Sports Analytics Weekly by kubeia.io - 4/2025

This study analyzes the efficiency and accuracy of NFL player prop betting markets by examining 12,624 unique bets across four major sportsbooks: DraftKings, ESPN BET, BetMGM, and Pinnacle. The research evaluates two probability adjustment methodologies—Power and Multiplicative models—while also assessing relative market sharpness among the sportsbooks.The findings demonstrate that Pinnacle consistently exhibits the sharpest pricing in the dataset. Furthermore, the analysis reveals that sportsbooks incorporate favorite-longshot bias in their vigorish distribution, suggesting that accounting for this bias produces more accurate probability estimates.

Going to school on what the advanced stats mean

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Football analysis is an applied research area that has seen a huge upsurge in recent years. More complex analysis to understand the soccer players’ or teams’ performances during matches is required. The objective of this study was to prove the usefulness of the expected goals on target (xGOT) metric, as a good indicator of a soccer team’s performance in professional Spanish football leagues, both in the women’s and men’s categories. Method: The data for the Spanish teams were collected from the statistical website Football Reference. The 2023/24 season was analyzed for Spanish leagues, both in the women’s and men’s categories (LigaF and LaLiga, respectively). For all teams, the following variables were calculated: goals, possession value (PV), expected goals (xG) and xGOT. All data obtained for each variable were normalized by match (90 min). A descriptive and correlational statistical analysis was carried out. Results: In the men’s league, this study found a high correlation between goals per match and xGOT (R2 = 0.9248) while in the women’s league, there was a high correlation between goals per match (R2 = 0.9820) and xG and between goals per match and xGOT (R2 = 0.9574). Conclusions: In the LaLiga, the xGOT was the best metric that represented the match result while in the LigaF, the xG and the xGOT were the best metrics that represented the match score.

How to find out whether your model relies on spurious correlations

Perhaps you have someone in your life who’s prone to sports gambling. Michael Lewis has someone. So he comes up with a scheme to “innoculate” his 17-year-old son against the lure of placing bets online. All the while, Lewis tries to craft the perfect “master class” for would-be gamblers to understand the dangers of what they might be getting themselves into.