Do weather and crowds change how much a player produces?
2015/16 — 2024/25Seasons
5Leagues
525KPlayer-matches
Finding
Weather barely changes how much players produce: with all five leagues, rain and humidity effects sit within about ±2%, and wind is small (about −1% per +10 km/h). Crowds clearly do: empty stadiums roughly halved home advantage, and it came back with the fans.
02Why it matters
If rain, wind or heat changed what players produce, every raw stat line would carry the weather with it, and a player's numbers would partly depend on the climate he plays in.
Crowds are the same question with people instead of weather: does a full stadium change what happens on the pitch?
Does the environment a match is played in move player numbers?
03What we did
Player-match output
Kickoff weather at the stadium
Fans or closed doors
Same player, team and season
Effect of the environment
Each player is compared with himself — wet days against dry, full stadiums against empty — so differences in ability and team quality never enter the comparison.
Technical detailHow the estimate is built
Weather: on per-minute output with player × season, opponent × season, league × kickoff-hour and league × season × month ; ERA5 weather at the stadium and kickoff hour. A player × team × season version moves no estimate by more than 0.9 percentage points.
Crowds: team-level PPML with team × season and opponent × season fixed effects; 13,888 matches with fans and 1,893 behind closed doors, partial crowds excluded. Crowd status from a dated, sourced calendar per league.
Six hypotheses fixed before looking (rain and long shots, wind and headers/crosses, heat and late-game output). on cluster and p-values; with the closed-doors dates shifted 2–4 years.
04What we found
Crowds
Final
Without fans, home advantage shrank — and came back with them.
The pooled xG home edge went from +30% with fans to +13% behind closed doors, then back to +26% when crowds returned.
Pooled team xG home edge, by period
Home ÷ away, team level, all five leagues.
+30%+13%+26%
With fansClosed doorsFans back
The xG home edge fell from +30% to +13% without crowds and recovered to +26% when they returned.
Study 01 · Final Summary §3 (team level)
Every league lost xG home advantage without fans; Ligue 1 lost its whole goals edge.
The crowd touches every part of the home edge.
Home ÷ away at team level: goals 1.27 → 1.11, 1.29 → 1.13, shots 1.23 → 1.13. Yellow cards went from 0.89 (home side booked less) to 1.02 — the advantage gone.
Home ÷ away, with fans vs behind closed doors
1.00 = no home advantage. Team level.
Goals1.27 → 1.11
xG1.29 → 1.13
Shots1.23 → 1.13
Yellow cards0.89 → 1.02
0.81.01.2
With fansClosed doors
Every attacking ratio moved toward 1.00 without fans, and the home side's lighter treatment in yellow cards disappeared.
Study 01 · Final Summary §3
Weather
Models and placebo check done · conclusion and freeze pending
Weather barely changes how much players produce.
With all five leagues, rain and humidity effects on shots, xG, xA, goals and key passes sit within about ±2%. Wind is small but now detectable: about −1% shots, key passes and xA per +10 km/h. Over ten Premier League seasons alone, 0 of 20 weather × metric effects survived correction.
Weather, next to the crowd
Change in output. The shaded band is the range the five-league rain and humidity estimates sit in.
Rain, humidity±2%
Wind +10 km/h (xA)−1.2%
Home edge, behind closed doors+13%
Home edge, with fans+30%
−5%0%+10%+20%+30%
Rain and humidity move output by about 2% at most and wind by about 1% — a small fraction of what a crowd does to home advantage.
Study 01 · five-league weather run (6 Oct 2026); crowd rows team level
Six predictions, written down before looking.
0of 6pre-registered weather hypotheses survive
Rain and long shots, wind and headers or crosses, heat and late-game output: on five leagues and 445,377 non-penalty shots, none of them held up.
05What surprised us
What the raw data suggested
Forwards' xA rose 29% in the rain in the 2024/25 Premier League — a promising lead.
What happened after we checked
On three other leagues the same effect was −1.4%; on all five, −1.2% (p = 0.43). Not replicated.
Lesson
A striking result from one league and one season is a hypothesis, not a finding. It has to replicate.
06What it means
For rain, wind and humidity, the weather is not something a player's numbers need correcting for. Temperature is the exception: a small association that survives the placebo check, mostly in Serie A — its final conclusion is pending review.
Crowds are different — and a crowd effect is a home effect. That is where Study 2 picks up.
07Limitations
The hand-written weather conclusion and the freeze are still pending; the temperature result is provisional until then.
The closed-doors period is mostly one season, so per-player crowd estimates are noisy; there are no attendance figures — only fans or no fans.
Cup matches and fixture congestion are not in the data.
Observational data: effects are associations within carefully matched comparisons.