0.307, average - a good day, not a model error
  • Brayan Rocchio: 2-for-4, 0 HR, 1 RBI [+0.47 runs vs projection] season xwOBA 0.294, below average - a good day, not a model error

Verdict: neither side broke materially - the result is closer to variance

Starting pitchers & relievers: actual / projected + context (ERA is workload-aware: ER over 9 innings, so a short blow-up is not read like a quality start; ERA error in parentheses when material. exp BB and exp SO are the continuous rate expectations. The integer beside each is a simulation draw reconciled to the opposing simulated batting box, so it is not the line that ranks pitchers: on the 2026-09-07 slate the integers published 39 walks and 121 strikeouts against 51 and 130 real, while these expectations landed on 50.4 and 132.6.)

PitcherTeamOutsERAERHHRBBexp BBSOexp SOContext (as-of)
CLEDaniel Espino (Starter)2 / 1213.5 / 6.75 (+6.75)1 / 32 / 30 / 11 / 11.732 / 52.41venue away: 0 vs 27 ERA (ok) · opp run factor 0.98 (average) · 15 prior appearances this season
CLETim Herrin (Middle Reliever)3 / 30 / 9 (-9.00)0 / 10 / 10 / 10 / 00.493 / 10.97
CLEShawn Armstrong (Middle Reliever (High Leverage))2 / 90 / 00 / 00 / 10 / 00 / 00.471 / 30.88
CHWHagen Smith (Long Reliever)2 / 413.5 / 13.51 / 21 / 20 / 12 / 00.941 / 11.87

Hitters: actual / projected (sorted by run impact vs projection)

BatterTeamABH2B3BHRRBIRBBSORun impactSeason xwOBASignal
Jo Adell (DH)CLE4 / 42 / 10 / 01 / 00 / 03 / 00 / 11 / 01 / 21.420.329 above averageprojection too low
Munetaka Murakami (1B)CHW4 / 40 / 20 / 10 / 00 / 00 / 20 / 00 / 03 / 0-1.250.351 elitebad day
Randal Grichuk (LF)CHW4 / 31 / 10 / 00 / 00 / 10 / 10 / 10 / 01 / 1-0.930.335 above averagebad day
Patrick Bailey (C)CLE4 / 42 / 10 / 00 / 00 / 00 / 01 / 01 / 01 / 10.80.307 averageno signal
Kyle Teel (C)CHW4 / 41 / 01 / 00 / 00 / 01 / 00 / 00 / 02 / 20.780.321 above averageprojection too low
Nathaniel Lowe (1B)CLE2 / 30 / 20 / 20 / 00 / 00 / 11 / 13 / 00 / 0-0.570.335 above averagebad day
Brayan Rocchio (SS)CLE4 / 42 / 10 / 00 / 00 / 01 / 00 / 00 / 00 / 20.470.294 below average—
José Ramírez (3B)CLE4 / 52 / 21 / 01 / 00 / 12 / 22 / 11 / 00 / 00.330.325 above average—
Chase DeLauter (RF)CLE4 / 51 / 10 / 00 / 00 / 01 / 01 / 11 / 00 / 00.330.346 elite—
Braden Montgomery (RF)CHW3 / 40 / 00 / 00 / 00 / 00 / 01 / 01 / 02 / 20.330.325 above average—
Chase Meidroth (2B)CHW4 / 41 / 11 / 00 / 00 / 00 / 01 / 00 / 02 / 10.310.301 below average—
Steven Kwan (CF)CLE6 / 41 / 00 / 00 / 00 / 01 / 01 / 00 / 11 / 00.140.328 above average—
Travis Bazzana (2B)CLE2 / 30 / 10 / 00 / 00 / 00 / 22 / 12 / 10 / 1-0.140.299 below average—
Miguel Vargas (3B)CHW4 / 41 / 10 / 10 / 00 / 00 / 00 / 11 / 02 / 10.020.378 elite—
Angel Martínez (LF)CLE4 / 40 / 00 / 00 / 00 / 00 / 00 / 00 / 03 / 100.299 below average—
Full model trace, player evidence, and audit findings

Fundamental evidence entering the pick

SignalHome-away edgeMeaning
Season quality0.161positive favors home; negative favors away
Recent form0.03positive favors home; negative favors away
Starting-pitcher matchup-0.008positive favors home; negative favors away
Composite-0.102positive favors home; negative favors away

Score and confidence evolution

StageAway-home runsConfidenceWhat changed
historical_ml4.63-2.8n/aBase ML historical model prediction
variance_applied5-3n/aDeterministic baseline target (variance factor 1.0)
enhanced_prediction5-40.535Enhanced ML with recent form, H2H, low-score analysis (confidence shrunk by projected_margin_is_one_run, matchup_recency_guardrail)
kpi_layer5-4n/aSavant KPI blend applied to the model target
embedded_savant_run_environment5-4n/aTarget score adjusted by temporal Savant lineup quality versus opposing starter quality
fundamental_edge_target_review5-4n/aRefreshed score target and win probability after Savant/pitcher/team-strength adjustments
capped_target5-4n/aCapped at max 12 realistic runs
simulation_result5-4n/aFinal inning-by-inning simulation result

Official postgame stage attribution

StageBeforeAfterToward final pickWhat changed
variance_applied4.63-2.85-30.172Deterministic baseline target (variance factor 1.0)
enhanced_prediction5-35-4-1Enhanced ML with recent form, H2H, low-score analysis (confidence shrunk by projected_margin_is_one_run, matchup_recency_guardrail)
kpi_layer5-45-4-0Savant KPI blend applied to the model target
embedded_savant_run_environment5-45-4-0Target score adjusted by temporal Savant lineup quality versus opposing starter quality
fundamental_edge_target_review5-45-4-0Refreshed score target and win probability after Savant/pitcher/team-strength adjustments
capped_target5-45-4-0Capped at max 12 realistic runs
simulation_result5-45-4-0Final inning-by-inning simulation result

Largest player-level adjustments from the ultra-detailed trace

These are pregame model adjustments, not claims about actual postgame player error.

TeamPlayerRoleNet effectLargest change
CHWSean Newcombpitcher / Starterworsepredicted_SO -4
CHWBryan Hudsonpitcher / Middle Reliever (High Leverage)betterpredicted_IP 2.1
CLEDaniel Espinopitcher / Starterbetterpredicted_BB -2
CLEShawn Armstrongpitcher / Middle Reliever (High Leverage)betterpredicted_IP 2
CHWJordan Hickspitcher / Middle Reliever (High Leverage)betterpredicted_ER -2
CLENathaniel Lowebatter / 1Bbetterpredicted_2B 1.814
CLETravis Bazzanabatter / 2Bbetterpredicted_RBI 1.71
CHWMunetaka Murakamibatter / 1Bdeboostedpredicted_SO -1.557

Structural audit findings

SeverityRuleFindingSubject
infoRECONCILIATION_PROPAGATIONNo score_target_reconciliation step was used for this game.

LAD@ATLHIT

Predicted: LAD 6-4 (conf -0.01, toss_up)Actual: LAD 4-1Brier 0.243total bias +5
Root cause: Toss-up that went our way
Evidence-backed diagnosis
Quantified contributing factors
TeamStarterProjectedActualER err
LADTyler Glasnow2 ER / 16 outs1 ER / 14 outs-1
ATLTyler Mahle3 ER / 15 outs1 ER / 19 outs-2
Decision internals: run factors home×1.064 / away×0.925; savant lineup adjustment applied

Player-level breakdown (projected vs actual)

Every value is actual / projected. Run impact approximates how far each hitter's real line moved run expectancy from its projection; it orders the movers and is not a published stat.

Top deviations that drove the game:

Pitcher versus batter: what actually broke this game

Per-pitch matchup fields are not populated in the current feeds, so this is reconstructed from the settled box: each starter's workload-adjusted ERA, the bullpen share behind him, and the opposing lineup's real production against its projection, with the hitters who beat that projection named.

AWAY pitching

Tyler Glasnow (LAD) threw 14 outs, 1 ER = 1.93 ERA against a projected 3.38 ERA (-1.45 ERA error)

Bullpen behind him: 0 ER over 2 outs.

The HOME lineup he faced produced 0 runs on 0 hits and 0 HR, against a projected 0 runs / 0 hits (0 runs vs projection).

No individual hitter beat his projection by a meaningful margin.

Verdict: offense: the lineup scored well below its projection

HOME pitching

No settled pitching line for this club. The forecast named Tyler Mahle (ATL) at a projected 5.4 ERA, but the per-player feed carries no pitching row for him in this game, so the actual-versus-projected comparison cannot be made on this side. That is a source-coverage gap in the settled box, not a forecasting failure.

Bullpen behind him: 0 ER over 0 outs.

The AWAY lineup he faced produced 3 runs on 5 hits and 1 HR, against a projected 6 runs / 9 hits (-3 runs vs projection).

Who did the damage to him:

  • Andy Pages: 2-for-3, 0 HR, 2 RBI [+0.94 runs vs projection] season xwOBA 0.343, elite - real projection error
  • Max Muncy: 1-for-4, 1 HR, 1 RBI [+0.93 runs vs projection] season xwOBA 0.349, elite - real projection error
  • Kyle Tucker: 1-for-3, 0 HR, 0 RBI [+0.33 runs vs projection] season xwOBA 0.331, above average - a good day, not a model error

Verdict: neither side broke materially - the result is closer to variance

Starting pitchers & relievers: actual / projected + context (ERA is workload-aware: ER over 9 innings, so a short blow-up is not read like a quality start; ERA error in parentheses when material. exp BB and exp SO are the continuous rate expectations. The integer beside each is a simulation draw reconciled to the opposing simulated batting box, so it is not the line that ranks pitchers: on the 2026-09-07 slate the integers published 39 walks and 121 strikeouts against 51 and 130 real, while these expectations landed on 50.4 and 132.6.)

PitcherTeamOutsERAERHHRBBexp BBSOexp SOContext (as-of)
LADTyler Glasnow (Starter)14 / 161.93 / 3.381 / 21 / 40 / 25 / 01.835 / 56.81venue away: 2.84 vs 4.25 ERA (ok) · opp run factor 1.06 (strong) · 13 prior appearances this season
LADAlex Vesia (Middle Reliever)2 / 30 / 00 / 01 / 00 / 00 / 00.450 / 11.34

Hitters: actual / projected (sorted by run impact vs projection)

BatterTeamABH2B3BHRRBIRBBSORun impactSeason xwOBASignal
Freddie Freeman (1B)LAD4 / 50 / 30 / 00 / 00 / 00 / 00 / 10 / 00 / 2-1.410.363 elitebad day
Will Smith (C)LAD4 / 50 / 10 / 00 / 00 / 10 / 20 / 10 / 02 / 0-1.40.389 elitebad day
Teoscar Hernández (LF)LAD4 / 31 / 10 / 00 / 00 / 10 / 11 / 20 / 12 / 1-1.260.332 above averagebad day
Andy Pages (CF)LAD3 / 42 / 00 / 00 / 00 / 02 / 00 / 00 / 00 / 00.940.343 eliteprojection too low
Max Muncy (3B)LAD4 / 41 / 10 / 00 / 01 / 01 / 21 / 00 / 00 / 20.930.349 eliteprojection too low
Shohei Ohtani (DH)LAD3 / 30 / 10 / 00 / 00 / 00 / 01 / 11 / 11 / 1-0.470.397 elite—
Enrique Hernández (2B)LAD2 / 40 / 10 / 00 / 00 / 00 / 10 / 00 / 00 / 1-0.470.279 weak—
Mookie Betts (SS)LAD4 / 40 / 00 / 00 / 00 / 00 / 00 / 10 / 10 / 1-0.330.339 above average—
Kyle Tucker (RF)LAD3 / 41 / 10 / 00 / 00 / 00 / 00 / 01 / 00 / 00.330.331 above average—
Full model trace, player evidence, and audit findings

Fundamental evidence entering the pick

SignalHome-away edgeMeaning
Season quality-0.61positive favors home; negative favors away
Recent form-0.314positive favors home; negative favors away
Starting-pitcher matchup0.139positive favors home; negative favors away
Composite-0.469positive favors home; negative favors away

Score and confidence evolution

StageAway-home runsConfidenceWhat changed
historical_ml4.7-3.97n/aBase ML historical model prediction
variance_applied5-4n/aDeterministic baseline target (variance factor 1.0)
enhanced_prediction5-40.507Enhanced ML with recent form, H2H, low-score analysis (confidence shrunk by matchup_recency_guardrail)
kpi_layer5-4n/aSavant KPI blend applied to the model target
embedded_savant_run_environment6-4n/aTarget score adjusted by temporal Savant lineup quality versus opposing starter quality
fundamental_edge_target_review6-4n/aRefreshed score target and win probability after Savant/pitcher/team-strength adjustments
capped_target6-4n/aCapped at max 12 realistic runs
simulation_result6-4n/aFinal inning-by-inning simulation result

Official postgame stage attribution

StageBeforeAfterToward final pickWhat changed
variance_applied4.7-3.975-40.276Deterministic baseline target (variance factor 1.0)
enhanced_prediction5-45-4-0Enhanced ML with recent form, H2H, low-score analysis (confidence shrunk by matchup_recency_guardrail)
kpi_layer5-45-4-0Savant KPI blend applied to the model target
embedded_savant_run_environment5-46-41Target score adjusted by temporal Savant lineup quality versus opposing starter quality
fundamental_edge_target_review6-46-4-0Refreshed score target and win probability after Savant/pitcher/team-strength adjustments
capped_target6-46-4-0Capped at max 12 realistic runs
simulation_result6-46-4-0Final inning-by-inning simulation result

Largest player-level adjustments from the ultra-detailed trace

These are pregame model adjustments, not claims about actual postgame player error.

TeamPlayerRoleNet effectLargest change
LADTyler Glasnowpitcher / Starterworsepredicted_BB -4
LADBrock Stewartpitcher / Middle Reliever (High Leverage)worsepredicted_SO 4
ATLDylan Doddpitcher / Middle Relieverbetterpredicted_ER -4
ATLTyler Mahlepitcher / Starterworsepredicted_SO 3
ATLGrant Holmespitcher / Long Relieverworsepredicted_ER 2
LADFreddie Freemanbatter / 1Bworsepredicted_H 1.91
ATLAustin Rileybatter / 3Bworsepredicted_SO 1.762
LADMax Muncybatter / 3Bworsepredicted_RBI 1.71

Structural audit findings

SeverityRuleFindingSubject
infoRECONCILIATION_PROPAGATIONNo score_target_reconciliation step was used for this game.

MIL@SDHIT

Predicted: MIL 6-5 (conf -0.01, toss_up)Actual: MIL 3-1Brier 0.245total bias +7
Root cause: Toss-up that went our way
Evidence-backed diagnosis
Quantified contributing factors
TeamStarterProjectedActualER err
MILRobert Gasser2 ER / 11 outs1 ER / 12 outs-1
SDWalker Buehler3 ER / 11 outs1 ER / 9 outs-2
Decision internals: run factors home×0.973 / away×1.017; savant lineup adjustment applied

Player-level breakdown (projected vs actual)

Every value is actual / projected. Run impact approximates how far each hitter's real line moved run expectancy from its projection; it orders the movers and is not a published stat.

Top deviations that drove the game:

Pitcher versus batter: what actually broke this game

Per-pitch matchup fields are not populated in the current feeds, so this is reconstructed from the settled box: each starter's workload-adjusted ERA, the bullpen share behind him, and the opposing lineup's real production against its projection, with the hitters who beat that projection named.

AWAY pitching

Robert Gasser (MIL) threw 12 outs, 1 ER = 2.25 ERA against a projected 4.91 ERA (-2.66 ERA error)

Bullpen behind him: 0 ER over 12 outs.

The HOME lineup he faced produced 0 runs on 0 hits and 0 HR, against a projected 0 runs / 0 hits (0 runs vs projection).

No individual hitter beat his projection by a meaningful margin.

Verdict: offense: the lineup scored well below its projection

HOME pitching

No settled pitching line for this club. The forecast named Walker Buehler (SD) at a projected 7.36 ERA, but the per-player feed carries no pitching row for him in this game, so the actual-versus-projected comparison cannot be made on this side. That is a source-coverage gap in the settled box, not a forecasting failure.

Bullpen behind him: 0 ER over 0 outs.

The AWAY lineup he faced produced 3 runs on 10 hits and 0 HR, against a projected 6 runs / 8 hits (-3 runs vs projection).

Who did the damage to him:

  • Garrett Mitchell: 2-for-4, 0 HR, 1 RBI [+1.56 runs vs projection] season xwOBA 0.353, elite - real projection error
  • Jackson Chourio: 1-for-4, 0 HR, 1 RBI [+0.8 runs vs projection] season xwOBA 0.344, elite - real projection error
  • William Contreras: 2-for-5, 0 HR, 0 RBI [+0.61 runs vs projection] season xwOBA 0.334, above average - real projection error

Verdict: neither side broke materially - the result is closer to variance

Starting pitchers & relievers: actual / projected + context (ERA is workload-aware: ER over 9 innings, so a short blow-up is not read like a quality start; ERA error in parentheses when material. exp BB and exp SO are the continuous rate expectations. The integer beside each is a simulation draw reconciled to the opposing simulated batting box, so it is not the line that ranks pitchers: on the 2026-09-07 slate the integers published 39 walks and 121 strikeouts against 51 and 130 real, while these expectations landed on 50.4 and 132.6.)

PitcherTeamOutsERAERHHRBBexp BBSOexp SOContext (as-of)
MILRobert Gasser (Starter)12 / 112.25 / 4.911 / 23 / 31 / 01 / 11.663 / 43.3venue away: 4.66 vs 3.4 ERA (worse here) · opp run factor 0.97 (average) · 21 prior appearances this season
MILAaron Ashby (Setup Man)9 / 40 / 6.75 (-6.75)0 / 10 / 10 / 12 / 00.423 / 21.56
MILTrevor Megill (Closer)3 / 120 / 00 / 00 / 30 / 00 / 10.182 / 11.07

Hitters: actual / projected (sorted by run impact vs projection)

BatterTeamABH2B3BHRRBIRBBSORun impactSeason xwOBASignal
Brice Turang (2B)MIL5 / 41 / 30 / 10 / 00 / 00 / 20 / 10 / 10 / 1-1.580.344 elitebad day
Garrett Mitchell (CF)MIL4 / 42 / 00 / 01 / 00 / 01 / 01 / 00 / 00 / 21.560.353 eliteprojection too low
Joey Ortiz (3B)MIL4 / 40 / 20 / 00 / 00 / 00 / 00 / 10 / 01 / 0-0.940.297 below averageprojection too high
Christian Yelich (DH)MIL4 / 51 / 10 / 00 / 00 / 10 / 20 / 20 / 01 / 0-0.930.308 averageno signal
Jackson Chourio (LF)MIL4 / 51 / 00 / 00 / 00 / 01 / 00 / 01 / 00 / 00.80.344 eliteprojection too low
William Contreras (C)MIL5 / 32 / 00 / 00 / 00 / 00 / 00 / 10 / 10 / 20.610.334 above averageprojection too low
Sal Frelick (RF)MIL3 / 41 / 00 / 00 / 00 / 01 / 01 / 00 / 01 / 10.470.281 weak—
Jake Bauers (1B)MIL1 / 41 / 10 / 10 / 00 / 00 / 01 / 13 / 10 / 10.350.371 elite—
Cooper Pratt (SS)MIL4 / 51 / 11 / 10 / 00 / 00 / 20 / 00 / 00 / 200.315 average—
Full model trace, player evidence, and audit findings

Fundamental evidence entering the pick

SignalHome-away edgeMeaning
Season quality-0.723positive favors home; negative favors away
Recent form0.334positive favors home; negative favors away
Starting-pitcher matchup-0.045positive favors home; negative favors away
Composite-0.233positive favors home; negative favors away

Score and confidence evolution

StageAway-home runsConfidenceWhat changed
historical_ml4.32-3.96n/aBase ML historical model prediction
variance_applied4-4n/aDeterministic baseline target (variance factor 1.0)
enhanced_prediction4-50.505Enhanced ML with recent form, H2H, low-score analysis (confidence shrunk by projected_margin_is_one_run)
kpi_layer4-5n/aSavant KPI blend applied to the model target
embedded_savant_run_environment4-5n/aTarget score adjusted by temporal Savant lineup quality versus opposing starter quality
fundamental_edge_target_review6-5n/aRefreshed score target and win probability after Savant/pitcher/team-strength adjustments
capped_target6-5n/aCapped at max 12 realistic runs
simulation_result6-5n/aFinal inning-by-inning simulation result

Official postgame stage attribution

StageBeforeAfterToward final pickWhat changed
variance_applied4.32-3.964-4-0.358Deterministic baseline target (variance factor 1.0)
enhanced_prediction4-44-5-1Enhanced ML with recent form, H2H, low-score analysis (confidence shrunk by projected_margin_is_one_run)
kpi_layer4-54-5-0Savant KPI blend applied to the model target
embedded_savant_run_environment4-54-5-0Target score adjusted by temporal Savant lineup quality versus opposing starter quality
fundamental_edge_target_review4-56-52Refreshed score target and win probability after Savant/pitcher/team-strength adjustments
capped_target6-56-5-0Capped at max 12 realistic runs
simulation_result6-56-5-0Final inning-by-inning simulation result

Largest player-level adjustments from the ultra-detailed trace

These are pregame model adjustments, not claims about actual postgame player error.

TeamPlayerRoleNet effectLargest change
MILRobert Gasserpitcher / Starterdeboostedpredicted_ER -3
MILTrevor Megillpitcher / Closerworsepredicted_H 3
SDWalker Buehlerpitcher / Starterworsepredicted_BB 3
SDAdrian Morejonpitcher / Closerworsepredicted_H 3
SDJackson Merrillbatter / CFworsepredicted_RBI 2.46
SDAustin Haysbatter / DHboostedpredicted_AB 2.325
MILAaron Ashbypitcher / Setup Manworsepredicted_SO 2
SDFernando Tatis Jr.batter / RFworsepredicted_AB -1.96

Structural audit findings

SeverityRuleFindingSubject
infoRECONCILIATION_PROPAGATIONNo score_target_reconciliation step was used for this game.

TB@NYYMISS

Predicted: NYY 3-4 (conf +0.09, lean)Actual: TB 4-3Brier 0.296total bias +0
Root cause: Several errors of similar size
Evidence-backed diagnosis
Quantified contributing factors

No large single-factor errors.

TeamStarterProjectedActualER err
TBNick Martinez2 ER / 13 outs2 ER / 11 outs0
NYYMax Fried2 ER / 16 outs4 ER / 17 outs2
Decision internals: run factors home×0.966 / away×0.98; savant lineup adjustment applied

Player-level breakdown (projected vs actual)

Every value is actual / projected. Run impact approximates how far each hitter's real line moved run expectancy from its projection; it orders the movers and is not a published stat.

Top deviations that drove the game:

Pitcher versus batter: what actually broke this game

Per-pitch matchup fields are not populated in the current feeds, so this is reconstructed from the settled box: each starter's workload-adjusted ERA, the bullpen share behind him, and the opposing lineup's real production against its projection, with the hitters who beat that projection named.

AWAY pitching

Nick Martinez (TB) threw 11 outs, 2 ER = 4.91 ERA against a projected 4.15 ERA (0.76 ERA error)

Bullpen behind him: 0 ER over 5 outs.

The HOME lineup he faced produced 0 runs on 0 hits and 0 HR, against a projected 0 runs / 0 hits (0 runs vs projection).

No individual hitter beat his projection by a meaningful margin.

Verdict: neither side broke materially - the result is closer to variance

HOME pitching

No settled pitching line for this club. The forecast named Max Fried (NYY) at a projected 3.38 ERA, but the per-player feed carries no pitching row for him in this game, so the actual-versus-projected comparison cannot be made on this side. That is a source-coverage gap in the settled box, not a forecasting failure.

Bullpen behind him: 0 ER over 0 outs.

The AWAY lineup he faced produced 3 runs on 6 hits and 1 HR, against a projected 3 runs / 6 hits (0 runs vs projection).

Who did the damage to him:

  • Ryan Vilade: 1-for-2, 1 HR, 1 RBI [+0.6 runs vs projection] season xwOBA 0.327, above average - real projection error
  • Taylor Walls: 1-for-3, 0 HR, 0 RBI [+0.47 runs vs projection] season xwOBA 0.251, weak - a good day, not a model error

Verdict: neither side broke materially - the result is closer to variance

Starting pitchers & relievers: actual / projected + context (ERA is workload-aware: ER over 9 innings, so a short blow-up is not read like a quality start; ERA error in parentheses when material. exp BB and exp SO are the continuous rate expectations. The integer beside each is a simulation draw reconciled to the opposing simulated batting box, so it is not the line that ranks pitchers: on the 2026-09-07 slate the integers published 39 walks and 121 strikeouts against 51 and 130 real, while these expectations landed on 50.4 and 132.6.)

PitcherTeamOutsERAERHHRBBexp BBSOexp SOContext (as-of)
TBNick Martinez (Starter)11 / 134.91 / 4.152 / 25 / 40 / 01 / 20.93 / 43.17venue away: 2.38 vs 3.9 ERA (ok) · opp run factor 0.97 (strong) · 31 prior appearances this season
TBCam Booser (Setup Man)2 / 20 / 00 / 00 / 00 / 00 / 00.130 / 10.71
TBBryan Baker (Closer)3 / 30 / 00 / 00 / 10 / 01 / 00.292 / 10.93

Hitters: actual / projected (sorted by run impact vs projection)

BatterTeamABH2B3BHRRBIRBBSORun impactSeason xwOBASignal
Jonathan Aranda (1B)TB3 / 31 / 10 / 00 / 00 / 11 / 10 / 20 / 10 / 0-1.260.343 elitebad day
Ryan Vilade (RF)TB2 / 31 / 10 / 00 / 01 / 01 / 01 / 00 / 10 / 20.60.327 above averageprojection too low
Junior Caminero (3B)TB4 / 41 / 20 / 00 / 00 / 00 / 11 / 00 / 01 / 0-0.470.364 elite—
Liam Hicks (C)TB4 / 40 / 10 / 00 / 00 / 00 / 00 / 00 / 02 / 1-0.470.319 average—
Taylor Walls (SS)TB3 / 41 / 00 / 00 / 00 / 00 / 00 / 00 / 00 / 10.470.251 weak—
Richie Palacios (2B)TB3 / 30 / 00 / 00 / 00 / 00 / 00 / 00 / 12 / 1-0.330.306 average—
Yandy Díaz (DH)TB4 / 41 / 00 / 00 / 00 / 00 / 00 / 10 / 12 / 00.140.346 elite—
Jonny DeLuca (CF)TB3 / 41 / 10 / 00 / 00 / 00 / 11 / 00 / 00 / 100.261 weak—
Full model trace, player evidence, and audit findings

Fundamental evidence entering the pick

SignalHome-away edgeMeaning
Season quality0.176positive favors home; negative favors away
Recent form0.182positive favors home; negative favors away
Starting-pitcher matchup-0.014positive favors home; negative favors away
Composite0.291positive favors home; negative favors away

Score and confidence evolution

StageAway-home runsConfidenceWhat changed
historical_ml3.96-5.57n/aBase ML historical model prediction
variance_applied4-6n/aDeterministic baseline target (variance factor 1.0)
enhanced_prediction3-40.544Enhanced ML with recent form, H2H, low-score analysis (confidence shrunk by projected_margin_is_one_run, matchup_recency_guardrail)
kpi_layer3-4n/aSavant KPI blend applied to the model target
embedded_savant_run_environment3-4n/aTarget score adjusted by temporal Savant lineup quality versus opposing starter quality
fundamental_edge_target_review3-4n/aRefreshed score target and win probability after Savant/pitcher/team-strength adjustments
capped_target3-4n/aCapped at max 12 realistic runs
simulation_result3-4n/aFinal inning-by-inning simulation result

Official postgame stage attribution

StageBeforeAfterToward final pickWhat changed
variance_applied3.96-5.574-60.391Deterministic baseline target (variance factor 1.0)
enhanced_prediction4-63-4-1Enhanced ML with recent form, H2H, low-score analysis (confidence shrunk by projected_margin_is_one_run, matchup_recency_guardrail)
kpi_layer3-43-40Savant KPI blend applied to the model target
embedded_savant_run_environment3-43-40Target score adjusted by temporal Savant lineup quality versus opposing starter quality
fundamental_edge_target_review3-43-40Refreshed score target and win probability after Savant/pitcher/team-strength adjustments
capped_target3-43-40Capped at max 12 realistic runs
simulation_result3-43-40Final inning-by-inning simulation result

Largest player-level adjustments from the ultra-detailed trace

These are pregame model adjustments, not claims about actual postgame player error.

TeamPlayerRoleNet effectLargest change
TBNick Martinezpitcher / Starterbetterpredicted_H -4
TBCole Sulserpitcher / Middle Relieverworsepredicted_H 4
NYYMax Friedpitcher / Starterworsepredicted_ER 2
NYYRyan Weatherspitcher / Middle Relieverbetterpredicted_ER -2
NYYCody Bellingerbatter / LFbetterpredicted_AB -1.65
NYYLuis García Jr.batter / 1Bbetterpredicted_R 1.533
TBJonathan Arandabatter / 1Bworsepredicted_R 1.519
TBYandy Díazbatter / DHworsepredicted_H -1.35

Structural audit findings

SeverityRuleFindingSubject
infoRECONCILIATION_PROPAGATIONNo score_target_reconciliation step was used for this game.

Cross-game lever tension

Each candidate fix, and exactly which games it would help versus hurt. A lever that repairs one game and breaks two is visible here before it is proposed.

score.variance_multiplier / score.variance_floor (widen run distributions)

Targets: brier_score, calibration_error · 0 helped vs 0 hurt
Would help
  • none
Would hurt / risk
  • none

player.pitcher.v4 form weights / player.pitcher_prior_games

Targets: starter_er_mae, starter_outs_mae · 0 helped vs 0 hurt
Would help
  • none
Would hurt / risk
  • none

recent.* / season.* run-mean weighting

Targets: team_run_mae, total_run_mae, accuracy · 3 helped vs 1 hurt
Would help
  • CLE@CHW (hit): team runs off by 5
  • LAD@ATL (hit): team runs off by 5
  • MIL@SD (hit): team runs off by 7
Would hurt / risk
  • TB@NYY (miss): team runs already close (off 2); reweight risks disturbing it

Luna deep post-mortem (full)

> Coverage receipt: COMPLETE · 9/8 sections; 4/4 games; 6/6 causes; 7/7 sources

1. Evidence receipt and gaps

All 7 source_manifest entries are recorded as loaded. The supplied evidence identifies each by path, purpose, and byte count:

The manifest says the files were loaded; this analysis cannot independently verify their contents against the paths. All 4 games listed in the diagnosis are reviewed, matching games_reviewed: 4, expected_games: 4, and the coverage matrix’s 4/4 counts for structural audits, deep audits, continuous-learning games, canonical artifacts, and starter comparisons.

Gaps and internal inconsistencies to retain in the record:

2. Executive diagnosis

Winner accuracy

The slate went 3/4 (75%), with one miss, TB@NYY. This exceeds the supplied walk-forward accuracy of 0.570149 and historical winner accuracy of 0.600414, but four games do not establish improved performance. The cross-slate winner-accuracy trend is explicitly flat, with mean 0.7381 over the reported series.

A correct winner is not evidence that the score or confidence was good. Three games had the correct winner but substantial run errors.

Calibration quality

The four-game confidence bucket reports average confidence 0.5228, hit rate 0.75, and signed bucket calibration error −0.2272, labeled underconfident under the stated convention (published confidence minus observed hit rate). Its weighted absolute calibration error is 0.2272. That is a large single-slate mismatch, but the bucket contains only four games and the causal register explicitly says not to change calibration on this slate alone.

The reported published pick-side confidence values average approximately 0.528; the bucket’s 0.5228 matches the average of the displayed *home* probabilities (including probabilities below 0.5), not the average pick-side confidence. The signed-error definition is stated, but the confidence convention underlying that bucket is not fully clear. The conclusion is still poor slate-level alignment, not a reliable direction for a global curve.

Score accuracy

Published team-run MAE is 2.375 and total-run MAE is 3.75 across four games. Team-run absolute errors are 5, 5, 7, and 2. Predicted margins are compressed: 1, 2, 1, and 1 runs, versus actual margins of 6, 3, 2, and 1. The holdout run-model R² values are near zero: home 0.002143, away 0.030936, total 0.002415. Exact score outputs therefore have weak demonstrated signal.

Starter accuracy

All four games have starter comparisons in starter_lines, with identity matches true. The starter outcomes were mixed: CLE’s Daniel Espino allowed one earned run in two outs against a 3-ER projection, while TB’s Max Fried allowed four ER against a 2-ER projection. These comparisons do not show a uniform slate-wide starter miss, and the conspicuous Espino result is identified as an outlier/variance event. The diagnosis does not support tuning starter weights from this slate alone.

Artifact integrity

No supplied game structural audit has critical, error, or warning findings; all four are PASS, and the game diagnostic says the forecast file was clean. Coverage is complete for the four games. These facts argue against a saved-score artifact causing the TB miss. They do not resolve the internal MIL@SD probability-side contradiction or the missing TB player join. The latter are evidence/contract-quality issues to address in reporting and trace validation.

Causal issue register: reconciliation of every entry

No critical or error item appears in the causal register. The separate internal probability-label inconsistency is an evidence/contract issue discussed in section 6.

3. Every game

“Home-minus-away edge” below is the supplied signed system edge, not a probability distance from 50%. A 0.12 signed home-away edge is moderate, not a near coin flip. Runs and starter lines are the supplied projections and outcomes; no missing player results are inferred.

CLE@CHW
LAD@ATL
MIL@SD
TB@NYY

4. Miss reconstruction

TB@NYY: earliest wrong-direction evidence and attribution

The earliest explicitly supplied pregame evidence already favored the result that lost: season edge +0.1757, recent edge +0.182, and composite home edge +0.2909 all favored NYY; pitcher edge was only −0.0142 for the home side. The confidence trace then reports governed probability 0.5665 for the home pick, and the published home probability remains 0.544016. The system therefore did not merely miss on a nominal 0.50 selection: its published lean was for NYY at a 0.088 home-away edge.

The probability fields are not fully ordered transparently: the trace governor input is 0.521431, but the governed output is 0.5665; the separate lineage raw-model field is 0.6185. The named calibration/governor, score-coherence, and recency stages are recorded, so the supplied evidence does not justify calling the calibrated-to-published movement a bypass. It does justify checking the mapping and semantics of the multiple raw fields.

Attribution by category:

Pipeline-stage quality across all stages and transitions

All stages are measured against official final scores; positive deltas versus historical_ml are regressions.

StageWinner hitsWinner accuracyTeam-run MAETotal-run MAEMargin MAEChange in winner direction
historical_ml3/40.751.88983.75942.6745Baseline
variance_applied2/40.501.8753.752.75MIL: MIL → TIE
enhanced_prediction2/40.502.03.03.0MIL: TIE → SD
kpi_layer2/40.502.03.03.0No change
embedded_savant_run_environment2/40.502.1253.252.75No change
fundamental_edge_target_review3/40.752.3753.752.25MIL: SD → MIL
capped_target3/40.752.3753.752.25No change
simulation_result3/40.752.3753.752.25No change
published_final3/40.752.3753.752.25No change

The historical → variance transition regressed winner accuracy by one hit (−0.25) on MIL@SD; its team-run MAE improved only 0.0148. The next stage changed MIL from tie to SD without restoring the correct direction. The embedded-Savant-to-fundamental-review transition later flipped MIL from SD to MIL and restored the slate to 3/4. That recovery does not erase the intermediate regression. From fundamental review onward, the score and winner did not change through publication; simulation produced no winner intervention.

Team-run MAE ended 0.4852 worse than historical ML, despite margin MAE improving 0.4245. Total-run MAE finished essentially unchanged from the historical baseline (3.75 versus 3.7594). This is not a consistent score-quality improvement.

5. Cross-game counterfactuals

Every supplied lever_tension entry:

  1. score.variance_multiplier / score.variance_floor (widen run distributions), targets Brier/calibration
  1. player.pitcher.v4 form weights / player.pitcher_prior_games, targets starter ER/outs MAE
  1. recent.* / season.* run-mean weighting

Tempting one-game fixes to reject:

6. Data and contract defects

Audit findings and severity counts
Specific contract and data issues
  1. MIL probability-side label inconsistency: lineage says home side/pick 0.505; game score, displayed edge, and diagnostic home probability imply away MIL is the pick at 0.505. Treat as an evidence/contract error requiring label validation. The contradictory label should not be silently used in calibration summaries.
  2. Probability-field semantics: lineage’s separate raw-model probability differs from the governor input/trace raw pick value for all four games. The named stages explain the calibrated/governed and calibrated-to-published changes at a high level, but the raw-field definitions and transition ordering should be explicit.
  3. probability_reversions incomplete event identification: one blend-stage flip is reported, but games is empty. No game can be named from this field, so it is not possible to check that flip against the per-game trace.
  4. TB player join gap: no per-player actuals joined for TB@NYY. This is a forensic coverage gap for player causality, not a demonstrated score artifact defect.
  5. Calibration bucket convention: the reported average 0.5228 matches the mean of the displayed home probabilities, while the prediction outcomes are pick-side outcomes. Because the bucket’s confidence convention is not fully described and MIL is mislabeled, its summary should be interpreted cautiously.
Complete pick-side probability lineage

Values below preserve the supplied lineage. “Governor input” corresponds to the trace’s raw pick probability; the separate raw-model field is also shown so the distinction is visible.

GameSeparate raw modelGovernor input → output / calibratedScore coherence → publishedRecency / recorded transformation
CLE@CHW0.58460.555841 → 0.5486 / 0.54860.548621 → 0.535129Guardrail applied; named score coherence then matchup-recency
LAD@ATL0.50970.535236 → 0.5084 / 0.50840.508443 → 0.507177Guardrail applied; published value recorded as matching calibrated/governed value
MIL@SD0.50000.524296 → 0.505 / 0.5050.505 → 0.505No guardrail; published equals calibrated. Side label conflicts with game record.
TB@NYY0.61850.521431 → 0.5665 / 0.56650.566481 → 0.544016Guardrail applied; named score coherence then matchup-recency

All four lineage entries say unexplained_material_delta: false. Calibrated-to-published movements are recorded as score-coherence and/or recency transformations; the TB material movement is therefore not called a bypass. The audit register specifically says TB’s published value being above a calibrated one is not a governor bypass when the recorded transformations explain it. The raw-model/governor-input distinction and the absent numeric recency factors remain trace-clarity issues, not established unrecorded bypasses.

7. Cross-slate persistence

Cross-slate findings and escalation status

The report includes 10 prior slates and an 11-slate trend window. Finding streaks:

FindingConsecutive slatesPresent now?Persistence interpretation
pipeline_winner_instability1YesCurrent-slate regression; not an established multi-slate streak.
score_margin_compression0NoIncidence in window is 4, but it is not current and has no present streak.
simulation_inert_on_slate11YesEscalated, established failure pattern; do not dismiss as single-slate noise.
single_slate_calibration_instability5YesEscalated persistent calibration pattern.
weak_run_model_signal5YesEscalated persistent near-zero run-signal pattern.

For every escalated finding:

The self-assessment separately records run_model_near_zero_signal, with total/home/away R² 0.002415/0.002143/0.030936, as an operator action. This agrees with the escalated weak-run-signal finding rather than adding a reason for a nightly parameter adjustment.

Structural cross-slate evidence
Metric trends and top-confidence-pick streak

The trend directions are explicitly:

The top-confidence-pick loss streak is 1: the 20261005 top pick missed, 20261006 hit, and 20261007 missed. The current slate’s top-confidence pick is therefore a loss but does not extend a consecutive loss streak from 20261005 because a hit intervened. Two dates in the supplied sequence are blank/unknown and should not be treated as results.

8. Adjustments for today

These are bounded proposals for shadow evaluation, not live changes. Persistence is ranked ahead of single-slate evidence. No promotion is recommended from this diagnosis alone.

  1. Persistent calibration instability — shadow confidence.empirical_max_weight upward by +0.02 absolute.
  1. Persistent simulation inertness — code/diagnostic action, not a parameter move.
  1. Persistent weak run signal — isolated feature/target backtest, not a nightly parameter change.
  1. Strongest single-slate structural driver — shadow score.variance_multiplier upward by 2% relative to its current value.

No recent.* / season.* run-mean change is recommended today: its slate tension is 3 helped versus 1 hurt, but the entry does not specify the direction or sub-weight, and its clearest evidence concerns run errors rather than winners. No pitcher-weight change is recommended from this mixed slate.

9. Bottom line

Known: the slate finished 3/4, with three correct winners but materially inaccurate scores; TB@NYY was the only winner miss, despite a moderate 0.088 published home edge. The pipeline temporarily moved MIL in the wrong winner direction at variance application before later recovering. Run-model holdout signal is near zero, calibration instability and simulation inertness are persistent escalations, and the saved forecast artifacts passed the reported game-level structural checks.

Uncertain: the precise TB offensive/bullpen/player contribution, the causal source of the wrong team-run allocation, the interpretation of every raw probability field, and whether a variance change would improve outcomes. TB player actuals are missing; MIL probability-side lineage is internally inconsistent.

Safest next action for the very next slate: preserve the full probability and stage trace, add a contract check that rejects side/probability-label contradictions such as MIL@SD, and keep any calibration change in a bounded shadow experiment with rolling Brier/calibration monitoring. This addresses a concrete evidence-integrity risk without pretending that one slate identifies a winning model adjustment.