Contextualized Goals in Soccer Frank Silva

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Methodology Applications Future Work 6

Win-Probability Model Score DifferentialInstances Home Wins+1399 Home Loss+175 Home Ties+193 Total th Minute: 7

Win-Probability Model Score DifferentialProbability P H (W) P H (L) P H (T) Total th Minute: 8

Win-Probability Model 9

15 th Minute: Score Differential Probability actual Probability calculated P H (W) P H (L) P H (T) *New Probabilities based on Regressions Valuing Goals 10

. 719 P H (W) = P H (W) * 3 + P H (T) * 1= P H (T) = th Minute, (+1) Score Differential: Expected Value of Points 11

Exp. Value (+2) – Exp. Value (+1) ExPA = – = Expected Points Added (ExPA) th Minute:

PlayerGoals 1. Sergio Aguero26 2. Harry Kane21 3. Diego Costa20 4. Charlie Austin18 5. Alexis Sanchez16 Top EPL Scorers vs. Top ExPA PlayerExPA 1. Harry Kane Alexis Sanchez Sergio Aguero Diego Costa Charlie Austin Goal count does not tell the entire story

1. Account for team quality 2. Account for shot difficulty Future Applications 14 Betting lines and Expected Goal metric can further contextualize goals

Daniel Sturridge 22 goals Yaya Touré 20 goals 15

Daniel Sturridge 22 goals Up by 3 or more: 1 Penalty kicks: 0 16

Yaya Touré Up by 3 or more: 3 Penalty kicks: 5 20 goals 17

Applications 18