Individual players have location-specific shooting proficiency that differs from their overall finishing rate. Like Danny Green's NBA shot chart (47% from one corner, 40% from another, 36% elsewhere), football players have zones where their conversion rates are meaningfully above or below their average. Identifying these sweet spots requires high-volume data (training or multi-season aggregation) and enables tactical decisions: which player should take this free kick from this angle, and when in open play should we create shots from this player's best zone.
Minimum data: 30+ shots from the same broad zone to detect a meaningful sweet spot. Divide the pitch into a fine grid (2m × 2m cells or similar); compute conversion rate per cell; smooth with a spatial kernel to avoid noise in sparse cells; compare to the player's overall expected conversion rate. Sweet spots are cells where actual conversion significantly exceeds expected conversion (accounting for shot difficulty). Present as a personalized shot chart — not just where they shoot, but where they over-perform.
Individual player shot maps show persistent spatial patterns — zones where a specific striker converts at 2-3x the average rate for that zone, and other zones where they underperform. These sweet spots reflect biomechanical preference (dominant foot, body shape, preferred shot type) and are remarkably stable across seasons. A striker's conversion rate at their sweet spot is a genuine repeatable skill, not variance.