Nightly self-improvement · slate 2026-09-11

Generated 2026-09-12T05:00:00.009283-04:00 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
2026-09-11
status completed
Winners
10/15
Brier 0.2407
Learned or changed
0
of 5 stages
Blocked
0
wanted to act and could not
Release
v4.31.0
DRIFT
AuditDetailedDeep Slate ReviewLuna Post-mortemDaily LearningAdaptive Status

What each learning stage did

StageOutcomeDetail
KPI settlementfaileddid not run
Bullpen usage modelnothing to learnNo pregame bullpen forecasts to settle. Refit: not attempted.
Adaptive parameter proposal (Luna)nothing to learncandidate_registered:
Auto-applynothing to learnno_promotable_candidate
Code agentnothing to learndisabled_by_config: code changes are made on the development host, never in the container.

Games

GamePredictedActualHome win probResultMain driverStarters
BAL@TOR4-57-40.505missGenuine toss-up that flippedChris Bassitt: 15 proj / 15 real outs; Max Scherzer: 15 proj / 15 real outs
CHW@STL4-63-70.598hitAnthony Kay: 15 proj / 12 real outs; Matthew Liberatore: 15 proj / 13 real outs
CIN@MIL6-80-200.540hitAndrew Abbott: 14 proj / 6 real outs; Dustin May: 14 proj / 18 real outs
CLE@MIN4-55-20.505missGenuine toss-up that flippedParker Messick: 18 proj / 16 real outs; Taj Bradley: 17 proj / 18 real outs
COL@DET4-52-60.541hitMason Adams: 13 proj / 15 real outs; Framber Valdez: 18 proj / 18 real outs
HOU@TB3-51-30.505hitMiguel Ullola: 9 proj / 3 real outs; Drew Rasmussen: 18 proj / 21 real outs
KC@BOS4-63-20.653missRun environment far lower than projected (over-dispersed)Seth Lugo: 15 proj / 15 real outs; Sonny Gray: 18 proj / 18 real outs
LAA@WAS4-53-40.576hitYusei Kikuchi: 15 proj / 12 real outs; Cade Cavalli: 17 proj / 18 real outs
LAD@MIA6-46-20.420hitBlake Snell: 17 proj / 17 real outs; Ryan Gusto: 13 proj / 18 real outs
NYM@NYY4-64-60.530hitNolan McLean: 18 proj / 15 real outs; Carlos Rodón: 17 proj / 19 real outs
PHI@ATL3-45-60.527hitAaron Nola: 17 proj / 19 real outs; Chris Sale: 19 proj / 21 real outs
PIT@CHC4-52-120.530hitWilber Dotel: 15 proj / 6 real outs; Shota Imanaga: 16 proj / 18 real outs
SD@SF5-47-50.495hitRobbie Ray: 15 proj / 15 real outs; Anthony Molina: 15 proj / 9 real outs
SEA@OAK7-65-60.494missGenuine toss-up that flippedGeorge Kirby: 17 proj / 18 real outs; Jeffrey Springs: 14 proj / 15 real outs
TEX@ARI6-41-90.432missStarting-pitcher projection was wrongMacKenzie Gore: 15 proj / 12 real outs; Merrill Kelly: 16 proj / 13 real outs

Day over day

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

MetricPriorCurrentChangeResult
brier_score0.24450.2421-0.0024improved
accuracy0.57500.60000.0250improved
team_run_mae2.57082.4417-0.1291improved
total_run_mae4.07503.7167-0.3583improved
calibration_error0.05130.08720.0359regressed
starter_er_mae1.97281.8716-0.1012improved
starter_outs_mae3.20623.1284-0.0778improved

Calibration produced for the next slate

MetricScale usedMeasuredRowsStatus
No calibration produced.

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.

KPIStatusTargetProposedRowsSlatesGain intervalProgress
luna_pitcher_release_speed_vs_righthanded_startersshadowSO20260923330/4005/5[-0.0007, 0.0007]
luna_pitcher_barrel_rate_vs_rhh_righthanded_startersshadowHR20260923330/4005/5[-0.0004, 0.0049]
luna_batter_contact_rate_vs_breaking_righthanded_startersshadowH20260923330/4005/5[-0.0045, 0.0044]
luna_batter_contact_rate_vs_breaking_left_handed_starters_for_strikeoutsshadowSO20260924122/4004/5[-0.0027, 0.0021]
luna_pitcher_contact_xwoba_allowed_vs_righthanded_starters_for_strikeoutsshadowSO20260924122/4004/5[-0.0001, 0.0000]
luna_pitcher_whiff_rate_breaking_vs_left_handed_hitters_for_hitsshadowH20260924122/4004/5[-0.0056, -0.0011]
luna_pitcher_home_run_rate_vs_righthanded_startersshadowHR20260925122/4004/5[-0.0010, 0.0056]
luna_batter_ground_ball_rate_vs_fastball_vs_lhp_for_home_runsshadowHR2026092686/4003/5[-0.0001, -0.0000]
luna_pitcher_whiff_rate_vs_right_handed_starters_for_batter_strikeoutsshadowSO2026092951/4002/5[–, –]
luna_batter_whiff_rate_vs_breaking_right_handed_starters_for_hitsshadowH2026092951/4002/5[–, –]
luna_batter_walk_rate_vs_righthanded_pitchers_for_home_runsretiredHR202609240/4000/5[–, –]

Operator actions the cycle asked for (0)

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

PriorityOwnerFindingAction
No operator actions requested.

Luna post-mortem

Luna (gpt-5.6-luna) post-mortem, status received. Full analysis.

## 1. Evidence receipt and gaps

### Sources received

The manifest contains seven expected artifacts:

| Source | Status | Size | Purpose |
|---|---:|---:|---|
| `prediction review` | Loaded | 377,381 bytes | Official outcomes and scoring errors |
| `forensic deep audit` | Loaded | 240,613 bytes | Probability, provenance, starter, and decision contracts |
| `continuous learning` | Loaded | 2,544,895 bytes | Stage quality, calibration, lineage, score distribution, starter comparisons |
| `detailed report` | Loaded | 352,194 bytes | Full game and simulation rendering |
| `ultra detailed player audit` | Loaded | 32,629,527 bytes | Player-level prediction trace |
| `structural audit` | Loaded | 1,840,289 bytes | Invariant findings |
| `integrity revision audit` | **Missing** | — | Post-remediation proof for immutable revision artifacts |

The missing integrity-revision audit is the only explicit source gap. It prevents verification of post-Luna immutable-revision artifacts, but the game-level structural audits report clean saved artifacts.

### Slate coverage

All 15 expected games were reviewed:

`BAL@TOR`, `CHW@STL`, `CIN@MIL`, `CLE@MIN`, `COL@DET`, `HOU@TB`, `KC@BOS`, `LAA@WAS`, `LAD@MIA`, `NYM@NYY`, `PHI@ATL`, `PIT@CHC`, `SD@SF`, `SEA@OAK`, and `TEX@ARI`.

Coverage is complete:

- Canonical artifacts loaded: **15/15**
- Continuous-learning games: **15/15**
- Forensic deep-audit games: **15/15**
- Starter comparisons: **15/15**
- Structural audits: **15/15**
- Overall structu