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The framework can simulate games from a given game state, with its primary output being the ensuing probabilities and events from multiple simulations. These can provide insights into match dynamics and underlying mechanisms. We discuss the framework\u2019s design, features, and methodologies, including model optimization, data processing, and evaluation techniques. The models within this framework are developed to predict specific aspects of soccer events, such as event type, success likelihood, and further details. In an applied context, we showcase the estimation of xP+, a metric estimating a player\u2019s contribution to the team\u2019s points earned. This work ultimately enhances the field of sports event prediction and practical applications and emphasizes the potential for this kind of method.<\/jats:p>","DOI":"10.1007\/s10994-024-06606-y","type":"journal-article","created":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T15:10:36Z","timestamp":1726240236000},"page":"8687-8709","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Towards a foundation large events model for soccer"],"prefix":"10.1007","volume":"113","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4802-7558","authenticated-orcid":false,"given":"Tiago","family":"Mendes-Neves","sequence":"first","affiliation":[]},{"given":"Lu\u00eds","family":"Meireles","sequence":"additional","affiliation":[]},{"given":"Jo\u00e3o","family":"Mendes-Moreira","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,9,13]]},"reference":[{"key":"6606_CR1","doi-asserted-by":"publisher","unstructured":"Akiba, T., Sano, S., Yanase, T., et\u00a0al. 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