Luna deep analysis — slate 20261008

Coverage receipt: COMPLETE · 9/8 sections; 1/1 games; 5/5 causes; 7/7 sources

1. Evidence receipt and gaps

All seven source_manifest entries are present and marked loaded:

Game-level review: one game is supplied in games[]: CLE@CHW. Its official result is CLE 9, CHW 5. The game record says games_reviewed: 1, hits: 1, misses: 0; the continuous-learning summary says one settled game, also one hit and zero misses. Thus the available game-level result is internally consistent.

Coverage-count contradiction: the same evidence reports expected_games: 1, but canonical_artifacts_loaded: 2, continuous_learning_games: 2, forensic_deep_audit_games: 2, structural_audits_completed: 2, and forensic_deep_audit_games: 2. The causal register describes this as “2/1 games structurally audited.” These counts do not reconcile to the single supplied game record. The pipeline transitions also name TB@NYY, which is absent from games[] and has no supplied score, probability, or game-level audit here. I report that transition as evidence of a coverage/provenance gap, not as a second game that can be independently evaluated.

There are no listed starter comparisons for a second game, and the only player-level trace supplied is for CLE@CHW. I do not infer any missing TB@NYY results or player outcomes.

2. Executive diagnosis

Winner accuracy

• The one supplied game was a winner hit: CLE was predicted to win and won 9–5.
• Published away-win probability was 0.505; this was a marginal pick, not evidence of a strong winner forecast. The confidence edge was only 0.01, and conviction was toss_up.
• Slate winner accuracy is reported as 1.0, but the settled sample is one. It must not be treated as evidence of reliable performance.

Calibration quality

• The game Brier score is 0.245025, corresponding to the published 0.505 probability and a hit.
• The calibration monitor has one settled observation in the 0.50–0.55 bucket: confidence 0.505, observed hit rate 1.0, signed calibration error −0.495 under the stated “confidence minus hit rate” definition—i.e., underconfidence for this one observation.
• Weighted absolute calibration error is reported as 0.495. This is a large one-observation error, but the direction on the only bucket is underconfident. That conflicts with the self-assessment’s label confidence_overconfident and its “lower confidence caps” proposal. It also warrants caution with the cross-slate escalation’s prescribed increase in empirical shrinkage: the escalation is established as a recurring finding, but the direction of any adjustment is not validated by this single hit.
• The supplied cross-slate record nonetheless reports six consecutive slates of single_slate_calibration_instability; its persistent status is actionable, while the present one-game calibration reading is not enough to select a production change.

Score accuracy

• Prediction: CLE 5, CHW 4, total 9, away margin 1.
• Actual: CLE 9, CHW 5, total 14, away margin 4.
• Winner was correct, but both the exact score and the run environment were wrong: total runs were under-projected by 5, CLE runs by 4, CHW runs by 1. The listed team-run absolute error is 5; the stage-quality team-run MAE for this one game is 2.5 (the mean of the two team errors).
• Predicted margin was 1 versus actual margin 4, an absolute margin error of 3. The evidence records signed margin error −3 in an away-margin convention and +3 in a home-minus-away convention; these are consistent under opposite sign conventions.
• The single observed margin is compressed relative to the result (predicted margin ≤2; actual margin ≥4). It supports monitoring, not a general widening based on one blowout.

Starter accuracy

• CLE starter Parker Messick: projected 3 ER, 15 outs, 5.40 ERA; recorded 2 ER, 7 outs, 7.71 ERA. ER error is −1 (actual below projection), ERA error is +2.31 (actual ERA above projection), and the outs projection differs by 8. These measures point in different directions; they should not be reduced to one claim that the starter projection was simply “accurate.”
• CHW starter Hagen Smith: projected 0 ER, 8 outs, 0.00 ERA; recorded 0 ER, 2 outs, 0.00 ERA in the starter-lines object. The settled per-player feed says there is no pitching line for him and marks the line missing. The zero-ERA comparison is therefore not independently supported by that feed; outs differ by 6.
• The player-forensics summary attributes a 7.71 ERA to the CLE starter and reports the CHW starter’s line missing. Overall starter evidence is incomplete and should not be used to claim both starts were accurately forecast.

Artifact integrity

• The per-game forecast-file integrity observation says clean: 0 defects, 1 informational note; the game’s structural audit is PASS, with 0 critical, 0 error, 0 warning and 1 info.
• No supplied finding identifies a corrupted saved score artifact as the cause of the game result. The prediction missed the final run totals despite a structurally clean game artifact.
• However, probability provenance contains a raw-probability mismatch and the overall coverage counts do not reconcile. Those are auditability/contract concerns even though the supplied game artifact itself is marked clean.

Causal issue register — every entry reconciled

1. score_margin_compression — high, score distribution, CLE@CHW. Evidence: 1/1 predicted margins ≤2; 1/1 actual margins ≥4; mean predicted margin 1.00 versus actual 4.00. Action: check tail coverage and margin MAE across recent out-of-sample slates before widening. Guardrail: a single blowout does not justify widening every score prediction.
2. single_slate_calibration_instability — high, calibration, CLE@CHW. Evidence: weighted absolute calibration error 0.4950 across one game. Action: watch confidence buckets over the rolling window before changing calibration weight. Guardrail: one slate is far too small to establish a stable calibration curve.
3. weak_run_model_signal — high, model validation, CLE@CHW. Evidence: home/away/total run-model R² = 0.0021/0.0309/0.0024. Action: treat exact runs as low-confidence; investigate features/target rather than tuning score tails. Guardrail: small positive R² only means beating a mean-only reference; it does not make exact scores reliable.
4. complete_slate_audit_coverage — info, coverage, CLE@CHW. Evidence says “2/1 games structurally audited.” Action: retain a per-game audit receipt in each report. Guardrail: full audit coverage does not cancel game-level findings. The stated coverage count is internally inconsistent with the one supplied game record and must not be taken as proof that the unprovided game was reviewed here.
5. simulation_inert_on_slate — info, simulation, CLE@CHW. Evidence: 0 flip candidates and 0 published flips. Action: measure simulation contribution across rolling slates, separating score realization from winner flipping. Guardrail: zero winner flips is not itself a defect and does not mean no score-reconciliation work occurred. The cross-slate evidence separately escalates the recurring simulation issue, discussed below.

3. Every game

CLE@CHW — winner hit, score miss

Prediction and result

• Predicted: CLE 5, CHW 4; CLE winner.
• Actual: CLE 9, CHW 5; CLE winner.
• Correct-winner/wrong-score game: yes.
• Published home-win probability 0.495, away/pick probability 0.505. Home-minus-away edge −0.01; the system’s absolute edge is 0.01, which is described as toss_up. The diagnostic correctly cautions that an edge of 0.01 is not “the half-scale distance from 50%.”
• Conviction bucket: toss_up. No high-conviction pick is present.

Errors

• Brier: 0.245025.
• CLE team-run error: 4; CHW team-run error: 1; listed combined team-run absolute error: 5; stage-quality team-run MAE: 2.5.
• Total-run error/bias: predicted 9 versus actual 14, so −5 (under-projection).
• Margin: predicted away margin 1; actual away margin 4; absolute margin error 3.

Starter comparison

• CLE—Parker Messick, identity match:
• Projected: 3 ER, 15 outs, 5.40 ERA.
• Actual: 2 ER, 7 outs, 7.71 ERA.
• ER error −1; ERA error +2.31; outs short of projection by 8.
• CHW—Hagen Smith, identity match in the starter-lines object:
• Projected: 0 ER, 8 outs, 0.00 ERA.
• Recorded there: 0 ER, 2 outs, 0.00 ERA.
• The player feed explicitly has no pitching line for Smith, so the zero-ERA comparison is not independently established. Outs were 6 fewer than projected.
• The matchup breakdown identifies Smith’s settled-feed line as missing, with reason “no pitching line for this player in the settled per-player feed.” Do not interpret a projected/recorded 0.00 ERA as proof the projection was well supported.

Pregame edges, confidence and controls

• Season home-minus-away edge: +0.1605.
• Recent home-minus-away edge: +0.030.
• Pitcher home-minus-away edge: −0.0005.
• Composite home edge: −0.0853.
• Season quality edge: +0.2685; recent quality edge: −0.04. Season-quality margin adjustment was 0 because the quality edge was below the action threshold.
• Raw probability in model_trace: 0.526027; calibration sample size 571, empirical hit rate 0.5499; governed pick probability 0.505. Governor was applied.
• Recency guardrail was marked applied, but discount factor and reason are null. Do not infer a numerical recency discount.
• Starter-experience shrinkage was not applied; minimum starter games 21 and shrink factor 1.0.
• Score-coherence probability and published pick probability are both 0.505.
• A separate probability_lineage record says raw model pick probability was 0.500, rather than 0.526027. That discrepancy is a provenance issue, not a basis for choosing whichever raw value better explains the final pick.

Score path

• Historical ML: winner accuracy 0/1; margin MAE 5.429; team-run MAE 2.7145; total-run MAE 5.1472.
• Variance-applied: winner accuracy 0/1; margin MAE 5.000; team-run MAE 2.500; total-run MAE 5.000. Compared with historical ML, score errors improved, but winner accuracy did not.
• Enhanced prediction: winner accuracy 1/1; margin MAE 3.000; team-run MAE 2.500; total-run MAE 5.000.
• KPI, embedded Savant run environment, fundamental-edge target review, capped target, simulation result, and published final have the same listed metrics as enhanced prediction. No subsequent stage changed the measured result.
• The transition table says variance → enhanced changed CLE from CHW to CLE and improved CLE@CHW; this is the provided evidence that the enhanced stage corrected the winner direction. It also names TB@NYY, which cannot be reconciled to the supplied game list.

Important player-level evidence

• CLE’s offense was under-projected by 4 runs. The player feed reports five material deviations, of which three are labeled learnable from the hitter’s own contact quality:
• Angel Martínez: 0-for-3, 0 HR, 0 RBI against projections of 1.0 H and 1.0 HR; run impact −1.73; xwOBA .299, below average. Classified as model overrating a weak hitter.
• José Ramírez: 2-for-5, 1 HR, 3 RBI against projections of 0.0 H and 0.0 HR; impact +1.54; xwOBA .325, above average. Classified as model underrating a strong hitter.
• Steven Kwan: 1-for-3, 0 HR, 0 RBI against projections of 0.0 H and 0.0 HR; impact +1.13; xwOBA .328, above average. Also classified as model underrating a strong hitter.
• Nathaniel Lowe: 2-for-4, no HR/RBI against projections of 2.0 H and 1.0 HR; impact −1.55. Listed as a top mover, not among the three deviations supported by the stated contact-quality assessment.
• Travis Bazzana: 1-for-3, 1 RBI against projections of 0.0 H and 0.0 HR; impact +0.78. Also listed as a top mover, not among those three learnable cases.
• The remaining named contributors have smaller listed impacts: Jo Adell +0.33, Austin Hedges −0.33, Brayan Rocchio +0.33, and Chase DeLauter −0.14. Their supplied lines are not a basis for inventing further causal claims.
• Slate hitter totals also show projection weaknesses: AB 34 vs 30 actual (+13.3%); H 6 vs 8 (−25%); BB 5 vs 7 (−28.6%); SO 8 vs 2 (+300%); RBI 5 vs 7 (−28.6%); R 5 vs 7 (−28.6%); HR 2 vs 1 (+100%); 2B 0 vs 1 (−100%). For H, BB, SO, RBI, R and HR, a flat slate-mean hitter projection had lower reported MAE than the per-hitter projection. This is a one-slate diagnostic, not a stable player-model conclusion.

Audit and cause

• Structural audit: PASS, risk score 0; 108 good, 1 info, no critical/error/warning findings. Forecast-file integrity is reported clean, with one informational note.
• No primary or secondary driver is assigned (null); player-forensics verdict counts assign two deviations to variance and none to offense or pitching as a side-level verdict.
• This was a winner hit, but the CLE offense and total were materially under-projected. A correct winner does not make the score prediction good.

4. Miss reconstruction

Game losses: none in the supplied game list. Thus there is no losing pick for which to assign a wrong-winner cause. CLE@CHW is a winner hit and a score miss, not a winner loss. The unexplained TB@NYY transition cannot be reconstructed as a game result from this evidence.

For the score miss in CLE@CHW, the earliest relevant evidence and distinctions are:

• Bad input: no direct evidence establishes a bad team-score input. The feed does document a missing CHW starter line, and the raw probability values conflict (see Section 6); neither proves that an input caused the score miss.
• Bad weighting / run signal: the offense and total were under-projected, and several CLE hitter projections missed. The validated run models have near-zero holdout R². That is stronger evidence of weak run-prediction signal than of any specific one-game weighting mistake.
• Calibration: the confidence probability was nearly even and the winner happened to hit. Calibration is a recurring cross-slate issue, but it is not the demonstrated cause of the run-total shortfall.
• Starter error: Messick allowed fewer ER than projected but had a higher ERA and substantially fewer outs than projected. Smith’s settled per-player line is missing. The evidence does not isolate starter error as the main cause of CLE’s four-run excess.
• Offense/bullpen miss: CLE’s actual nine runs exceeded its projected five by four. The supplied diagnostics identify hitter deviations, but side-level player-forensics assigns the game closer to variance, not an offense verdict. Bullpen detail is insufficient to apportion the score error: the feed reports CLE bullpen ER 1 and CHW bullpen ER 0, but does not establish that bullpen performance caused the miss.
• Run-environment miss: total runs were under-projected by five; this is directly established. It is consistent with weak run-model signal and the supplied player deviations, but not enough to identify a unique causal lever.

Pipeline-stage quality and transitions

All listed stages have one game of measurement; interpret the metrics as one-game observations.

• Historical ML → variance improved margin MAE by 0.429 and team-run MAE by 0.2145, with no winner-accuracy change.
• Variance → enhanced improved margin MAE by 2.0 and changed CLE from CHW to CLE, improving this game’s winner direction. The transition also contains the unprovided TB@NYY direction change.
• Enhanced → KPI → embedded run environment → fundamental-edge review → capped target → simulation → published final shows no listed winner-direction or score-metric change.
• The table therefore records an early wrong winner direction that was recovered at enhanced prediction. A later recovery does not erase the initial wrong direction. The transition’s extra TB@NYY reference remains an audit gap.
• largest_team_run_regression_vs_base is labeled variance-applied, but its deltas versus historical ML are negative (improvements), not regressions. The label and numeric deltas are internally inconsistent; the numeric values show improvement on this one game.

5. Cross-game counterfactuals

The supplied lever_tension contains three entries; with only one game, its listed benefits and costs are limited to that game.

1. score.variance_multiplier / score.variance_floor — widen run distributions
2. Helps: none listed.
3. Hurts: none listed.
4. Net listed evidence: 0 helped, 0 hurt. The target field lists Brier score and calibration error, although the causal margin-compression finding is about score-distribution tails.
5. Decision: no production-wide widening is supported by this one result. The actual margin exceeded the predicted margin, but the register explicitly cautions against widening every score after one blowout. A bounded shadow test can be considered because margin compression recurs in the cross-slate streaks.

1. player.pitcher.v4 form weights / player.pitcher_prior_games
2. Helps: none.
3. Hurts: CLE@CHW—listed as a hit where the starter projection was “accurate (ER off 1),” so reweighting could disturb it.
4. Net: 0 helped versus 1 hurt.
5. Decision: do not change pitcher weights on this slate. The projection was not wholly accurate: ERA and outs differ materially, and Smith’s per-player line is missing. That limits the strength of the “accurate” characterization, but still gives no evidence for a broad pitcher-weight change.

1. recent.* / season.* run-mean weighting
2. Helps: CLE@CHW, whose team runs were off by 5.
3. Hurts: none listed.
4. Net: 1 helped, 0 hurt.
5. Decision: this is a plausible diagnostic lead, not a validated adjustment. The supplied lever name is a wildcard rather than an exact parameter, and the present slate is one game. Do not pick an arbitrary underlying parameter value.

Tempting one-game fixes to avoid: widening every score after the 9–5 result; changing pitcher-form weights based on this single starter comparison; fitting individual hitter weights to the deviations of Lowe or Bazzana without supporting cross-slate evidence; and treating the 0.505 winner probability as proof that confidence should be lowered or raised. Each would overfit sparse evidence or conflict with the supplied lever-tension/guardrail evidence.

6. Data and contract defects

Findings by reported audit severity

• Critical: none reported in the supplied structural audit summaries.
• Error: none reported.
• Warning: none reported.
• Info: one informational finding in the CLE@CHW structural audit (good: 108, info: 1), and one informational note in the forecast-file integrity summary. Their detailed text is not supplied, so they cannot be named more specifically. The causal register separately records two informational findings:
• complete_slate_audit_coverage, with evidence “2/1 games structurally audited,” action to retain per-game receipts, and guardrail that coverage does not cancel game-level findings.
• simulation_inert_on_slate, with 0 flip candidates and 0 published flips; its guardrail is that zero winner flips is not, by itself, a defect.
• No per-game audit finding is listed as critical, error, or warning. The count inconsistency and probability mismatch below are identifiable data/provenance defects, but the JSON does not assign them one of those formal severity labels.

Coverage reconciliation

The matrix says the expected game count is 1 while several loaded/audited counts are 2. The supplied game array and games_reviewed are both 1. The “2/1” causal-issue evidence therefore cannot be reconciled from this payload. The extra TB@NYY pipeline transition reinforces, but does not resolve, the discrepancy. Do not call coverage clean solely because all_games_structurally_audited is true.

Probability-lineage audit for the pick side

The published side was away/CLE at 0.505.

1. Raw model: model_trace reports raw pick probability 0.526027. probability_lineage instead reports raw model pick probability 0.500. These values conflict; the payload does not explain whether they have different definitions.
2. Calibrated: probability lineage reports calibrated pick probability 0.505, calibration sample size 571, empirical hit rate 0.5499.
3. Governor: lineage reports governor input 0.526027 and output 0.505. The model trace also says governor applied and governed pick probability 0.505.
4. Score coherence: reported as 0.505.
5. Recency: guardrail applied, but discount factor is null. No numerical recency transformation can be verified or inferred.
6. Published: pick probability 0.505, equal to calibrated, governed and score-coherence values; published_minus_calibrated is 0 and the lineage marks the published probability transformation as matching the calibrated/governed value.

The lineage does not label an unexplained material delta between calibrated/governed probability and published probability. However, the 0.500 versus 0.526027 raw-value conflict is unresolved, and the displayed raw-to-governor-input path has no explicit transformation description in the lineage. This is an observability/contract gap; the JSON does not establish that the final published probability bypassed a recorded calibration or governor transformation.

A separate probability_reversions record reports trained home-win probability 0.653438, blended home probability 0.575938, a blend-stage side change to home, and a published away side at home-win probability 0.495; it says the blend side did not survive publication (overwritten: 1). That material event is recorded in the separate reversions block, but it is not represented as a step in the pick-side probability_lineage. Treat this as an incomplete cross-block trace, not proof of an unrecorded bypass.

Model/process defects versus presentation/artifact concerns

• The score and starter misses are prediction-quality issues, not reported file corruption.
• Near-zero run-model R² and the hitter projection diagnostics are model-validation concerns.
• The missing Hagen Smith settled-feed line is a data completeness limitation.
• Conflicting raw probability values and unresolved game coverage are contract/provenance issues.
• The forecast file is expressly reported clean; no presentation bug is established as the reason for this game’s pick or score.

7. Cross-slate persistence

Required structural blocks

• margin_distribution: one row, CLE@CHW; predicted margin 1, actual margin 4, signed margin error −3. One observation only.
• pipeline_stage_quality.transitions: winner direction first remains wrong through variance-applied, then changes from CHW to CLE at enhanced prediction; later stages show no change. The TB@NYY references are not corroborated by the game list.
• calibration_monitoring: one settled observation, confidence 0.505, actual hit rate 1.0, signed error −0.495 (underconfident for the observed bucket), weighted absolute error 0.495.
• high_raw_cluster: 0 games, 0 hits, threshold 0.65. There are no high-raw picks in this block.
• simulation_control: 2 observed games, 0 flip candidates, 0 published flips; status diagnostic_only_without_independent_support. This is not evidence that a winner flip should have occurred. The cross-slate streak, however, makes the repeated lack of useful simulation signal an established diagnostic concern.

Finding streaks — every entry

• pipeline_winner_instability: 0 consecutive slates, not present now; 3 incidences in the 11-slate window; no target lever.
• score_margin_compression: 1 consecutive slate, present now; 4 incidences in the window; target levers score.variance_multiplier, score.variance_floor.
• simulation_inert_on_slate: 11 consecutive slates, present now; 11 incidences; target list includes simulation.allow_score, but param_actionable is false.
• single_slate_calibration_instability: 6 consecutive slates, present now; 9 incidences; target levers confidence.empirical_max_weight, confidence.base_cap, confidence.moderate_cap.
• weak_run_model_signal: 6 consecutive slates, present now; 9 incidences; target list includes training XGBoost parameters, but param_actionable is false.

Escalated findings — established failures, not single-slate noise

1. Simulation inertness, 11 consecutive slates. Target lever listed: simulation.allow_score; target metrics: team-run MAE and total-run MAE; stated direction: confirm the simulation module is running rather than silently no-oping. This has a concrete code/diagnostic action, not a supported parameter adjustment. The self-assessment identifies a likely structural cause: the same draws are used both to search for a target-realizing play-by-play and estimate the win distribution; early exit can leave only about two selected draws. It recommends an independent, unsteered distribution batch that does not early-exit, feeding the resulting win rate to the distribution-agreement policy. This root-cause description is supplied as a self-assessment, not independently demonstrated by the game receipt.
2. Calibration instability, 6 consecutive slates. Target levers: confidence.empirical_max_weight, confidence.base_cap, confidence.moderate_cap; metrics: Brier and calibration error; recommended direction: increase empirical shrinkage. Its persistence warrants a bounded shadow experiment. The current one-game bucket is underconfident, while the self-assessment proposes lower caps; this directional conflict argues for shadow comparison and monitoring rather than automatic application.
3. Weak run-model signal, 6 consecutive slates. Target levers are listed as training.xgb.n_estimators, training.xgb.max_depth, and training.xgb.learning_rate, but param_actionable is false. Target metrics: team-run and total-run MAE. The stated action is to investigate features/target by isolated training backtest, not to force a nightly parameter change. Holdout R² is 0.002415 total, 0.002143 home, 0.030936 away.

Trend directions, stated explicitly

• margin_bias: regressing, mean −1.7778.
• mean_team_run_error_on_losses: improving, mean 2.375.
• weighted_calibration_error: regressing, mean 0.429.
• winner_accuracy: improving, mean 0.7778.

Top-confidence-pick loss streak

• Reported loss_streak: 0.
• Listed outcomes: 20260929 hit; 20260930 hit; 20261001 hit; 20261003 hit; 20261004 hit; 20261005 miss; 20261006 hit; 20261007 miss; 20261008 hit. Two entries have blank dates and unknown; those cannot be counted as hits or misses from this record.
• Current top pick on 20261008 was a hit, but this short sequence includes two recent misses and does not imply robust high-confidence calibration.

Cross-slate bias context

The separate 10-slate bias record does not establish an actionable starter or lineup-run bias:

• Starter ERA error mean −0.561, 6/10 same sign, z −1.67; status hold, not persistent.
• Lineup-run delta mean −0.593, 7/10 same sign, z −1.89; status hold, not persistent.

These are not grounds for changing context.opponent_strength_weight or score.variance_floor on their own.

8. Adjustments for today

Recommendations below are bounded proposals or diagnostics; none is promoted or applied here. Persistent patterns receive priority over the one-game signal.

1. Persistent calibration instability — shadow experiment.
2. Parameter: confidence.empirical_max_weight.
3. Direction/magnitude: increase by 0.02 absolute from its current registered value in a shadow arm only; do not change the base or moderate caps in this same experiment.
4. Expected metrics: test for lower rolling weighted calibration error and Brier score. These are hypotheses to measure, not guaranteed improvements; the current one-game bucket is underconfident, so also check for deterioration on correctly calibrated low-confidence picks.
5. Games helped/hurt: no specific game-level helps/hurts are recorded for this lever in lever_tension; none can be named from this slate. CLE@CHW was a 0.505-probability hit, so blindly reducing its confidence could hurt calibration for this one observation.
6. Why this ranks highly: six consecutive slates and nine window incidences, with calibration-error regression in the trend summary. Keep it shadow-only because present-slate direction and self-assessment direction conflict.

1. Persistent simulation inertness — code/diagnostic action, not a parameter move.
2. Target named in the finding: simulation.allow_score; do not force a change to it, because the finding is explicitly param_actionable: false.
3. Action: operator/code review of the simulation draw loop and _build_simulation_distribution; verify whether early exit and target-realization selection are contaminating the win-rate sample. Compare against an independent unsteered, non-early-exiting probability batch as proposed in the supplied self-assessment.
4. Expected metrics: a non-vacuous simulation contribution, evaluated against team-run and total-run MAE and winner-direction intervention over subsequent slates. No game-level levers are identified in the tension list for this code path.
5. Why this ranks highly: 11 consecutive slates. The next step is verification and measurement, not asserting that a winner flip should have happened.

1. Persistent near-zero run-model signal — isolated feature/target backtest, not parameter tuning.
2. Target list: training.xgb.n_estimators, training.xgb.max_depth, training.xgb.learning_rate; the finding marks this non-actionable by parameter.
3. Action: follow the supplied operator recommendation: investigate the shared feature contract and run an isolated same-fingerprint training/backtest; consider source-labelled no-vig market prices when available, park/weather, bullpen rest/fatigue and platoon-adjusted lineup quality. Bump the model schema version if feature semantics change.
4. Expected metrics: improved holdout run-model R² and out-of-sample team-run/total-run MAE, measured before any deployment. No specific lever_tension games map to training changes.
5. Why this ranks highly: six consecutive slates plus the supplied holdout R² values. Nightly variance tuning cannot repair missing predictive signal.

1. Strongest single-slate driver: compressed margin and under-projected run total — bounded shadow only.
2. Parameter: score.variance_multiplier (a named target of score_margin_compression; do not simultaneously alter score.variance_floor).
3. Direction/magnitude: test a +0.05 absolute change from the current registered multiplier in a shadow arm only.
4. Expected metrics: improve rolling margin tail coverage and margin MAE; monitor team-run and total-run MAE for regression. One game cannot establish the expected direction or size of a real improvement.
5. Games helped/hurt: current lever_tension lists no helped or hurt games for score variance. The only directly relevant game is CLE@CHW, where predicted margin 1 and actual margin 4 favor a wider tail; the causal register explicitly warns not to widen every score from one blowout. No other game is supplied to assess collateral effects.
6. Why lower-ranked: the single-slate compression observation is real, and margin bias is trending regressing, but the single game is too weak for a production change. Use a shadow comparison with a rollback monitor; do not promote on this result.

No production change to pitcher weights or a wildcard recent.* / season.* parameter is recommended: the supplied tension gives no net cross-game evidence, and the latter does not name an exact parameter. The self-assessment’s general “lower caps and widen run variance” recommendation is not taken as a direct production instruction because it conflicts with the current observed calibration direction and the one-game score guardrail.

9. Bottom line

Known: CLE@CHW was a correct-winner, wrong-score prediction. The away win probability was 0.505; the pick hit, but CLE was under-projected by four runs and the total by five. Exact run models have near-zero reported holdout R². The game artifact passed its supplied structural checks, while the starter-feed line for Hagen Smith is missing.

Uncertain or defective: only one supplied game can be fully reviewed despite multiple reported coverage counts and a TB@NYY transition. Raw pick probability is reported as both 0.500 and 0.526027. Calibration’s current single observation is underconfident, despite a persistent calibration-instability finding and a conflicting self-assessment recommendation. The magnitude and causes of the score miss cannot be cleanly separated among run-model signal, offense, starter usage and variance from this game alone.

Safest next action: have the operator verify the simulation’s early-exit/draw-distribution path and measure an independent, unsteered win-probability distribution in shadow. This addresses the longest persistent failure without forcing a parameter move or claiming that the single game proves a particular score or winner adjustment.