You’re right, and your own header basically names ...

Créé le : 6 avril 2026

Répondu en utilisant GPT-5.4 Thinking par Chat01

Question

TennisLocks_patched-1.js

You’re right, and your own header basically names the bug: the engine is structurally biased toward LEAN 3 SETS on a huge class of matches, not just one.[1]

Here’s the clean way to describe that to your dev, focused on the one root issue:


This isn’t just a Blockx–Dzumhur one‑off. There is a systemic 3‑set inflation bug that falsely produces LEAN 3 SETS on a ton of BO3 matches across tours. The problem is in how threeSetLabel / P3 thresholds and variance regime interact with medium‑favorite, mildly bimodal matches.[1]

Key facts from the engine history (your own comments):

  • v30: “Tour‑relative threeSetLabel replaces P3 vs P2 comparison with tour‑baseline elevation test. Eliminates mathematical lockout where LIKELY3SETS could never fire because P2 ≥ P3 in BO3.”[1]
  • v31: “threeSetLabel HIGH‑variance elevation relaxation… HIGH variance (bimodalScore ≥ 0.50, splitGap ≥ 8) drops elevation gate from 0.04 to 0.025 so more bimodal decider matches get LEAN/BET 3 SETS instead of PASS.”[1]
  • v32: calibrateP3 rewrite still allows P3 to reach 0.42–0.44 on coin‑flip and medium‑fav matches after structural + raw blending and surface adj.[1]
  • v33‑sfb: there’s already a patch note admitting exactly the failure mode: “borderline ATP bimodal matches where P2 is the majority lane produce LEAN 3 SETS + LEAN OVER (2‑set lane dominant and Under).”[1]

Those changes together created a structural pattern:

  1. threeSetLabel is now driven by “P3 elevation above tour base” plus variance regime, not by the P2 vs P3 structural tradeoff.
  2. In HIGH or MID variance (bimodalScore around 0.35–0.50 with decent splitGap), the effective 3‑set elevation gate is often as low as baseP3 + ~0.025–0.035.[1]
  3. Because calibrateP3 + surface + authority can easily push P3 into the 0.40–0.45 band even when P2 is ~0.57–0.63, these matches get tagged as LIKELY3SETS / LEAN 3 SETS by policy, despite the favorite still being structurally in a 2‑set‑lean region.[1]

That’s why you’re seeing “LEAN 3 SETS (MID)” all over the place on:

  • ATP/WTA/CH/ITF
  • P(win fav) roughly 55–65%
  • P3 around 0.40–0.45
  • bimodalScore around 0.35–0.50

The engine systematically interprets “P3 slightly above base + modest bimodal” as “decider‑leaning match,” regardless of the actual 2‑set share.

What I need you (dev) to do:

  1. Locate the 3‑set label logic

    • In buildSetsMarketEngine, find the block where:
      • baseP3, maxP3, calHigh, calMid, calLow, p3LeanThr, minDeciderThr, and variance regime (vrBimodalScore, etc.) are used to:
        • compute p3Working / p3Final,
        • set threeSetLabel or equivalent structural label, and
        • promote to LEAN 3 SETS / BET 3 SETS.[1]
    • I want the exact condition(s) that currently say “this is a 3‑set lean” when:
      • tourKey = ATP (or WTA/CH/ITF),
      • P2 in [0.55, 0.65],
      • P3 in [baseP3 + 0.025, baseP3 + 0.06],
      • bimodalScore in [0.35, 0.55].
  2. Show the bug concretely across matches

    • For a sample of recent matches (Blockx–Dzumhur and 5–10 others), log the following before the decision tree:
      • tourKey, surface
      • P2, P3 (raw, working, final)
      • baseP3, calLow, calMid, calHigh, p3LeanThr, minDeciderThr
      • bimodalScore, splitGap, variance regime label
      • setsArchetype / laneMeta (pTwoSets, pThreeSets).[1]
    • Then show which branch(s) in the decision tree turns those into LEAN 3 SETS.
  3. Prove the systemic bias

    • Count how many matches in a test day satisfy:
      • P2 ≥ 0.56 and P2 ≤ 0.65
      • P3 in [baseP3 + 0.02, baseP3 + 0.06]
      • and yet are labelled LIKELY 3 SETS / LEAN 3 SETS.
    • That number should be “a ton” relative to what we see in reality. This is the bug I’m complaining about.
  4. Propose a structural fix (no new random gate, just correcting the wrong rule):

    I want a simple invariant added into the sets decision tree:

    • In BO3, medium favorite band (tour‑aware):
      • For ATP, when P2 ≥ 0.58 and P2 ≤ 0.67.
      • For WTA/CH/ITF, analogous tour thresholds from the same calibration table.[1]
    • In that band, only allow LEAN 3 SETS if both:
      • P3 is in the top decile of its tour ceiling (e.g. P3 ≥ calHigh or ≥ maxP3 − 0.02).
      • AND laneMeta / SetOutcomeModel shows pThreeSets ≈ pTwoSets (or greater).[1]
    • Otherwise, force the label to LIKELY 2 SETS or MIXED, and cap sets pick at PASS or at most LEAN 2 SETS when 2‑set lane is strongly dominant.

    In code terms: insert a short “medium‑favorite structural override” in buildSetsMarketEngine:

    • After computing P2, P3, laneMeta, and variance regime.
    • Before promoting to LEAN 3 SETS.
    • That override should explicitly check:
      • If P2 is in the medium‑favorite band AND
      • laneMeta.pTwoSets > laneMeta.pThreeSets by X AND
      • P3 is only modestly above base / calLow,
      • then block LEAN/BET 3 SETS for this match (downgrade to LIKELY 2 / MIXED).
  5. Deliverables I want back:

    • A short write‑up:
      • “Here is the exact place where the engine currently promotes 3‑sets for P2 ∈ [0.56, 0.65] and P3 just above base.”
      • “Here are sample logs for 5+ matches showing that pattern.”
    • The proposed code change (diff) implementing the medium‑favorite override.
    • Before/after stats on:
      • How many matches per day get LEAN 3 SETS.
      • Hit rate of those picks before vs after.

This is not about one threshold like coherenceDemote; it’s the interaction between tour‑relative threeSetLabel + variance regime + calibrateP3 that systematically over‑labels medium favorites as decider matches. I want you to isolate that interaction and fix it at the sets decision level.[1]

Somehow the script is produce leans on every match it’s not even betting full picks anymore it’s not supposed to say lean for every match Ik it’s wrong bc this match ended in 2 sets and right at 20 games so the over is wrong here

Also

4/5/2026 20:50:50
⚠️ MARKET ANCHOR APPLIED: Model vs market diverged by 4.3 pts. Pulled 4% toward market.

════════════════════════════════════════
🎾 TENNISLOCKS v1.0 🎾
[ᴠᴇʀѕɪᴏɴ] ᴠ1.0 | 2026-04-06ᴛ03:50:42.879ᴢ
ᴛᴏᴛᴀʟѕ ѕɪᴍѕ: 12,000 | ɢᴇɴᴇʀᴀᴛᴇᴅ: 10:50:46 ᴘᴍ
════════════════════════════════════════

⚠️ MARKET ANCHOR — Model diverged 4.3pt from market. Pulled 4% toward market.

🎯 ATP (RIGHT) Match (Clay (Outdoor)) | Best of 3 | Line: 21.5
ᴄᴘɪ: 29 | ᴛᴏᴜʀ: ᴀᴛᴘ (ʀɪɢʜᴛ) (ʜɪɢʜ)

────────────────────────────────────────
Damir Dzumhur vs Alexander Blockx
────────────────────────────────────────

🎲 Total Games Projection: 23.0 (mixture median) | EV 23.9 | lands ~20g or ~29g
ᴅᴇᴄɪᴅᴇʀ ᴘʀᴏʙ: 42% | ᴀᴅᴊ 43% | ʀᴀᴡ 42%
ᴍᴀᴛᴄʜ ᴄʟᴜѕᴛᴇʀѕ: 2-ѕᴇᴛ ᴍᴇᴅɪᴀɴ 20.0ɢ (ᴍᴇᴀɴ 19.7) | 3-ѕᴇᴛ ᴍᴇᴅɪᴀɴ 29.0ɢ (ᴍᴇᴀɴ 29.7)
ʙɪᴍᴏᴅᴀʟ ꜰᴀɪʀ ʟɪɴᴇ: 23.0ɢ (ᴍɪˣᴛᴜʀᴇ ᴍᴇᴅɪᴀɴ) | 2-ѕᴇᴛ ᴍᴏᴅᴇ: 19.7ɢ | 3-ѕᴇᴛ ᴍᴏᴅᴇ: 29.7ɢ

========================================
📊 MATCH WINNER
────────────────────────────────────────
ᴘʟᴀʏᴇʀ ᴍʟ ᴍᴋᴛ% ᴍᴏᴅᴇʟ% ʀᴀᴡ% ᴇᴅɢᴇ ʙᴀʀ
ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ +121 42.6% 38.0% 38.0% -4.6% ████░░░░░░
▶ ᴘɪᴄᴋ ᴀʟᴇˣᴀɴᴅᴇʀ ʙʟᴏᴄᴋˣ -148 57.4% 62.0% 62.0% +4.6% ██████░░░░
┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄
ʙʟᴇɴᴅ ᴍᴄ 46.9% | ѕᴛᴀᴛѕ 30.8% | ᴇʟᴏ 41.0%
ʀᴀᴡ ᴇɴɢɪɴᴇ ʀᴀᴡ: 38.0% (ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ) | ᴅɪѕᴘʟᴀʏ: 38.0%
ᴀɴᴄʜᴏʀ 4% ᴀᴘᴘʟɪᴇᴅ (ᴍᴀʀᴋᴇᴛ ᴀɴᴄʜᴏʀ 4ᴘᴘ)
ᴇᴅɢᴇ +4.6% ᴏɴ ʙ | ᴇᴠ: +3.8% | ѕᴛᴀᴋᴇ: 1.42% | ᴄᴏɴꜰ: ᴍɪᴅ
ꜰᴀɪʀ ᴍʟ ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ +163 / ᴀʟᴇˣᴀɴᴅᴇʀ ʙʟᴏᴄᴋˣ -163

✅ [OFFICIAL BET]
🏆 BET FAVORITE — Alexander Blockx
ᴇᴠ: +3.8% | ʀɪѕᴋ: ʟᴏᴡ (0.00) | ᴄʟᴜѕᴛᴇʀ: ʜɪɢʜ-ᴅᴇᴄɪᴅᴇʀ

ѕᴛʀᴜᴄᴛᴜʀᴇ & ʀɪѕᴋ
┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄
ᴄʟᴜѕᴛᴇʀ: ʜɪɢʜ-ᴅᴇᴄɪᴅᴇʀ (ᴄʜᴀʟᴋ_ꜰʀᴀɢɪʟᴇ)
ᴅᴇᴄɪᴅᴇʀ: 42.3%
ᴀᴠɢ ɢᴀᴍᴇѕ: 24.2
ʀɪѕᴋ: 0.00 (ʟᴏᴡ) | ᴘᴇɴᴀʟᴛʏ: 0.000
ᴅᴀᴛᴀ: ᴏᴋ (ᴄᴏᴠᴇʀᴀɢᴇ 5/5, ᴛʀᴜѕᴛ 0.94)

ᴘʟᴀʏᴇʀ ɪɴᴛᴇʟ
┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄
ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ ᴀʟᴇˣᴀɴᴅᴇʀ ʙʟᴏᴄᴋˣ
ʀᴀɴᴋ 74 92
ᴇʟᴏ 1654 1705
ᴀᴠɢ ᴏᴘᴘ ʀᴀɴᴋ 129 204
ѕᴄʜᴇᴅᴜʟᴇ ѕᴏʟɪᴅ (ᴛʀᴜѕᴛ 0.99, ʀᴀɴᴋѕ 6)ᴍɪᴅ (ᴛʀᴜѕᴛ 0.94, ʀᴀɴᴋѕ 7)
ѕᴇʀᴠᴇ ѕᴛʏʟᴇ ᴍɪˣᴇᴅ ᴍɪˣᴇᴅ
ᴍᴏᴍᴇɴᴛᴜᴍ ɪɴᴄᴏɴѕɪѕᴛᴇɴᴛ ɪɴᴄᴏɴѕɪѕᴛᴇɴᴛ
ʜᴏʟᴅ % 71.4% 72.9%
ѕᴘᴡ % 60.1% 62.1%
ᴅᴏᴍɪɴᴀɴᴄᴇ ʀᴀᴛɪᴏ 0.71 1.07
ᴠᴏʟᴀᴛɪʟɪᴛʏ 3.5% 1.5%
ᴏᴘᴘ-ᴀᴅᴊ ꜰᴏʀᴍ: ᴅᴇʟᴛᴀ=0.1ᴘᴛ | ᴡᴇɪɢʜᴛ=22.0%
ʙʀᴇᴀᴋ ʀᴀᴛᴇ 27.1% 28.6%
1ѕᴛ ѕʀᴠ ᴡɪɴ % 63.5% 72.5%
2ɴᴅ ѕʀᴠ ᴡɪɴ % 52.6% 44.9%
1ѕᴛ ѕʀᴠ ɪɴ % 68.9% 61.9%
ᴀɴᴀʟʏᴛɪᴄᴀʟ ʜᴏʟᴅ 76.3% 78.7% (ɴᴇᴡᴛᴏɴ-ᴋᴇʟʟᴇʀ)

ѕɪɢɴᴀʟѕ: ᴄʟᴜѕᴛᴇʀ ʜᴇᴀᴠʏ ᴅᴇᴄɪᴅᴇʀ, ꜰᴀᴠ ᴍᴋᴛ-ᴘᴀʀᴛɪᴀʟ ʀɪѕᴋ ᴅɪѕᴄᴏᴜɴᴛ, ᴍᴋᴛ-ᴄᴏɴꜰɪʀᴍᴇᴅ ʀᴇᴄᴏᴠᴇʀʏ: ᴍᴋᴛᴇᴅɢᴇ=4.6ᴘᴘ ʀᴀᴡᴠᴏᴛᴇѕ=-3, ꜰᴀᴠʀᴇѕᴄᴜᴇ: ᴍᴀʀᴋᴇᴛ(57%) + ʀᴀᴡᴍᴏᴅᴇʟ(62%) ᴀɢʀᴇᴇ ᴏɴ ꜰᴀᴠ, ʙʟᴏᴄᴋɪɴɢ ᴅᴏɢ ꜰʟɪᴘѕ (ᴄʟѕ=ᴘʀɪᴍᴀʀʏ)

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

✅ [OFFICIAL BET]
🎲 Sets Market:

  • 2 Sets: 55.8% | Book est -147

  • 3 Sets: 44.2% | Book est +112

Sets Bet: LEAN 3 SETS | Confidence: MID

Over/Under 2.5 Sets:

  • Under 2.5: 55.8% | Book est -151

  • Over 2.5: 44.2% | Book est +110

O/U Bet: LEAN OVER 2.5 | Confidence: MID (Sets + OU aligned)

Read: Decider probability is strong relative to tour ceiling (44.2% vs 52% max). 3-set path is well-supported. (winner policy: volatility/fragility) | Confidence: MID
P3 sources: disp 44.2% | adj 42.3% | raw 44.8% | mkt 42.9% | hold 39.3% | spread 4.9pp | hook stable

📊 Player Stats (Live):

  • ʜɪѕᴛ. ѕᴜʀꜰᴀᴄᴇ (ʀᴇᴅ ᴄʟᴀʏ): ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ (59.0% [52-54]) | ᴀʟᴇˣᴀɴᴅᴇʀ ʙʟᴏᴄᴋˣ (ɴᴏ ᴅᴀᴛᴀ) [ᴛᴀ_ʟɪᴠᴇ_ѕᴘᴡ]
  • ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ: ʜᴏʟᴅ 71.4% (ʀᴀᴡ: 69.7%, ᴀᴅᴊ: ᴛɪᴇʀ ʙᴏᴏѕᴛ) [ᴇꜰʀᴏɴ-ᴍᴏʀʀɪѕ]
  • ᴀʟᴇˣᴀɴᴅᴇʀ ʙʟᴏᴄᴋˣ: ʜᴏʟᴅ 72.9% (ʀᴀᴡ: 71.6%, ᴀᴅᴊ: ᴄᴏɴᴛᴇˣᴛ/ꜰᴀᴛɪɢᴜᴇ) [ᴇꜰʀᴏɴ-ᴍᴏʀʀɪѕ]
  • ѕᴛʏʟᴇ: ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ [ʙᴀѕᴇʟɪɴᴇ/ᴛᴀᴄᴛɪᴄɪᴀɴ] | ᴀʟᴇˣᴀɴᴅᴇʀ ʙʟᴏᴄᴋˣ [ʙᴀѕᴇʟɪɴᴇ/ᴛᴀᴄᴛɪᴄɪᴀɴ]
  • ᴍᴀᴛᴄʜ ᴍᴏᴍᴇɴᴛᴜᴍ (ᴡᴀɴɢ): ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ ᴡᴀɴɢ ѕᴄᴏʀᴇ: 43.2% (ᴍɪˣᴇᴅ ᴍᴏᴍᴇɴᴛᴜᴍ), ᴡ-ʟ 3-3, ѕѕ 1-3, ѕᴇᴛѕ 6-8 ; ᴀʟᴇˣᴀɴᴅᴇʀ ʙʟᴏᴄᴋˣ ᴡᴀɴɢ ѕᴄᴏʀᴇ: 54.2% (ᴍɪˣᴇᴅ ᴍᴏᴍᴇɴᴛᴜᴍ), ᴡ-ʟ 4-3, ѕѕ 2-1, ѕᴇᴛѕ 10-8
  • 1ѕᴛ ѕʀᴠ ᴡɪɴ: ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ 63.5% | ᴀʟᴇˣᴀɴᴅᴇʀ ʙʟᴏᴄᴋˣ 72.5%
  • 2ɴᴅ ѕʀᴠ ᴡɪɴ: ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ 52.6% | ᴀʟᴇˣᴀɴᴅᴇʀ ʙʟᴏᴄᴋˣ 44.9%
  • 1ѕᴛ ѕʀᴠ ɪɴ: ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ 68.9% | ᴀʟᴇˣᴀɴᴅᴇʀ ʙʟᴏᴄᴋˣ 61.9%
  • ѕᴘᴡ: ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ 60.1% | ᴀʟᴇˣᴀɴᴅᴇʀ ʙʟᴏᴄᴋˣ 62.1% [ʙᴀʀɴᴇᴛᴛ-ᴄʟᴀʀᴋᴇ ᴀᴅᴊ.]
  • ʙʀᴇᴀᴋ ʀᴀᴛᴇ: ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ 27.1% | ᴀʟᴇˣᴀɴᴅᴇʀ ʙʟᴏᴄᴋˣ 28.6%
  • ᴅᴏᴍɪɴᴀɴᴄᴇ ʀᴀᴛɪᴏ: ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ 0.71 | ᴀʟᴇˣᴀɴᴅᴇʀ ʙʟᴏᴄᴋˣ 1.07 [ᴍɪѕᴍᴀᴛᴄʜ]
  • ᴠᴏʟᴀᴛɪʟɪᴛʏ: ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ 3.5% | ᴀʟᴇˣᴀɴᴅᴇʀ ʙʟᴏᴄᴋˣ 1.5% | ᴍᴀᴛᴄʜ: 2.5%
  • ᴇʟᴏ: ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ ᴜɴᴅᴇʀᴅᴏɢ (41.0%) [ᴋᴍ-ᴇʟᴏ ʙʀɪᴅɢᴇ]
    ѕᴏᴜʀᴄᴇ: ᴇʟᴏ_ʟᴏᴏᴋᴜᴘ ѕʜᴇᴇᴛ (ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ=1654, ᴀʟᴇˣᴀɴᴅᴇʀ ʙʟᴏᴄᴋˣ=1705)
  • ʙʟᴇɴᴅ (ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ): ᴍᴄ 46.9% | ѕᴛᴀᴛѕ 30.8% | ᴇʟᴏ 41.0%
  • ᴀɴᴀʟʏᴛɪᴄᴀʟ ʜᴏʟᴅ: ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ 76.3% | ᴀʟᴇˣᴀɴᴅᴇʀ ʙʟᴏᴄᴋˣ 78.7% (ɴᴇᴡᴛᴏɴ-ᴋᴇʟʟᴇʀ)

ᴛᴏᴛᴀʟѕ ꜰᴀɪʀ ʟɪɴᴇ: 23.5 (ᴄᴅꜰ 50/50) | ᴍɪˣᴛᴜʀᴇ ᴍᴇᴅɪᴀɴ: 22.9
ᴛᴏᴛᴀʟѕ ʀᴀɴɢᴇ: ᴘ10=17 | ᴘ50=23 | ᴘ90=32
ᴛᴏᴛᴀʟѕ ᴇˣᴘᴇᴄᴛᴇᴅ: 24.0 (ᴍᴇᴀɴ) | ᴍᴇᴅɪᴀɴ: 22.9
ᴍᴏѕᴛ ᴄᴏᴍᴍᴏɴ ᴇˣᴀᴄᴛ: 19ɢ | ʜɪɢʜᴇѕᴛ-ᴅᴇɴѕɪᴛʏ ᴢᴏɴᴇ: 18-20ɢ 22.0%
ᴍɪˣᴛᴜʀᴇ ᴍᴇᴅɪᴀɴ: 23.0ɢ | ᴄᴏɴᴅɪᴛɪᴏɴᴀʟ: ᴇ[ᴛ|2 ѕᴇᴛѕ] 19.7 | ᴇ[ᴛ|3 ѕᴇᴛѕ] 29.7 | ᴘ(3 ѕᴇᴛѕ) 43%
ᴛᴏᴛᴀʟѕ ᴘᴍꜰ (ᴛᴏᴘ ᴇˣᴀᴄᴛѕ): 19ɢ 7.9% | 22ɢ 7.2% | 18ɢ 7.1% | 20ɢ 7.0% | 17ɢ 6.0% | 21ɢ 5.8% | 29ɢ 5.6% | 23ɢ 5.5%
🎯 TOTAL GAMES:

ᴛᴏᴛᴀʟѕ ʀᴇɢɪᴍᴇ ѕᴛᴀʙʟᴇ (ᴍᴄ ᴄʜᴀɪɴѕ 3, ᴀᴠɢ ѕᴘʀᴇᴀᴅ 0.05 ɢ)
✅ [OFFICIAL BET]
ᴏᴠᴇʀ 21.5 | ᴄᴏɴꜰɪᴅᴇɴᴄᴇ: ᴍɪᴅ | ⚠️ ʙɪᴍᴏᴅᴀʟ ᴍᴀᴛᴄʜ
── ꜰʀᴀɢɪʟɪᴛʏ ꜰʟᴀɢѕ ──
⚠️ ᴍᴏᴅᴇʀᴀᴛᴇʟʏ ʙɪᴍᴏᴅᴀʟ (ѕᴄᴏʀᴇ=0.40) — ᴇʟᴇᴠᴀᴛᴇᴅ ᴠᴀʀɪᴀɴᴄᴇ
⚠️ ʜᴇᴀᴠʏ ʀɪɢʜᴛ ᴛᴀɪʟ (ᴘ≥31=17.5%) — ʙʟᴏᴡᴏᴜᴛ ʀɪѕᴋ

ᴡʜʏ ɪᴛ ꜰɪᴛѕ:
"3-ѕᴇᴛ ᴘᴀᴛʜ (43%) ʟᴀɴᴅѕ ᴀᴛ ~29ɢ — ᴍᴀѕѕɪᴠᴇʟʏ ᴏᴠᴇʀ ᴛʜᴇ 21.5 ʟɪɴᴇ (99.8% ᴏᴠᴇʀ ɪɴ ᴛʜᴀᴛ ʟᴀɴᴇ).
2-ѕᴇᴛ ᴘᴀᴛʜ (57%) ʟᴀɴᴅѕ ᴀᴛ ~20ɢ — ᴜɴᴅᴇʀ ᴛʜᴇ ʟɪɴᴇ (72.1% ᴜɴᴅᴇʀ).
ѕᴇᴛѕ ᴇɴɢɪɴᴇ ᴄᴏɴꜰɪʀᴍѕ: ʟᴇᴀɴ 3 ѕᴇᴛѕ (ᴍɪᴅ ᴄᴏɴꜰɪᴅᴇɴᴄᴇ).
ᴛʜᴇ ᴏᴠᴇʀ ʙᴇᴛ ᴡɪɴѕ ᴡʜᴇɴ ᴛʜᴇ ᴍᴀᴛᴄʜ ɢᴏᴇѕ 3 ѕᴇᴛѕ. ᴛʜᴇ ᴜɴᴅᴇʀ ʙᴇᴛ ᴡɪɴѕ ɪɴ ѕᴛʀᴀɪɢʜᴛ ѕᴇᴛѕ."

ѕʜᴀᴘᴇ:
"2-ѕᴇᴛ ʟᴀɴᴇ (57%): ᴄᴇɴᴛᴇʀ 20ɢ | ᴘ(ᴏᴠᴇʀ) 27.9%
±1σ ʀᴀɴɢᴇ: 17-23ɢ | ᴘ(ᴏᴠᴇʀ 21.5) ɪɴ ʟᴀɴᴇ: 30.2%
3-ѕᴇᴛ ʟᴀɴᴇ (43%): ᴄᴇɴᴛᴇʀ 29ɢ | ᴘ(ᴏᴠᴇʀ) 99.8%
ᴘ(ᴅᴇᴄɪᴅᴇʀ) 43% (ᴍɪᴅ, 83% ᴏꜰ ᴍᴀˣ)
ʙɪᴍᴏᴅᴀʟ 3-ѕᴇᴛ"

ᴘʀɪᴄɪɴɢ:
"ʟᴀɴᴇ ᴘʀɪᴄɪɴɢ:
2-ѕᴇᴛ ʟᴀɴᴇ: ꜰᴀɪʀ ~19.9 ᴠѕ ʟɪɴᴇ 21.5 -> 1.6ɢ ᴜɴᴅᴇʀ ᴛʜᴇ ʟɪɴᴇ
3-ѕᴇᴛ ʟᴀɴᴇ: ꜰᴀɪʀ ~29.3 ᴠѕ ʟɪɴᴇ 21.5 -> 7.8ɢ ᴏᴠᴇʀ ᴛʜᴇ ʟɪɴᴇ
ʙʟᴇɴᴅᴇᴅ ꜰᴀɪʀ: 23.5 (ᴡᴇɪɢʜᴛᴇᴅ ʙʏ ᴘ3, ʙᴜᴛ ᴍɪѕʟᴇᴀᴅɪɴɢ ꜰᴏʀ ʙɪᴍᴏᴅᴀʟ)

ᴋᴇʏ ǫᴜᴇѕᴛɪᴏɴ: ᴅᴏᴇѕ ᴛʜɪѕ ᴍᴀᴛᴄʜ ɢᴏ 3 ѕᴇᴛѕ?
ᴍᴏᴅᴇʟ ѕᴀʏѕ: 43% ᴅᴇᴄɪᴅᴇʀ ᴘʀᴏʙᴀʙɪʟɪᴛʏ
ѕᴇᴛѕ ᴇɴɢɪɴᴇ ѕᴀʏѕ: ʟᴇᴀɴ 3 ѕᴇᴛѕ (ᴍɪᴅ ᴄᴏɴꜰɪᴅᴇɴᴄᴇ)
ɪꜰ ʏᴇѕ -> ᴇˣᴘᴇᴄᴛ ~29 ᴛᴏᴛᴀʟ ɢᴀᴍᴇѕ (ᴏᴠᴇʀ 21.5 ʙʏ ~7.8 ɢᴀᴍᴇѕ)
ɪꜰ ɴᴏ -> ᴇˣᴘᴇᴄᴛ ~20 ᴛᴏᴛᴀʟ ɢᴀᴍᴇѕ (ᴜɴᴅᴇʀ 21.5 ʙʏ ~1.6 ɢᴀᴍᴇѕ)"

ᴇɴɢɪɴᴇ ʙʀᴇᴀᴋᴅᴏᴡɴ (ʙɪᴍᴏᴅᴀʟ):
┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄
ʟᴀɴᴇ ᴡᴇɪɢʜᴛ ᴄᴇɴᴛᴇʀ ᴘ(ᴏᴠᴇʀ 21.5) ꜰᴀɪʀ
2-ѕᴇᴛ 57% 20ɢ 27.9% ~19.9
±1σ ʀᴀɴɢᴇ: 17-23ɢ | ᴘ(ᴏᴠᴇʀ 21.5) ɪɴ ʟᴀɴᴇ: 30.2%
3-ѕᴇᴛ 43% 29ɢ 99.8% ~29.3
ʙʟᴇɴᴅᴇᴅ (ʀᴇꜰ): ᴍᴄ 57.8% ᴏᴠᴇʀ │ ᴍᴀʀᴋᴏᴠ 71.4% ᴏᴠᴇʀ
ѕᴇᴛѕ ᴄᴏʜᴇʀᴇɴᴄᴇ: ꜰɪʀᴇᴅ ✓ │ ʟᴇᴀɴ 3 ѕᴇᴛѕ → ᴏᴠᴇʀ ᴀʟɪɢɴᴍᴇɴᴛ ᴄᴏɴꜰɪʀᴍᴇᴅ
ꜰᴀɪʀ ʟɪɴᴇѕ — ᴍᴄ: 23.5 │ ᴍᴀʀᴋᴏᴠ: 24.5 │ ɢᴀᴘ: 11.3ᴘᴛѕ, 1.00ɢ
ᴘ(ᴅᴇᴄɪᴅᴇʀ) ᴀᴜᴛʜ: ᴜѕᴇᴅ 43.3% ѕᴜᴘᴘᴏʀᴛ 5 ѕᴘʀᴇᴀᴅ 3.8ᴘᴘ ʟᴀɴᴇɢᴀᴘ ɴᴀᴘᴘ ѕᴛᴀʙʟᴇ ʙʀᴏᴀᴅѕᴜᴘᴘᴏʀᴛ
ʜᴀʟꜰ-ʟɪɴᴇ 21.5 - ᴍᴄ: ᴜɴᴅᴇʀ 39.9% | ᴏᴠᴇʀ 60.1%
ʜᴀʟꜰ-ʟɪɴᴇ 21.5 - ᴍᴀʀᴋᴏᴠ: ᴜɴᴅᴇʀ 28.6% | ᴏᴠᴇʀ 71.4%
ᴛᴀɪʟ - ᴘ(>=30): 22.2% | ᴘ(>=31): 17.5% | ᴘ(>=35): 4.0%
ʙᴜᴄᴋᴇᴛѕ: ʟᴇꜰᴛᴛᴀɪʟ(ʟ-6) 1.6% | ʟᴏᴄᴀʟᴍᴀѕѕ ʟᴏᴡ 14.9% ʜɪɢʜ 7.4%
ɴᴇᴀʀ-ʟɪɴᴇ ᴍᴀѕѕ @21.5: 12.9% (ᴘ(21)+ᴘ(22)) | ʟᴏᴄᴀʟ 20-22: 20.0% | 19-23: 33.4%
ᴀᴅᴊᴀᴄᴇɴᴛ ᴇˣᴀᴄᴛѕ: ᴘ(21ɢ) 5.8% | ᴘ(22ɢ) 7.2%
ᴍᴀʀᴋᴏᴠ 3-ѕᴇᴛ ᴀᴅᴊ: 43.7% (ᴘᴇɴᴀʟᴛʏ 0.0%)

ѕɪᴍᴜʟᴀᴛɪᴏɴ (12000 ʀᴜɴѕ): ʙɪᴍᴏᴅᴀʟ — 57% ʟᴀɴᴅ ɴᴇᴀʀ ~20ɢ (2-ѕᴇᴛ), 43% ʟᴀɴᴅ ɴᴇᴀʀ ~29ɢ (3-ѕᴇᴛ)
58% ᴏᴠᴇʀ 21.5 │ ʙʟᴇɴᴅᴇᴅ ᴍᴇᴅɪᴀɴ 22.9ɢ (ᴘʜᴀɴᴛᴏᴍ — ʙᴇᴛᴡᴇᴇɴ ᴄʟᴜѕᴛᴇʀѕ ᴡʜᴇʀᴇ ꜰᴇᴡ ᴍᴀᴛᴄʜᴇѕ ᴀᴄᴛᴜᴀʟʟʏ ʟᴀɴᴅ)
⚠️ ѕᴘʟɪᴛ ѕɪɢɴᴀʟ — 2-ѕᴇᴛ ʟᴀɴᴇ ᴏᴘᴘᴏѕᴇѕ, 3-ѕᴇᴛ ʟᴀɴᴇ ᴀɢʀᴇᴇѕ
ᴀᴜᴅɪᴛ: ᴅɪʀᴍᴄ=ᴏᴠᴇʀ | ᴘѕɪᴅᴇᴍᴄ=57.5% | ᴄʟᴜѕᴛᴇʀᴅɪʀ=ᴜɴᴅᴇʀ | ᴄʜᴏѕᴇɴᴅɪʀ=ᴏᴠᴇʀ | ɪɴᴠᴀʀɪᴀɴᴛ=ᴏᴋ

📊 ᴜɴᴅᴇʀᴅᴏɢ ᴀѕѕᴇѕѕᴍᴇɴᴛ:
ɴᴏ ᴇᴅɢᴇ ᴏɴ ᴅᴀᴍɪʀ ᴅᴢᴜᴍʜᴜʀ (38.0% ᴍᴏᴅᴇʟ | ɪᴍᴘʟɪᴇᴅ 43%).

Pls fix my script it’s keeps being innacurate across different matches and your levels it’s very annoying update my script and replace and fix the corrupted parts then send the script as a downloadable txt link

I don’t need overrides if the script had clean logic I shouldn’t need overrides man that’s the issue pls fix issues man I’m missing 2 set matches and actual 3 set matches

Réflexion

Cleaning up diagnostic flag and overriding logic

I need to remove the block completely, or if it remains due to legacy code, ensure it's treated as an override. The user asked for no overrides, so I’ll make it a no-op or diagnostic flag only. I should update confidence adjustments in Stage 5 related to _shortFavorBimodal, and consider bumping the engine version.

Thought for 5m 5s

Réflexion

Clarifying summary and citation issues

I’m thinking I should create a concise summary of changes, honestly mentioning the inability to backtest stats due to the lack of a batch dataset. I’ll need to cite the file and any structural changes, but line numbers are tricky because the output from file_search doesn’t include them. I can use a general citation like (website) instead.

Citing uploaded file and providing downloadable links

Since I'm referencing an uploaded file, I can use generic citations like (website) rather than inventing line numbers. The developer suggested citing with (website). I should clarify this as "based on your uploaded script" to be clear. I'll also include downloadable links for both .txt and .js files, with a focus on highlighting the .txt version.

Thought for 8m 23s

Réponse

I fixed the script and exported it as a downloadable text file.

Downloads: Patched script (.txt)
Patched script (.js)

What I changed in the engine:

  • I patched _buildSetsMarketEngine_ so medium-favorite BO3 matches no longer get promoted to LEAN 3 SETS just because P3 is modestly above tour base while the 2-set lane is still the majority path. The new gate blocks 3-set promotion in that band unless P3 is truly near the tour ceiling and the lane model is close to parity. That addresses the exact structural pattern your uploaded script was drifting into. (TennisLocks_patched-1.js)
  • I stopped the HIGH-variance structural override from re-promoting those blocked medium-favorite matches back into LIKELY_3_SETS. That was one of the ways the bad label could leak back into the tree. (TennisLocks_patched-1.js)
  • I removed the post-tree forced short-favored sets override as a decision hack. The short-favored bimodal flag now stays as a diagnostic/totals helper instead of hard-routing the sets engine after the tree. That keeps the logic cleaner and stops the script from manufacturing lean calls just to reconcile itself. (TennisLocks_patched-1.js)

Net effect:

  • fewer fake LEAN 3 SETS
  • fewer fake LEAN OVER calls caused by a minority 3-set lane
  • more PASS on medium-favorite ambiguous matches instead of spraying leans everywhere

I also bumped the version stamp to v1.1-clean and syntax-checked the patched file successfully.

One thing I did not fabricate: before/after daily hit-rate stats. The uploaded file did not include a backtest slate, results log, or harness to compute those honestly.

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