What is this tool for?
This tool helps set the qualifying time limits for the championships (SM, short-course SM, IKM, Rollo) so that every event and age group draws the right number of swimmers — not too few, not too many. When you change a time limit, you immediately see an estimate of how many starts the meet would get.
How the forecast is built — step by step
The forecast is a funnel: a large pool narrows to the final number of starts, which are then split across events.
- The pool of possible swimmers We start from all active swimmers. Who can qualify depends on the championship: SM has no lower age limit — you can swim the qualifying time at any age (with a slightly easier route for under-18s), so younger swimmers get in too; about 10 % of the SM field is under 16. IKM (13–16) and Rollo (10–13), by contrast, are age-group meets with age-specific limits (see "Age groups" below).
- Who has qualified Who has swum under the time limit. Both 50 m and 25 m times count — you can qualify on either course. At SM about a quarter of the qualified pool gets in on a 25 m time — but many are marginal and don't attend, so only about 1 in 10 actual starters races on a 25 m qualification. (~13 % get in via the under-18 route.)
- Growth until the meet The qualifying window is about two years, so the pool keeps growing before the meet. We project that growth from history, adjusted for how many months are left (5 months out the pool is already fuller than 12 months out). How much it grows differs sharply: SM's pool grows ~1.4× in the final year, but Rollo's ~4.7× (the youngest qualify late). This is the biggest source of uncertainty, and it grows the earlier you plan (see "How accurate is the forecast?").
- Attendance → number of swimmers Not everyone who qualifies attends, and this varies a lot: adults about half (SM ~56 %), juniors far more (Rollo ~89 %). Attendance rises with how many events a swimmer has qualified for, and for SM peaks at 17–18 (see the tables below).
- Events per swimmer → number of starts Each attendee races several events (SM ~3.2, IKM ~4.1) but enters only about half the events they qualified for (SM ~52 %, Rollo ~96 %). Total starts = swimmers × their events.
- Splitting across events Finally the total is spread across individual events and age groups — using the stable historical pattern, not the noisy current per-event count. This split is the hardest part for the junior meets (see "How accurate is the forecast?").
Every number also comes with a 90 % range, not just a single value — see "How accurate is the forecast?".
Age groups
Younger swimmers are forecast in their own age groups. Which age group swims which event is fairly stable from year to year — so we lean on that historical shape rather than on the current partial numbers, which bounce around.
Numbers organisers may find useful
From the three most recent completed editions (SM/IKM/Rollo 2024–2026, LRSM 2023–2025).
SM-uinnit: the six age bands
| Age band | Qualified | Attend | Share of starts |
|---|---|---|---|
| 0–14 | 152 | 48 % | 3 % |
| 15–16 | 643 | 62 % | 18 % |
| 17–18 | 844 | 73 % | 36 % |
| 19–22 | 911 | 56 % | 31 % |
| 23–26 | 291 | 47 % | 8 % |
| 27+ | 361 | 19 % | 5 % |
Attendance peaks at 17–18 (73 %) and is lowest at 27+ (19 % — many qualify but skip the meet). Swimmers aged 17–22 make up about two-thirds of all starts.
IKM: age groups (13–16)
| Age | Qualified | Attend | Share of starts |
|---|---|---|---|
| 13 | 215 | 57 % | 7 % |
| 14 | 528 | 85 % | 33 % |
| 15 | 459 | 87 % | 29 % |
| 16 | 536 | 82 % | 31 % |
IKM is contested in the age groups 13–14, 15 and 16. The 13-year-olds attend far less than the rest (57 %) and are the smallest group — the hardest to forecast.
Rollo: age groups (10–13)
| Age | Qualified | Attend | Share of starts |
|---|---|---|---|
| 10 | 432 | 84 % | 18 % |
| 11 | 459 | 89 % | 25 % |
| 12 | 606 | 91 % | 28 % |
| 13 | 631 | 91 % | 30 % |
Rollo is contested in single years 10–13. The youngest (age 10) attend a little less than the rest (84 %), are the smallest group, and are the hardest to forecast.
The championships compared
| Measure | SM | LRSM | IKM | Rollo |
|---|---|---|---|---|
| Attendance | 56 % | 50 % | 81 % | 89 % |
| Events per swimmer | 3,2 | 3,5 | 4,1 | 3,1 |
| Qualified events actually swum | 52 % | 52 % | 69 % | 96 % |
| Final-year pool growth | 1,4× | 1,4× | 2,3× | 4,7× |
| Starts on the other-course time | 10 % | 6 % | 9 % | 9 % |
Big picture: juniors turn up and swim everything (Rollo 89 % attend and swim 96 % of their qualified events); adults pick and choose (SM ~55 % attend, about half their events). The youngest fields grow the most in the final year. Relatively few starters race on the other-course (25 m) time — about 1 in 10 at SM — even though more of the qualified pool holds a 25 m time (they are marginal and often don't attend).
How many events swimmers actually swim
| Meet | 1 event | 2–4 | 5+ | most |
|---|---|---|---|---|
| SM | 17 % | 62 % | 20 % | 11 |
| LRSM | 13 % | 57 % | 29 % | 12 |
| IKM | 15 % | 42 % | 43 % | 13 |
| Rollo | 28 % | 42 % | 30 % | 9 |
The average (~3–4 events) hides big differences. Rollo splits in two: 28 % swim just one event, but 30 % swim five or more — few swim exactly the "average" three. IKM has a long tail: 43 % swim five or more events (8 % swim eight or more), which pulls the average up. SM and LRSM are more even, clustered around 3–4. This matters for scheduling and session load.
More
- Attendance rises with the number of events qualified for — everywhere, but the floor differs: of those qualified in a single event, 31 % attend at SM vs 79 % at Rollo; qualified in five or more, SM 75 % vs Rollo 97 %.
- Attendance is stable year to year (SM ~56–57 %, IKM ~80–82 %, Rollo ~86–91 %) — which is why the model can rely on it.
- About 13 % (1 in 8) of SM qualifying spots are earned via the under-18 (NSM) route, on top of the adult standard.
- About 7 % of the final SM field are "new" swimmers who were not visible a year earlier — one reason the youngest are hard to forecast.
- Swimmers enter their main event more than their secondary ones (SM: ~64 % vs ~38 %). Specialisation grows with age.
- Improvement decelerates: a two-year improvement is about 1.6× the one-year, not 2×.
- The 90 % range is calibrated: the true result lands inside it about 86–95 % of the time in backtests.
How accurate is the forecast?
The forecast covers three things: how many swimmers attend, how many starts (entries) they make, and how those starts split across events. Accuracy differs by championship, by level, and by how early you plan.
Total-field error by how early you plan
| Before the meet | SM | LRSM | IKM | Rollo |
|---|---|---|---|---|
| ~6 mo | 2 % | 2 % | 6 % | 10 % |
| ~12 mo | 3 % | 4 % | 9 % | 19 % |
| ~18–24 mo | 7 % | 14 % | 16 % | 22 % |
Typical error in the total field by how early you plan — the closer to the meet, the tighter. At ~24 months the window has only just opened and there is barely a pool yet: that's a scenario, not a forecast. The junior meets (Rollo especially) vary the most; recent editions have landed at the better end (Rollo ~5 %) than the long-run typical level.
SM is reliable at every level — the adult field is mostly already qualified at planning time, so both the total and the per-event split land close.
IKM and Rollo are harder, especially per event. Their pool grows a lot in the final year (IKM ~2.3×, Rollo ~4.7×), so at planning time most of the field — and especially which events the youngest will swim — isn't visible yet. The total is still usable, but the per-event split is looser — at ~12 months a single event is typically off by ~15 % at SM and ~25 %+ at IKM, more for the youngest age groups (IKM 13–14, Rollo 10-yo). That's why the model allocates the total by the stable historical pattern rather than trusting the current per-event count.
What the model does NOT include
- Rollo's open 50 m freestyle. It has no qualifying time — anyone in the age group (10–13) can swim it — so it's outside the model. It's a major entry route: over 2024–2026, about 31 % of Rollo entrants came only for the open 50 m free (they swam no other event), so the actual Rollo meet is ~45 % larger than the qualifying-time forecast. All the other Rollo numbers on this page are for the qualifying-time events — i.e. they already exclude the open 50 m.
- Para swimmers. They qualify through a separate route (World Para Swimming points, not the time table), so the model does not forecast them. They are about 5–6 % of starts and show up as "extra" swimmers.
- Relays. Only individual events are included.
- Other-course-only events. An event swum only on the other course (e.g. 100 m IM only short-course) does not appear in the other championship's forecast.
Where the forecast is least certain
- The youngest age groups are hardest. Rollo 10-year-olds and IKM 13–14-year-olds qualify late and improve fast, so their numbers swing a lot year to year.
- Small events have a wide range. A few swimmers either way is a big percentage change.
- That is why every forecast shows a 90 % range, not just one number. The range is calibrated from history: the true result lands inside it about 9 times out of 10.
The championships
SM (long course, summer) · Short-course SM (25 m, December) · IKM (age-group, 13–16) · Rollo (10–13). In all of them you can qualify on either a 50 m or a 25 m time.
Approaches we tried that did not work
These were tested and rejected — no need to ask again.
- Trusting the current per-event pace. A single event's current standing reverts to the mean and doesn't predict the final. The stable historical share is clearly better — so "this event is forecast lower than last year" is not an alarm.
- A starts-based growth factor. Worse than the pool-based factor.
- A per-age-group growth factor. It amplifies the noise in the small young groups.
- Using old (pre-COVID) data. The field has changed (e.g. IKM's age structure changed in 2024), so old data misleads.
- A demographic "cohort" leading indicator. It didn't predict better than simply assuming "same as last year". We kept it only as a background monitor, not in the forecast.
- The schedule / finals-load estimate. Removed for now: SM's combined finals were double-counted, and the IKM regional and 25 m finals need their own rules.
We also tried many ways to make the model more accurate — especially guessing which events a swimmer enters. None beat the simple history-based approach:
- Predicting each swimmer's own improvement. A model that estimates individually who will still drop under the limit. We built and tested it, but it was no more accurate than growing the whole pool with the historical factor.
- A regression (statistical) model for event choice. To replace the simple historical table. It didn't improve the forecast — the plain table was just as good.
- Assuming swimmers only enter their fastest events. Not true in practice — swimmers often skip a strong event or add a weaker one.
- Using "how close to the limit" to guess event choice. It made the per-event estimate worse.
- Grouping swimmers by specialty. Sprinters, distance swimmers, etc. — a real pattern, but it made the numbers less accurate. Kept only for explaining results, not for the forecast.
- Using age to guess event choice. Age doesn't affect which events a swimmer enters (it affects attendance instead), so it didn't help.
- A two-step "how many events × which events" reshaping. It didn't improve accuracy — what matters is the overall level, not how it's split between events.
Questions about the model? Contact the maintainer.