Forecasting sporting events encapsulate a compelling intellectual endeavor, underscored by the substantial financial activity of an estimated $80 billion wagered in global sports betting during 2022, a trend that grows yearly. Motivated by the challenges set forth in the Springer Soccer Prediction Challenge, this study presents a method for forecasting soccer match outcomes by forecasting the shot quantity and quality distributions. The methodology integrates established ELO ratings with machine learning models. The empirical findings reveal that, despite the constraints of the challenge, this approach yields positive returns, taking advantage of the established market odds.

翻译：体育赛事预测是一项引人入胜的智力活动，其背后是巨大的金融活动支撑——2022年全球体育博彩投注额估计达800亿美元，且这一趋势逐年增长。受Springer足球预测挑战赛所提出挑战的启发，本研究提出了一种通过预测射门数量与质量分布来预测足球比赛结果的方法。该方法将成熟的ELO评分体系与机器学习模型相结合。实证结果表明，尽管存在挑战赛的约束条件，此方法仍能利用现有市场赔率获得正收益。