AI 中文总结
该研究以意甲19赛季比赛为样本，发现结构模型对收盘价无增量信息，定义比赛杠杆效应并为ACF佛罗伦萨计算，还修正了自身早期研究的错误。
AI 中文摘要
足球预测研究通常报告准确率在50%左右，并认为其与博彩市场具有竞争力。但针对均匀基准的准确率回答了错误的问题；值得探讨的问题是，模型是否包含无保证金收盘价未吸收的信息。我们将该测试形式化为对数意见池中的拟合权重，并将其应用于意甲19个完整赛季（7220场比赛），结果为负且稳定。调优指数衰减的Dixon-Coles模型达到53.4%的准确率，排名概率得分0.1972，而市场的排名概率得分为0.1905；配对差值为+0.0067（95%置信区间[0.0046, 0.0088]），且在全部7个测试赛季中市场均胜出。结构模型的拟合池权重为0.000，对数损失曲线在验证集和测试集上均随该权重单调递增，因此这是边界解而非优化假象。将相同机制重新应用于射正数据，得到的变体对进球模型的权重为0.35（包含进球模型缺乏的信息），对市场的权重为0.000；两个结构信号互为信息补充，均被定价。结构模型在主胜赔率边际上的校准优于市场（斜率0.995对1.103），但明显更不精准：市场的优势在于区分度而非可靠性，这是仅靠准确率无法区分的。价值不在于更优的预测，而在于基于校准预测构建的内容。我们定义比赛杠杆效应为俱乐部在一场比赛获胜与失利之间，实现赛季目标的概率变化，并为ACF佛罗伦萨计算：对阵保级对手的客场比赛杠杆是对阵最终冠军的主场比赛的2.25倍。本文还记录并修正了我们早期研究中的错误。
英文摘要
Studies of association-football forecasting routinely report three-way accuracy in the low fifties and present it as competitive with the betting market. Accuracy against a uniform benchmark answers the wrong question; the question worth asking is whether a model carries information a margin-free closing price has not already absorbed. We formalise that test as the fitted weight in a logarithmic opinion pool and apply it to nineteen complete Serie A seasons (7,220 matches). The answer is negative and stable. A Dixon-Coles model with tuned exponential decay attains 53.4% accuracy and a Ranked Probability Score of 0.1972 against the market's 0.1905; the paired difference is +0.0067 (95% CI [0.0046, 0.0088]) and the market wins in all seven test seasons. The fitted pooling weight on the structural model is 0.000, and the log-loss profile is monotone increasing in that weight on validation and test alike, so this is a boundary solution, not an optimisation artefact. Refitting the same machinery to shots on target yields a variant earning weight 0.35 against the goals model -- it carries information the goals model lacks -- and 0.000 against the market. Two structural signals, each informative about the other, both priced. The structural model is better calibrated than the market on the home-win margin (slope 0.995 versus 1.103) while clearly less sharp: the market's advantage is discrimination rather than honesty, which accuracy alone cannot distinguish. Value lies not in a better forecast but in what is built on a calibrated one. We define match leverage, the change in a club's probability of achieving a season objective between winning and losing a fixture, and compute it for ACF Fiorentina: an away fixture against a relegation rival carried 2.25x the leverage of hosting the eventual champions. The paper also documents and corrects errors in an earlier study of our own.
Comments16 pages, 5 figures. Code and data pipeline: https://github.com/pitcany/seriea-leverage
