預測 / 足球 / 蘇格蘭. 蘇格蘭挑戰盃 / 羅斯郡 vs 哈茨U21

預測審核: 羅斯郡 vs 哈茨U21 預測、賠率與AI投注建議

Sep 26, 2026 - 14:00
14 1.34
0 1.26
xG Accuracy: 2%

AI correctly predicted the 羅斯郡 win.

The match finished 14–0, validating the model's directional assessment.

追蹤市場與全場比賽結果

預測評級 F

每行比較賽前模型傾向與全場比賽結果。

  • 市場 預測 結果 結果
  • 大小球2.5 小於2.5球 大於2.5球 (14 進球) ✖ 錯誤
  • 雙方進球 雙方進球 (BTTS) 是 否 ✖ 錯誤
  • 1X2 羅斯郡 羅斯郡 ✔ 正確
  • 波膽洞察 1-1, 1-0, 0-1, 2-1, 1-2 14-0 ✖ 錯誤

模型與收盤市場

Strong Disagreement

The closing market prices 羅斯郡 higher than the statistical model.

最大概率差距: 羅斯郡 -43.5 pp

結果 模型 收盤市場 差異 信號
羅斯郡 37.1% 80.5% -43.5 pp Market Higher
Draw 29.6% 12.6% +17.1 pp Model Edge
哈茨U21 33.3% 6.9% +26.4 pp Model Edge

The closing market estimates 羅斯郡's win probability at 80.5%, compared with the model's estimate of 37.1%, a difference of 43.5 percentage points. This highlights a disagreement between the model and market consensus, without indicating which view is ultimately correct.

Model probabilities are generated from the statistical xG model using a Poisson distribution. Closing market probabilities are derived from consensus closing 1X2 odds after margin removal. Values represent implied probabilities rather than betting recommendations. Closing snapshot: PRE5.

全場比賽結束後,模型的方向性偏向與結果一致(羅斯郡 win 14–0)。

赛后洞察

有效之处

  • Expected goals projected a high-scoring match (ΣxG 2.60) — 14 goals materialised

失误之处

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
  • Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (14 goals)

市场启示

Large model–market gaps do not automatically mean the market is right. Here the closing market priced 羅斯郡 higher (80.6% vs model 37.1%, 43.5 pp), but the model's lean was validated (羅斯郡 win 14–0).

Premium betting site stake: New users can use the promo code FHn2uDc1 to receive $100 cash.

預測時間線

此預測如何從預測轉變為全場回顧。

  1. Sep 26, 2026 · 14:11 UTC Forecast generated
    • Model 1X2 · 羅斯郡 37.0% · Draw 29.6% · 哈茨U21 33.4%
    • xG · 羅斯郡 1.34 — 哈茨U21 1.26
  2. Sep 26, 2026 · 13:49 UTC Opening odds snapshot PRE30
    • 1X2 odds · 羅斯郡 1.10 · Draw 7.05 · 哈茨U21 12.84
    • Implied 1X2 · 羅斯郡 80.5% · Draw 12.6% · 哈茨U21 6.9%
    • Bookmaker · Pinnacle
  3. Sep 26, 2026 · 14:11 UTC Closing snapshot recorded PRE5
    • 1X2 odds · 羅斯郡 1.10 · Draw 7.05 · 哈茨U21 12.84
    • Implied 1X2 · 羅斯郡 80.5% · Draw 12.6% · 哈茨U21 6.9%
    • Bookmaker · Pinnacle
  4. Sep 26, 2026 · 14:00 UTC Kickoff
  5. FT Full-time result 羅斯郡 win · 14–0
  6. FT Prediction validated Directional lean matched full-time result
  7. Archived Prediction review

歷史快照

開賽時凍結 — 模型在比賽開始前的輸出。

歷史判決: Cautious / Wait

歷史標籤: Originally displayed as "Wait for validation".

歷史決策 Wait
結果 Validated
賽前指標(歷史背景)
預測可靠性 27/100 · Low
  • Validation: Fail
  • Large market gap (43 pp)
證據 ★★★★★
  • No strong statistical edge
  • Market strongly disagrees on price
  • Validation failed
Pricing proximity (inverse gap) 0/100
Monitoring Confidence 7/100

验证报告

Immutable Snapshot

预测时间: Sep 21, 2026 · 01:57 UTC 快照 ID: dp-10101895

收盘赔率 1.1
AI 公平赔率 —
CLV 待定
最终赛果 羅斯郡 win · 羅斯郡 14–0 哈茨U21
预测结果 ✔ Correct
决策评级 F

模型绩效

本场预测计入:

  • Primary Bets ROI (180d): -100.0%

回顧常見問題

預測的準確性如何?
本頁面評估方向性市場(1X2、大小球 2.5、雙方進球)與全場比賽結果的對應情況。預測評級反映了這些追蹤市場中有多少與實際結果相符。
xG 準確性測量什麼?
xG 準確性比較模型賽前的預期進球數與實際比分 — 而非每個市場是否命中。即使方向性回顧表現強勁,xG 準確性得分也可能中等。
為什麼未能預測精確比分?
即使模型對比賽輪廓的解讀良好,精確比分的結果仍屬於低概率事件。我們會突出顯示主要的比分範圍作為參考;未命中精確賠率線並不會否定方向性回顧。
這是否改善了 AI 的記錄?
每場完成的比賽都會記錄在我們的驗證流程中。彙總的命中率和 CLV 研究會另行發布 — 本頁面為逐場比賽的審核記錄。

預測僅供參考。請負責任地投注並量力而行。過去的表現不保證未來的結果。

AI 比賽簡報

AI 比賽摘要

Model favours 羅斯郡; market prices 羅斯郡 instead — inputs may be missing or stale.

  • Model: 羅斯郡 1.34 xG vs 哈茨U21 1.26 → 羅斯郡 37.1%
  • Market: 羅斯郡 ~80.5% implied
  • Validation failed — do not treat 1X2 EV as actionable.

Do not act on 1X2 value until validation passes. Structural leans (O/U, BTTS) need separate odds review.

Structural lean (model): O/U 2.5 Under 2.5 (Under 2.5 51.8% · Over 2.5 48.2%); BTTS Yes (Yes 54.5% · No 45.5%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes

歷史推薦

歷史決策: Wait

結果: Validated — Pre-match lean validated against the full-time result.

開賽前考慮的風險因素

  • Price movement: implied probabilities and EV move with odds.
  • Sample / data gaps: low-information leagues widen forecast bands.
  • In-play state: goals and red cards are not modelled here.
  • Scoreline variance: the most likely scoreline is still usually a low absolute probability outcome (often well below 20%).

最後更新

September 28, 2026 (UTC)

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