An affordable data solution for player recruitment for clubs in the South African Premier Soccer League
As football becomes increasingly data-driven, the high cost of advanced player analytics threatens to leave resource-limited clubs at a competitive disadvantage, particularly in player scouting. This growing reliance on expensive, granular data under-scores the need for affordable, innovative data solutions. This dissertation seeks to democratize access to player evaluation data for football clubs in the South African Premier Soccer League. This is achieved by developing a cost-effective system that uses models to approximate Statsbomb's proprietary ‘On the ball' player evaluation metric using cheaper, frequency data from Wyscout and FBref. The analysis shows that linear regression models can effectively estimate key components of this metric using basic frequency statistics. The findings are then packaged into a prototype web-based Decision Support System with budget-aware scouting features, showcasing how club scouts and analysts can integrate sophisticated data-driven recruitment strategies into their clubs without incurring prohibitive data costs.
Clubs, South Africa, Premier soccer league
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