利兹的故事：通过预期进球（xG）建模从另一个角度审视2015/16赛季EPL
Leicester's Tale: Another Perspective on the EPL 2015/16 Through Expected Goals (xG) Modelling
AI总结：
通过xG建模分析2015/16赛季英超联赛，发现模型能有效反映球队表现，但对罕见结果的概率预测有限。
摘要：
概率建模是评估球队表现和预测比赛结果的有效工具。然而，一个尚未被充分探讨的重要问题是这些模型是否能够可靠地反映实际表现，同时为与预期相差甚远的罕见结果赋予有意义的概率。在本研究中，我们构建了一个基于预期进球（xG）的推断性概率框架。该框架将射门层面的事件数据转化为赛季层面的积分、排名和结果概率模拟。使用2015/16赛季的英超联赛作为数据，我们证明该框架能够捕捉联赛积分榜的整体结构。它能够正确识别前四名的争夺者和降级候选者，并解释最终积分和排名中相当大的方差。在全赛季评估中，该模型对极端结果的概率较低，特别是利兹的历史冠军胜利，这被视为一个统计异常。然后，我们通过仅使用半赛季信息来探讨xG的先验推断和早期诊断作用。利用前半赛季数据，我们模拟了剩余赛季，并显示那些半赛季xG表现较强的球队在后半赛季获得更多积分，即使考虑了他们当前的联赛位置。在半赛季评估中，利兹队在xG排名中名列前茅，并被赋予了一小但值得注意的赢得联赛的机会。这表明他们的最终成功可能性较低，但并非完全脱离其实际表现。我们的分析表明，预期进球模型在分析和早期预警诊断中表现最佳，而非作为罕见赛季结果的确定预测工具。
英文摘要：
Probabilistic modeling is an effective tool for evaluating team performance and predicting outcomes in sports. However, an important question that hasn't been fully explored is whether these models can reliably reflect actual performance while assigning meaningful probabilities to rare results that differ greatly from expectations. In this study, we create an inference-based probabilistic framework built on expected goals (xG). This framework converts shot-level event data into season-level simulations of points, rankings, and outcome probabilities. Using the English Premier League 2015/16 season as a data, we demonstrate that the framework captures the overall structure of the league table. It correctly identifies the top-four contenders and relegation candidates while explaining a significant portion of the variance in final points and ranks. In a full-season evaluation, the model assigns a low probability to extreme outcomes, particularly Leicester City's historic title win, which stands out as a statistical anomaly. We then look at the ex ante inferential and early-diagnostic role of xG by only using mid-season information. With first-half data, we simulate the rest of the season and show that teams with stronger mid-season xG profiles tend to earn more points in the second half, even after considering their current league position. In this mid-season assessment, Leicester City ranks among the top teams by xG and is given a small but noteworthy chance of winning the league. This suggests that their ultimate success was unlikely but not entirely detached from their actual performance. Our analysis indicates that expected goals models work best as probabilistic baselines for analysis and early-warning diagnostics, rather than as certain predictors of rare season outcomes.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
