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My match winner keeps selecting a match winner and...

Criado em: 1 de outubro de 2026

Respondido usando GPT-5.6 Thinking por Chat01

Pergunta

TennisLocks_v1729.txt

My match winner keeps selecting a match winner and it loses a lot it picks the wrong player it did for this match I keep trying to correct it without hardcoding for this match but every time I fix it makes carts higher

10/1/2026 16:06:43
════════════════════════════════════════
🎾 TENNISLOCKS 🔒
MATCH PROJECTION
PRE-MATCH REPORT
GENERATED 6:06 PM | October 1, 2026
Point, game, and set projection
════════════════════════════════════════

🎯 WTA 1000 Beijing China (OUTDOOR) | Best of 3 | Line: 21.5
Tour: WTA | Court speed (CPI): 38

────────────────────────────────────────
Dayana Yastremska vs Caty McNally
────────────────────────────────────────

💰 MODEL PICKS:

  • TOP [SETS PLAYED 2.5] UNDER | 78.4% | OFFICIAL BET
  • #2 [TOTAL GAMES] UNDER 21.5 | 68.2% | full-match games | OFFICIAL BET
  • #3 [PROP] Caty McNally OVER 0.5 Sets Won | 71.3% | fair odds -248 | OFFICIAL BET

🟡 LOW CONFIDENCE:

  • Match Winner: Caty McNally 61.1% | LOW forecast

Matchup read:
Projected hold: Dayana Yastremska 56.9% | Caty McNally 63.2%
Hold separation: Caty McNally +6.3 percentage points.
Implied return vs this serve: Dayana Yastremska 44.4% | Caty McNally 47.1%
Matchup Dominance Ratio: Dayana Yastremska 0.94 | Caty McNally 1.06
Projected break: Dayana Yastremska 36.8% | Caty McNally 43.1%
Implied return separation: Caty McNally +2.7 percentage points (1 minus opponent tree serve).
Risk: LOW | score 0.15
Pricing data: WEAK | opponent-rank samples 3/3 | trust 1.00

PLAYER FORM
┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄
Dayana Yastremska Caty McNally
Rank 111 72
Elo 1686 1758
Average Opponent Rank 62 63
Schedule Strength HARD HARD
Ace Rate 3.6% 2.7%
Recent Record 3-4 3-4
Projected Hold 56.9% 63.2%
Recent Serve Pts Won 58.5% 56.2%
Recent Return Pts Won 37.9% 39.7%
Same-Surface Serve Pts 58.5% 56.2%
Matchup Serve Projection52.9% 55.6%
Implied Return Projection44.4% 47.1%
Dominance Ratio 0.94 1.06
Hold Volatility 21.6% 15.9%
Projected Break 36.8% 43.1%
First-Serve Pts Won 66.4% 60.6%
Second-Serve Pts Won 47.9% 47.6%
First-Serve In 63.1% 68.8%

MATCH WIN PROJECTION
Dayana Yastremska 38.9%
Caty McNally 61.1%
Tree serve points won: 52.9% / 55.6% | KSR_Q1_ACTIVE_POINT_OWNER_V1688
Projected winner: Caty McNally | Fair odds -157
KSR posterior-predictive owner: 4 cubature trees from the Q1 posterior | player tape count not on this Q1 (stored posterior is pre-full-tape-count; AutoFill rewrites it) | recent form sheet 7 | incremental replay 7 | tour prior 9239

POINT INPUT TELEMETRY [KSR Q1 AUTHORITY]
KSR Pre-Window (2026-08-02): Dayana Yastremska 54.0% +/- 4.1pp | Caty McNally 54.8% +/- 4.1pp
ACTIVE KSR + Current-Window Posterior: Dayana Yastremska 52.9% +/- 4.2pp | Caty McNally 55.6% +/- 4.1pp
Replay audit: player tape count not on this Q1 (stored posterior is pre-full-tape-count; AutoFill rewrites it) | recent form sheet 7 | incremental replay 7 | tour prior 9239 | current-window rows 3 / 6 | sheet rows admitted 0 / 0 | other-player bridge 456 | prior players 550 | prior through 2026-07-27
Same-tour surface window: Dayana Yastremska stored Q1 predates the full-tape count | AutoFill rewrites it | Caty McNally stored Q1 predates the full-tape count | AutoFill rewrites it
Current-window authority: UNKNOWN | -..2026-09-30 | tape rows added 0 | visible overrides 0 | target rows excluded 0 | off-surface rows kept in the serve/return walk 0
KSR hyperparameters: KSR_PREQUENTIAL_ML_RANK_FREE_PREDATED_V1693 | model UNSTAMPED | fit anchor 2026-08-01 | training rows 9239 | converged YES | deadline stop NO
Date note: 7 active replay row(s) use tournament-start date bounds.
Selected-row KSR replay trace:
#1 [B] 2026-08-02 toronto R128 | caty mcnally serve obs/pred 54.4/58.4% innov -0.166 | tatjana maria serve obs/pred 51.9/52.8% innov -0.039 | latent S/R W -0.036/0.113->-0.040/0.116 L 0.037/-0.037->0.035/-0.033
#2 [B] 2026-08-02 toronto R64 | caty mcnally serve obs/pred 60.9/54.1% innov 0.270 | linda noskova serve obs/pred 49.2/60.6% innov -0.462 | latent S/R W -0.040/0.116->-0.038/0.121 L 0.241/-0.027->0.236/-0.029
#3 [B] 2026-08-02 toronto R32 | alexandra eala serve obs/pred 54.3/54.4% innov -0.003 | caty mcnally serve obs/pred 52.2/50.3% innov 0.075 | latent S/R W -0.034/0.104->-0.034/0.103 L -0.038/0.121->-0.037/0.121
#4 [A] 2026-08-13 cincinnati R128 | tatjana maria serve obs/pred 71.1/54.7% innov 0.689 | dayana yastremska serve obs/pred 40.7/59.4% innov -0.746 | latent S/R W 0.035/-0.033->0.039/-0.025 L -0.003/0.033->-0.010/0.028
#5 [B] 2026-08-13 cincinnati R128 | caty mcnally serve obs/pred 60.0/54.7% innov 0.209 | mccartney kessler serve obs/pred 51.9/54.2% innov -0.095 | latent S/R W -0.037/0.121->-0.034/0.122 L 0.009/0.032->0.008/0.030
#6 [B] 2026-08-13 cincinnati R64 | anna kalinskaya serve obs/pred 55.2/56.7% innov -0.064 | caty mcnally serve obs/pred 49.1/53.4% innov -0.173 | latent S/R W 0.118/0.092->0.116/0.094 L -0.034/0.122->-0.037/0.123
#7 [A] 2026-08-24 monterrey R32 | janice tjen serve obs/pred 60.6/61.3% innov -0.033 | dayana yastremska serve obs/pred 57.3/58.9% innov -0.070 | latent S/R W 0.135/-0.045->0.134/-0.043 L -0.010/0.028->-0.012/0.029
Pricing owner: KSR Q1 posterior distribution. Predictive covariance is integrated into one posterior-predictive canonical PMF; Winner, Sets Played, Sets Won, and Total Games are marginals of that same mixed root.

Signals: risk: Winner evidence quality is WEAK

════════════════════════════════════════

📊 DATA QUALITY

  • Sample through:
    Dayana Yastremska: through 2026-09-30 | stored Q1 predates the full-tape count | recent-form sheet is the 7-row grid | AutoFill rewrites the tape count | sheet exact date-bounded rows
    Caty McNally: through 2026-09-30 | stored Q1 predates the full-tape count | recent-form sheet is the 7-row grid | AutoFill rewrites the tape count | sheet exact date-bounded rows
  • Recent exact rows:
    Dayana Yastremska: TML exact x7
    Caty McNally: TML exact x7
    Date precision: tournament-start date x7 / tournament-start date x7
  • Point sample: verified
  • KSR Q1 point owner: 52.9% / 55.6% | player tape count not on this Q1 (stored posterior is pre-full-tape-count; AutoFill rewrites it) | recent form sheet 7 | incremental replay 7 | tour prior 9239
  • Surface SPW (HARD):
    Dayana Yastremska: stored Q1 predates the full-tape surface count | AutoFill rewrites it
    Caty McNally: stored Q1 predates the full-tape surface count | AutoFill rewrites it
    Window: full-tape count not on this Q1 | AutoFill rewrites it
  • Recent records:
    Dayana Yastremska: W-L 3-4, SS 2-2, Sets 8-9
    Caty McNally: W-L 3-4, SS 2-3, Sets 7-9

Fair total: 18.5 | median 19.0
Projected range: P10 15 | median 19 | P90 29
Expected games: 20.5 | median 19.0
Best point forecast: 19 games | most likely exact: 17g (11.3%)
Densest 3-game range: 16-18g 32.2%
Straight-set matches: average 18.1 games | Three-set matches: average 29.0 games | Three-set probability: 22%
SERVE / RETURN MATCHUP
Same-surface serve points won: 58.5% / 56.2%
Legacy current matchup SPW: 58.5% / 56.2%
ACTIVE KSR matchup SPW: 52.9% / 55.6%
Measured same-surface return points won: 37.9% / 39.7%
THREE-SET OUTLOOK
Baseline three-set probability: 37.0%
Adjusted three-set probability: 21.6%
If Dayana Yastremska wins Set 1 / if Caty McNally wins Set 1: 32.3% / 13.7%
Set-2 history increases the likelihood of straight sets.
Set-2 transition evidence: N 13.0 | branch logit shift 0.588 | variance 2.019 | precision 0.495 | rows A/B 6/7 | equal-weight within set-history horizon

========================================

🎯 TOTAL GAMES
Total Games 21.5: UNDER 68.2% | MEDIUM | OFFICIAL BET

Correct my script then send me is a txt file

Resposta

I’ll trace the winner path from the KSR point inputs through the canonical score PMF, then patch the general logic rather than adding anything specific to Yastremska–McNally. I’ll also preserve the one-root rule so the fix doesn’t create a second winner model or inflate other market cards.

Pensamento

Fixed match winner selection and computed unbiased probabilities

Pensamento

Gating uncertain selections

I’m identifying the core issue: a winner is being published despite conflicting posterior components. I’d use directional support as a stability gate, issuing PASS or NO BET when confidence is insufficient rather than forcing a pick.

Gated uncertain selections

Inspected tennis lock decisions and extracted exact KSR definitions

Resposta

I found an important structural problem: the script calculates posterior direction support for the winner, but the winner publisher explicitly ignores it and classifies the pick from the 61.1% marginal alone. That means a fragile winner direction can still be printed even when the uncertainty components do not consistently agree; I’m checking the existing support calculation now so the correction can be isolated to winner publication and leave totals/sets untouched.

Pensamento

Refining winner publication

I’m tracing the regression to confidence ownership: weak 61.1% forecasts still publish a directional winner. I’d align publication with the canonical confidence framework and abstain on LOW-confidence outcomes rather than flip sides or hardcode this matchup.

Refined winner publication

Pensamento

Inspected budget logic, formatting safeguards, and winner confidence validation

Resposta

There are actually two independent failure modes in the file. The bigger one is that the current Q1 validator says schema, model revision, tour, surface, event, round, and date are not gates—it will accept a payload largely because it has two serve rates. That can let stale or context-mismatched KSR authority price a new match; I’m tightening that contract and separately making the winner publisher abstain instead of printing a low-confidence side.

Pensamento

Patched winner logic and validated syntax, decisions, and payloads

Resposta

The patched logic now does what you were aiming for without flipping the player to fit this result: the 61.1%/WEAK case becomes a Match Winner PASS, while a genuinely stable 70% winner can still be an official pick. I also tested stale/missing Q1 revision, wrong date, and wrong tour; those now fail closed instead of silently pricing the match.

Pensamento

Compared TennisLocks file changes

Pensamento

Validated strict event matching and Q1 autofill workflow

Pensamento

Verified TennisLocks file integrity

Worked for 3m 30s

Resposta

Fixed and saved as a new TXT version:

[Download TennisLocks_v1730.txt]

The main problems were structural, not specific to Yastremska–McNally. Your old Q1 validator explicitly allowed model revision, tour, surface, event, round, and date to not be validation gates, meaning an old/context-mismatched KSR payload could still be accepted as long as it contained serve rates. (TennisLocks_v1729.txt) The script also calculated posterior winner-direction support but the winner publisher wasn't actually using that support to decide whether to publish the side. (TennisLocks_v1729.txt) (TennisLocks_v1729.txt)

I changed v1730 so that:

  • Q1 must match the KSR model revision, players, tour family, surface, target date, event, and round.
  • Match Winner now uses the existing KSR posterior-direction uncertainty instead of ignoring it.
  • Winner direction needs at least 90% posterior-direction support to be publishable.
  • LOW winner forecasts are now PASS, not a selected player.
  • WEAK evidence like your McNally 61.1% example becomes Match Winner: PASS rather than picking McNally.
  • The underlying canonical probability is not flipped or artificially shrunk, so this isn't hardcoded to make Yastremska win.
  • Sets Played, Total Games, and props are not reweighted by this winner fix.
  • If Q1 is old/unstamped, the script now fails closed instead of silently using it. Run AutoFill once after installing v1730 so it writes a fresh Q1.

I also syntax-checked the full script and tested the new winner gate: 61.1% + WEAK → PASS; stable 70% → MODEL PICK; unstable 70% → PASS; stale date/model revision/wrong tour → rejected.

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