Betting Signal
- 模型显示
- 德国 70.5%
- 市场显示
- 德国 93.6%
- 差异
- 23.1 pp
- 状态
- Use caution — signals are mixed
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OddsGPT Interpretation
The betting market strongly prefers 德国 (93.6%).
德国 — market direction supports the model, but pricing still diverges (-23.1 pp).
模型 vs 市场对比
最大偏差
德国 -23.1 pp
市场对 德国 的乐观程度明显高于模型。
The fair estimate differs substantially from current market pricing. Large divergences can occur when rating inputs are incomplete, team-strength estimates are uncertain, or the market incorporates information not present in the model. Interpret with caution.
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.
由 Elo 调整泊松模拟生成，非博彩赔率。
How are win probabilities calculated?
Home and away expected goals (λ) are derived from Elo ratings and tournament parameters, then fed into a Dixon–Coles Poisson grid to produce 1X2, goal-line, and scoreline probabilities shown on this page.
Is this page betting advice?
No. OddsGPT displays model probabilities for informational purposes only. We do not recommend wagers or stake sizes on this page.
What does xG / λ mean here?
λ is the model’s pre-match expected goals for each team before variance is simulated. It is an input to the Poisson matrix, not a post-match expected-goals stat.
Why are exact score probabilities low?
Even the most likely scoreline typically sits below 15% because many score combinations share the probability mass — that is normal for Poisson models.
比赛阶段: 已完赛
决策生命周期
当前阶段: 等待 CLV
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预测已生成
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市场已对比入场 待定
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验证通过
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收盘已记录收盘 1.05
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CLV 已评估CLV 待定 等待 CLV 计算
