Probabilistic Structure in Football Pool Forecasting: From Outcome Models to Combination Design

Abstract

Football Pool Forecasting poses a recurring problem of coordinating performance with evidence quality, resource limits, and transfer across settings. This technical review examines translating match probabilities into transparent ticket combinations under a fixed budget. Its analysis connects 1 focal paper with 13 independently retrieved publications screened through Crossref or the named publisher. The analysis is organized around probability calibration, outcome dependence, combination coverage, budget constraints, and backtesting. The synthesis resists treating reported gains as context-free quantities, the review compares study questions, technical premises, and validation scope. Across the literature, the evidence indicates that advances in football pool forecasting become credible when behavior, measurement, and decision context are evaluated together and when uncertainty about selection effects is reported explicitly. The comparative structure connects method selection to decision consequence and recurring validity threats, and proposes a research agenda centered on clear comparators, adversarial conditions, and inspectable evidence.