Who hands out strikes, who collects them, and whether some players make strikes more likely just by showing up. An analysis of the Stanford pickup-soccer group.
Six findings from reconstructed games — the short version below, or the executive summary and full report with significance tables.
As an admin (emeritus), AbuBakr struck in just 21% of his games vs the 63% baseline — the strongest effect in the data (p < 0.001).
Games Conor plays see ~1.5× the strikes — and it holds even when he's not captaining (70% vs 56%, OR 1.85, p=0.031).
Controlling for captaincy, his effect vanishes: 63% vs 63% (OR 1.01, p=1.0).
Either present → 67%; neither → 56%. But "only Noah" dips below baseline — the signal is entirely Conor.
A handful of repeat offenders absorb most of the punishment. See the leaderboard below.
~98% of games kick off at 7am; evening games are too rare to analyze separately.
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Directed graph of who struck whom. Arrows point from enforcer to victim; node size = total involvement; edge thickness = number of strikes.
Share of a captain's games that produced at least one strike. Dashed line = 63% baseline.
Does merely being rostered move the strike rate? (Among games with a recap.)
Bars colored by distance from the 63% baseline — red = more strikes, blue = fewer.
When Conor plays, and whether some days are safer than others. The line shows how often Conor is on the field; bars show the strike rate (split by whether he played).
Conor is a Friday regular and skips Thursdays. Calmest day overall: Saturday (57%). His absence does the most work on Fri/Sat (~44–45%). Thursdays stay strike-heavy even without him — there's no day that's both Conor-light and low-strike.
The repeat offenders, by total strikes received.