預測 / 足球 / 世界. 球會友誼賽 / 鄧迪 vs 埃弗頓

預測審核： 鄧迪 vs 埃弗頓 預測、賠率與AI投注建議

鄧迪 鄧迪
Jul 18, 2026 - 13:00
0 1.39
4 1.21
xG Accuracy: 32%
埃弗頓 埃弗頓

AI correctly predicted the 埃弗頓 win.

The match finished 0–4, 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 (4 進球) ✖ 錯誤
  • 雙方進球 雙方進球 (BTTS) 是 否 ✖ 錯誤
  • 1X2 埃弗頓 埃弗頓 ✔ 正確
  • 波膽洞察 1-1, 1-0, 0-1, 2-1, 1-2 0-4 ✖ 錯誤

模型與收盤市場

Strong Disagreement

The closing market prices 埃弗頓 higher than the statistical model.

最大概率差距: 埃弗頓 -17.7 pp

結果 模型 收盤市場 差異 信號
鄧迪 33.9% 23.8% +10.1 pp Model Edge
Draw 27.4% 19.7% +7.7 pp Model Higher
埃弗頓 38.7% 56.4% -17.7 pp Market Higher

The closing market estimates 埃弗頓's win probability at 56.4%, compared with the model's estimate of 38.7%, a difference of 17.7 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: PRE1.

全場比賽結束後，模型的方向性偏向與結果一致（埃弗頓 win 0–4）。

Market Assessment

The market is materially more optimistic about 埃弗頓 than the current fair estimate.

  • Investors may be incorporating information not fully reflected in the baseline model.
  • Tournament-specific context can shift market pricing.

赛后洞察

有效之处

  • Expected goals projected a high-scoring match (ΣxG 2.60) — 4 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 (4 goals)

市场启示

Large model–market gaps do not automatically mean the market is right. Here the closing market priced 埃弗頓 higher (56.4% vs model 38.7%, 17.7 pp), but the model's lean was validated (埃弗頓 win 0–4).

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. Jul 18, 2026 · 20:14 UTC Forecast generated
    • Model 1X2 · 鄧迪 33.9% · Draw 27.4% · 埃弗頓 38.7%
    • xG · 鄧迪 1.39 — 埃弗頓 1.21
  2. Jul 18, 2026 · 12:31 UTC Opening odds snapshot PRE30
    • 1X2 odds · 鄧迪 3.72 · Draw 4.49 · 埃弗頓 1.57
    • Implied 1X2 · 鄧迪 23.8% · Draw 19.7% · 埃弗頓 56.4%
    • Bookmaker · Pinnacle
  3. Jul 18, 2026 · 13:00 UTC Closing snapshot recorded PRE1
    • 1X2 odds · 鄧迪 3.72 · Draw 4.49 · 埃弗頓 1.57
    • Implied 1X2 · 鄧迪 23.8% · Draw 19.7% · 埃弗頓 56.4%
    • Bookmaker · Pinnacle
  4. Jul 18, 2026 · 13:00 UTC Kickoff
  5. FT Full-time result 埃弗頓 win · 0–4
  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: Monitor
歷史決策 Monitor
結果 Validated
賽前指標（歷史背景）
預測可靠性 54/100 · Moderate
  • Validation: Warning
  • Large market gap (18 pp)
證據 ★★★★★
  • No strong statistical edge
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 11/100
Betting Confidence 43/100

验证报告

Immutable Snapshot

预测时间: Jul 24, 2026 · 13:06 UTC 快照 ID: dp-1597472

收盘赔率 1.57
AI 公平赔率 —
CLV 待定
最终赛果 埃弗頓 win · 鄧迪 0–4 埃弗頓
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

Quick read on how the model reads this matchup.

  • League: Club Friendlies
  • Fixture: 鄧迪 vs 埃弗頓
  • Kickoff: 2026-07-18 13:00:00
  • 1X2 (model): Home 33.0% · Draw 33.0% · Away 33.0%
  • xG (showing): 鄧迪 1.39 — 埃弗頓 1.21 (total xG ≈ 2.6)
  • Value headline: None — no positive EV could be estimated on tracked lines at current best prices (missing odds or thin book depth).
  • Structural leans (not bets): See the Over/Under and BTTS cards for any directional lean text.
  • BTTS (model): Yes N/A · No N/A
  • Correct score (top bin): N/A

When book depth is thin or odds are missing, EV may be unavailable even though the model still prefers one side on totals or BTTS — wait for cleaner prices or skip.

Most likely correct score stays a low-probability tail: use it for context, not as a must-bet story.

歷史推薦

歷史決策: Monitor

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 27, 2026 (UTC)

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