Nightly self-improvement · slate 2026-10-11

Generated 2026-10-12T05:00:00.008409-04:00 ET from official finals (mlb-api). Every learning stage is listed with what it did. "Blocked" means it wanted to act and a safety rule stopped it; "nothing to learn" means it had no eligible evidence.

Slate

2026-10-11

status completed

Winners

1/1

Brier 0.2041

Learned or changed

of 12 stages

Blocked

wanted to act and could not

Release

v15.28.3

consistent

Audit Detailed KPI Learning KPI Failures Luna KPI Review KPI Executive Odds Impact Odds Intelligence Deep Slate Review Luna Post-mortem Daily Learning Adaptive Status

What each learning stage did

Stage	Outcome	Detail
KPI settlement	learned	2 club totals scored stage by stage; layer moved toward the result on 1 of 2.
Hitter matchup calibration	learned	New per-metric scales for SO 0.49, BB 0.31, HR 1.75. Next slate's player effects read them.
KPI model refit	changed	New model 20261011T091221Z_bb8e6dd2.
KPI model rollback	nothing to learn	Kept 20261011T091221Z_bb8e6dd2: 2 settled club totals of its own, needs 30.
Bullpen usage model	changed	Challenger beat the current model on the holdout and was published.
Luna KPI review	blocked	Luna was not asked (skipped no pregame evidence): 3176 rows were local replays and none were verified pregame forecasts.
Luna KPI promotion	nothing to learn	10 candidates in shadow; none has enough prospective evidence yet (see below).
KPI winner-flip gate	nothing to learn	0/0 qualified flips over 0 slates; needs 30 flips over 10 slates with an interval above 0.5
Matchup Luna policy	nothing to learn	Settlement: complete; 0 prospective games over 0 dates; decision pending.
Adaptive parameter proposal (Luna)	nothing to learn	skipped_open_rollback_monitor:
Auto-apply	nothing to learn	no_promotable_candidate
Code agent	nothing to learn	disabled_by_config: code changes are made on the development host, never in the container.

Games

Game	Predicted	Actual	Home win prob	Result	Main driver	Starters
LAD@MIL	2-4	1-2	0.548	hit		Tarik Skubal: 19 proj / 15 real outs; Jacob Misiorowski: 16 proj / 13 real outs

Day over day

Rolling evidence window against the prior night. Associations, not causal proof.

Metric	Prior	Current	Change	Result
brier_score	0.2450	0.2449	-0.0001	improved
accuracy	0.6195	0.6195	0.0000	flat
team_run_mae	2.4292	2.4159	-0.0133	improved
total_run_mae	3.6549	3.6637	0.0088	regressed
calibration_error	0.1325	0.1324	-0.0001	improved
starter_er_mae	1.6435	1.6226	-0.0209	improved
starter_outs_mae	4.2222	4.1840	-0.0382	improved

Calibration produced for the next slate

Metric	Scale used	Measured	Rows	Status
H	1.000	1.245	1575	measured scale confirmed: the interval includes 1.0
SO	0.490	0.102	1575	learned: the interval excludes 1.0
BB	0.315	-0.207	1575	learned: the interval excludes 1.0
HR	1.750	2.623	1575	learned: the interval excludes 1.0

Luna KPI candidates and their promotion gate

Promotion needs 400+ prospective rows over 5+ slates after the proposal, with a gain interval above zero. Only verified pregame forecasts count; local replays never do.

KPI	Status	Target	Proposed	Rows	Slates	Gain interval
luna_pitcher_release_speed_vs_righthanded_starters	shadow	SO	20260923	330/400	5/5	[-0.0007, -0.0000]
luna_pitcher_barrel_rate_vs_rhh_righthanded_starters	shadow	HR	20260923	330/400	5/5	[-0.0010, 0.0101]
luna_batter_contact_rate_vs_breaking_righthanded_starters	shadow	H	20260923	330/400	5/5	[-0.0050, 0.0049]
luna_batter_contact_rate_vs_breaking_left_handed_starters_for_strikeouts	shadow	SO	20260924	51/400	2/5	[–, –]
luna_pitcher_contact_xwoba_allowed_vs_righthanded_starters_for_strikeouts	shadow	SO	20260924	122/400	4/5	[-0.0000, 0.0004]
luna_pitcher_whiff_rate_breaking_vs_left_handed_hitters_for_hits	shadow	H	20260924	122/400	4/5	[-0.0057, -0.0011]
luna_pitcher_home_run_rate_vs_righthanded_starters	shadow	HR	20260925	122/400	4/5	[-0.0021, 0.0105]
luna_batter_ground_ball_rate_vs_fastball_vs_lhp_for_home_runs	shadow	HR	20260926	0/400	0/5	[–, –]
luna_pitcher_whiff_rate_vs_right_handed_starters_for_batter_strikeouts	shadow	SO	20260929	51/400	2/5	[–, –]
luna_batter_whiff_rate_vs_breaking_right_handed_starters_for_hits	shadow	H	20260929	51/400	2/5	[–, –]
luna_batter_walk_rate_vs_righthanded_pitchers_for_home_runs	retired	HR	20260924	0/400	0/5	[–, –]

Operator actions the cycle asked for (48)

Changes to code or a model recipe are never made by the nightly cycle. These are the measured findings that need one.

Priority	Owner	Finding	Action
medium	model	starter length biased by +2.2 outs over 182 starts	recalibrate the starter workload projection toward real outs per start
medium	KPI model recipe	away_x_fastball was beyond ±3 standard deviations of its training range in 7 club totals	the live feature is built differently from the training rows; align the two constructions and retrain
medium	KPI model recipe	away_x_suppress was beyond ±3 standard deviations of its training range in 8 club totals	the live feature is built differently from the training rows; align the two constructions and retrain
medium	KPI model recipe	away_off_power_spread was beyond ±3 standard deviations of its training range in 8 club totals	the live feature is built differently from the training rows; align the two constructions and retrain
medium	KPI model recipe	away_x_ground was beyond ±3 standard deviations of its training range in 6 club totals	the live feature is built differently from the training rows; align the two constructions and retrain
medium	KPI model recipe	away_x_breaking was beyond ±3 standard deviations of its training range in 6 club totals	the live feature is built differently from the training rows; align the two constructions and retrain
medium	KPI recipe	pitcher_home_run_rate_allowed (poor) on HR: adjustments made HR worse over 200 hitter-games in 9 days, mean gain -0.0151, interval (-0.01922, -0.01174)	review this KPI's weight in the matchup multiplier; it is an operator change to the recipe
medium	KPI recipe	batter_strikeout_rate (average) on SO: adjustments made SO worse over 798 hitter-games in 11 days, mean gain -0.0089, interval (-0.01814, -0.00122)	review this KPI's weight in the matchup multiplier; it is an operator change to the recipe
medium	KPI recipe	pitcher_home_run_rate_allowed (weak) on HR: adjustments made HR worse over 248 hitter-games in 7 days, mean gain -0.0058, interval (-0.00747, -0.00414)	review this KPI's weight in the matchup multiplier; it is an operator change to the recipe
medium	KPI recipe	pitcher_strikeout_rate (average) on SO: adjustments made SO worse over 723 hitter-games in 11 days, mean gain -0.0041, interval (-0.00728, -0.00157)	review this KPI's weight in the matchup multiplier; it is an operator change to the recipe
medium	KPI recipe	derived_pitcher_hit_rate_allowed (weak) on H: adjustments made H worse over 313 hitter-games in 7 days, mean gain -0.0033, interval (-0.00856, -0.00018)	review this KPI's weight in the matchup multiplier; it is an operator change to the recipe
medium	KPI model	SF: KPI blend worse than the baseline over 6 games (MAE 1.813 vs 1.667, bias +1.357)	check the wrong-way features listed for this club and its data coverage
medium	KPI model	ARI: KPI blend worse than the baseline over 6 games (MAE 3.1 vs 3.0, bias -1.5)	check the wrong-way features listed for this club and its data coverage
medium	KPI model	COL: KPI blend worse than the baseline over 6 games (MAE 3.673 vs 3.333, bias +0.924)	check the wrong-way features listed for this club and its data coverage
medium	KPI model	BOS: KPI blend worse than the baseline over 7 games (MAE 2.185 vs 1.714, bias +2.185)	check the wrong-way features listed for this club and its data coverage
medium	KPI model	HOU: KPI blend worse than the baseline over 7 games (MAE 3.176 vs 2.143, bias -2.509)	check the wrong-way features listed for this club and its data coverage
medium	KPI model	SEA: KPI blend worse than the baseline over 6 games (MAE 2.39 vs 2.333, bias -0.345)	check the wrong-way features listed for this club and its data coverage
medium	KPI model	MIA: KPI blend worse than the baseline over 6 games (MAE 1.892 vs 1.833, bias +0.606)	check the wrong-way features listed for this club and its data coverage
medium	KPI model	MIL: KPI blend worse than the baseline over 8 games (MAE 1.645 vs 1.375, bias +0.201)	check the wrong-way features listed for this club and its data coverage
medium	KPI model	LAD: KPI blend worse than the baseline over 8 games (MAE 2.562 vs 1.875, bias +2.004)	check the wrong-way features listed for this club and its data coverage
medium	KPI model	STL: KPI blend worse than the baseline over 6 games (MAE 1.884 vs 1.667, bias +0.919)	check the wrong-way features listed for this club and its data coverage
low	KPI model recipe	away_off_discipline pushed the KPI forecast away from the result in 67% of 54 scored club totals, net -6.1 runs	candidate for removal or rework in the next kpi_model version
low	KPI model recipe	home_platoon_barrel pushed the KPI forecast away from the result in 61% of 61 scored club totals, net -3.6 runs	candidate for removal or rework in the next kpi_model version
low	KPI readings	Yuki Matsui (SD): KPI adjustments hurt H (gain -0.12 over 6 games, bias +0.44), BB (gain -0.69 over 6 games, bias +0.63), HR (gain -0.02 over 6 games, bias +0.15)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Trea Turner (PHI): KPI adjustments hurt SO (gain -0.61 over 8 games, bias +0.34)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Kyle Schwarber (PHI): KPI adjustments hurt SO (gain -0.58 over 8 games, bias +0.91), BB (gain -0.17 over 8 games, bias -0.25)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Jonny DeLuca (TB): KPI adjustments hurt SO (gain -0.55 over 6 games, bias +0.06)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Jordan Walker (STL): KPI adjustments hurt SO (gain -0.53 over 6 games, bias +0.18)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Gabriel Moreno (ARI): KPI adjustments hurt H (gain -0.47 over 5 games, bias -0.20)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Christian Walker (HOU): KPI adjustments hurt SO (gain -0.45 over 7 games, bias +0.47)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Ketel Marte (ARI): KPI adjustments hurt H (gain -0.42 over 6 games, bias +0.23)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Tim Tawa (ARI): KPI adjustments hurt H (gain -0.40 over 6 games, bias -0.04)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Colson Montgomery (CHW): KPI adjustments hurt H (gain -0.28 over 6 games, bias +0.64), SO (gain -0.40 over 6 games, bias -0.66)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Jac Caglianone (KC): KPI adjustments hurt H (gain -0.13 over 5 games, bias -0.91), SO (gain -0.39 over 5 games, bias +0.20)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	George Lombard Jr. (NYY): KPI adjustments hurt H (gain -0.15 over 6 games, bias -0.28), SO (gain -0.38 over 6 games, bias -0.12)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Drake Baldwin (ATL): KPI adjustments hurt SO (gain -0.38 over 9 games, bias +0.51), HR (gain -0.01 over 9 games, bias +0.05)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Yandy Díaz (TB): KPI adjustments hurt H (gain -0.21 over 5 games, bias -0.52), SO (gain -0.38 over 5 games, bias +0.88)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Ozzie Albies (ATL): KPI adjustments hurt SO (gain -0.35 over 10 games, bias -0.34), BB (gain -0.19 over 10 games, bias -0.10)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Christian Moore (LAA): KPI adjustments hurt SO (gain -0.34 over 6 games, bias +0.22)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Heriberto Hernández (MIA): KPI adjustments hurt H (gain -0.09 over 6 games, bias +0.09), SO (gain -0.34 over 6 games, bias +0.49)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Bryce Harper (PHI): KPI adjustments hurt SO (gain -0.33 over 8 games, bias +0.05)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Cam Smith (HOU): KPI adjustments hurt H (gain -0.08 over 7 games, bias +0.05), SO (gain -0.32 over 7 games, bias -0.05), HR (gain -0.04 over 7 games, bias +0.05)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Corbin Carroll (ARI): KPI adjustments hurt H (gain -0.32 over 6 games, bias +0.24)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Ty France (SD): KPI adjustments hurt SO (gain -0.31 over 9 games, bias +0.07)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Kody Clemens (MIN): KPI adjustments hurt SO (gain -0.31 over 5 games, bias +0.35)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Danny Jansen (TEX): KPI adjustments hurt SO (gain -0.29 over 6 games, bias +0.40)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Carson Benge (NYM): KPI adjustments hurt H (gain -0.13 over 6 games, bias -0.64), SO (gain -0.28 over 6 games, bias +0.04)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change
low	KPI readings	Taylor Trammell (HOU): KPI adjustments hurt H (gain -0.10 over 5 games, bias +0.71), SO (gain -0.28 over 5 games, bias -0.42), HR (gain -0.03 over 5 games, bias +0.12)	his KPI reading or its opponent pairing misleads; watch whether it persists before any change

Luna post-mortem

Luna (gpt-6-luna) post-mortem, status received. Full analysis.

## 1. Evidence receipt and gaps

**All seven `source_manifest` entries are marked loaded:**

| Source | Status and stated purpose |
|---|---|
| Prediction review, `/app/output/reports/prediction_review_20261011.json` (11,400 bytes) | Loaded; official outcomes and scoring errors |
| Forensic deep audit, `/app/output/reports/PREDICTION_SYSTEM_DEEP_AUDIT_20261011.json` (30,976 bytes) | Loaded; probability, provenance, starter, and decision contracts |
| Continuous learning, `/app/output/learning/continuous_learning_daily_20261011.json` (181,366 bytes) | Loaded; stage quality, calibration, probability lineage, score distribution, starter comparisons |
| Detailed report, `/app/output/reports/detailed_20261011.html` (31,609 bytes) | Loaded; game and simulation rendering |
| Ultra-detailed player audit, `/app/output/reports/20261011_ultra_detailed_player_audit.html` (1,635,801 bytes) | Loaded; player-level prediction trace |
| Structural audit, `/app/output/reports/audit_report_20261011.html` (120,679 bytes) | Loaded; invariant findings |
| Integrity revision audit, `/app/output/reports/audit_report_20261011_integrity_revision.html` (344,105 bytes) | Loaded; structural audit of three post-start game revisions |

**Slate coverage:** The diagnosis reports one expected game and one game reviewed; continuous-learning, forensic-deep-audit, starter-comparison, and structural-audit coverage are each 1/1. The reviewed game is **LAD@MIL**. No additional game is identified as missing by the s