Read this before quoting any number
This is built from public third-party records (Football Web Pages and Transfermarkt), not from clubs' own audited turnstile data. It is not an official FAW publication. Three limits matter, and they are stated again in full at the end:
- A small number of fixtures have no attendance on record.
- 2020-21 is excluded entirely: played behind closed doors.
- No television effect can be measured. Not one played fixture in the set carries a broadcast flag.
What the model suggests
Adjusted associations with attendance
Lines show 95% intervals clustered by home club. An interval crossing zero means the direction is uncertain; it does not establish no effect. These are individual intervals, not adjusted for testing multiple hypotheses.
Shorter journeys, stronger crowds
How far the away team travelled
Bar height is the attendance index; the figure underneath is the real average crowd.
Eligible fixtures, plotted
One dot per eligible match with travel data. The line averages fixtures in 20-minute journey bands containing at least eight matches.
Friday football: look beyond the raw gap
The raw attendance-index gap changes when the days are weighted to the same mix of journey bands. That descriptive reweighting is not the regression estimate below: it adjusts travel mix only. Neither comparison proves that moving a match will increase its crowd.
Before and after matching the travel mix
Grey is the raw average. Teal re-weights every day to the same mix of away journeys.
Why they differ: share of fixtures with a 3h+ away trip
Friday against Saturday, like for like
Kick-off slots
Attendance index by slot, with the real average crowd
Slots with fewer than eight recorded crowds are flagged as small samples.
Day against journey
Compare the attendance indices within each journey band. These are observed averages with unequal sample sizes—not evidence that Friday and Saturday are equivalent, or that one will work best for every club.
North, Mid and South
North, Mid and South are study categories, not official league divisions. The chart keeps all six fixture combinations visible. Geography, journey length and opponent appeal overlap; these averages cannot separate their contributions.
By fixture geography
Club regions follow the supplied club table. Aberystwyth and Newtown are Mid Wales. No claim is made that every trip inside one region is short.
North against South: crowd comparison
All other fixtures against North–South
Observed attendance indices, not adjusted effects. “All other fixtures” includes games involving Mid Wales.
Friday and Saturday within each comparison group
Observed attendance indices, not adjusted effects. “All other fixtures” includes games involving Mid Wales.
North v South, day by day
Observed attendance indices, not adjusted effects. “All other fixtures” includes games involving Mid Wales.
Derbies
Derby against everything else
“Derby” is a shorthand for an estimated drive under 45 minutes; it does not verify a sporting rivalry.
The strongest repeat fixtures
Minimum four meetings in the dataset.
The shape of a season
Month by month
Holidays and first/last recorded home games
Bank holiday fixtures
First and last recorded home game
“First” and “last” mean the first and last attendance recorded in each completed club-season in this dataset. The incomplete current season is excluded from this comparison. Missing matches mean these need not be the actual season openers or finales.
Does winning fill the ground?
By league position at kick-off
By form over the last five
Weather at kick-off
Weather estimates from Open-Meteo are matched to ground coordinates and London local time. Conditions use the kick-off hour rounded down. Rainfall totals cover three complete hourly periods ending at that hour; they are not minute-exact measurements or supporter forecasts.
Conditions at kick-off
Raw averages.
What survives the controls
Adjusted for home club, season, kick-off slot, journey band, month, bank holidays and form. Faded bars have intervals that include zero.
Weather estimates depend on the window, thresholds and model. The rain-by-distance chart is descriptive; it does not establish a separate interaction effect.
Does rain punish the long trips hardest?
Compare observed crowd indices within each journey band. Unequal fixture mixes prevent a causal conclusion.
Weather estimates depend on the window, thresholds and model. The rain-by-distance chart is descriptive; it does not establish a separate interaction effect.
Clashing with Cardiff, Swansea, Newport and Wrexham
Raw comparison
Descriptive comparison. Fixture dates, geography and opponent mix differ between groups.
Saturdays only
Descriptive comparison. Fixture dates, geography and opponent mix differ between groups.
By selected club or combination
Descriptive comparison. Fixture dates, geography and opponent mix differ between groups.
School holidays
Attendance by school-holiday window
Raw averages against term-time fixtures.
Welsh school holiday dates are approximated to an all-Wales calendar; individual local authorities vary by a few days, and Easter moves each year. The Christmas figure overlaps the Boxing Day and New Year fixtures, so the two should not be added together, they are overlapping comparisons.
Is the league actually growing?
Average crowd by season
2020-21 omitted: behind closed doors. 2026-27 is a part-season.
Raw change against model-adjusted change
Compared with 2024/25, the model’s chosen reference season. This is not a last-season growth rate. Regression intervals are clustered by home club.
Early evidence after the expansion
Change in home average, 2025-26 to 2026-27
The real crowd figures are shown on each bar. Swipe the chart to see all columns.
How the fixture list itself changed
Observed share of fixtures by day. A changing schedule can accompany changes in crowd size; this chart does not assign a causal contribution.
Club by club
Average home crowd by season
Cell colour shows the average crowd. Blank cells have no recorded home average in the study, including seasons outside the division. Hover any cell.
Every club in the dataset
Who brings a crowd
These are total home crowds when each visiting club appears. They do not count the visitors’ travelling support separately. Geography, host selection and rivalry can all affect the ranking.
Largest crowds in this dataset
Ideas to test, questions to keep open
Ideas worth testing
What remains uncertain
Data, gaps and method
What is missing, and how it could mislead
Coverage by season
Method and reproducibility
The downloadable attendance index uses the home club’s full recorded season average. Conditions charts recalculate that average with the Big Bont Bash excluded, so it cannot indirectly distort other Penybont matches. Models use log attendance with home-club fixed effects and the predictors listed in the downloadable model audit. Coefficients are converted as 100 × (exp(beta) − 1). They describe conditional log-scale associations; they are not guaranteed changes in an arithmetic crowd forecast.
Regression confidence intervals use home-club clustered covariance, a finite-sample correction and a t reference with the number of clubs minus one degrees of freedom. Ordinary intervals are retained in the audit for comparison. These are exploratory models with multiple comparisons, relatively few clusters and no causal identification. Alternate specifications may change estimates. Raw-chart intervals are ordinary descriptive mean intervals and do not have the same adjustment.
Road times use OSRM routes between the supplied grounds, not actual supporter origins or historic venue changes. Weather uses Open-Meteo reanalysis estimates; three hourly precipitation totals end at the rounded-down kick-off hour. Holiday dates are approximate; clash flags use regional groups. Ticket prices, separate away attendance, reliable television flags and VAR are not measured.
Match dataset · Clubs · Travel matrix · All results and model audit · Reproduction package