How it works, in two steps
The model knows only one thing: the scores of games already played. No player names, no club reputation, no history.
Measure each team's strength
A strong team wins by a lot. A team's strength therefore shows in its average score margin, computed game after game.
But not every 15-13 is worth the same. So the computation adds an adjustment that depends on the opponents' strength.
Reading a strength: "+3" means three points better than the division average. A +3 in Open cannot be compared with a +3 in Women's: divisions never play each other.
Turn a strength gap into a percentage
The favourite is always the team with the greater strength. If both teams have the same strength, each has a 50% chance of winning. The wider the strength gap, the closer the favourite gets to 100%, without ever reaching it.
Favourite's chance of winning: 79%
Curve set on the tournament shown below.
No cheating: every forecast is dated
Every tournament is replayed round by round. Before each round, the model is recomputed with completed games only, never with the games it has to predict. The accuracy shown is what someone following it live would have seen. Each tournament starts from scratch, with no memory of previous ones.
As long as one of the two teams has not played yet, the model gives no forecast. That covers the whole first round of a tournament.
Is it reliable? The record over 36 tournaments
Two questions. Does the model pick the right winner more often than simple methods? And are its percentages right: when it says 75%, does the favourite really win three times out of four?
Against simpler methods
| Method | Right winner | Error |
|---|---|---|
| Ultracks modelEach team's average score margin, adjusted for the strength of the opponents it faced. | 75.7% | 0.168 |
| Elo ratingThe chess rating: the winner takes points from the loser, more so when the win was unexpected. | 70.4% | 0.199 |
| Point differencePoints scored minus points conceded since the start of the tournament, regardless of the opponent. | 75.1% | 0.175 |
| Win rateShare of games won so far; with equal records, no favourite. | 75.5% | 0.197 |
| Coin flip50% for each team: the zero level, for comparison. | — | 0.250 |
Every method was replayed under the same conditions. The error measures the gap between the percentages given and what happened: 0 would be perfect, 0.25 is a coin flip. This is where the model stands out, and it is what matters to simulate a bracket.
Each dot groups the games of one percentage band; the bigger the dot, the more games. On the dashed line, the percentages are exact.
Ideas tested, and dropped
The model only looks at scores. Other information looked promising. Each idea was tested like the model itself, using only games already played, and had to hold on independent data: the first two on the close games of two World Championships, 2026 then 2022. None improved the forecasts reliably.
How scoring is spread across the roster
DroppedDoes a team whose offence relies on two or three players lose close games more often?
Eight ways of measuring concentration were tried. The effect points one way in 2026 and the other way in 2022: that is noise, not a signal.
Point duration
DroppedIs a team that scores quickly on offence and makes points drag on in defence stronger than its score says?
The most serious lead: the effect shows in 2026 but fades in 2022, on twice as many games. A real effect would get clearer with more data; this one vanishes. It was a false positive.
Memory of previous tournaments
DroppedIf a team keeps most of its players from one year to the next, do last year's games help forecast it?
A slight improvement when at least 70% of the roster is the same, but too small to be sure. The only clear benefit: forecasting the first games of a tournament. Within one European season, however, keeping a club's strength from one stage to the next clearly improves forecasts: that is what the seasons do.
What the model does not know
- It only sees scores: no fatigue, no injuries, no wind, no teams easing off once qualified.
- Early in a tournament each pool is a world of its own: comparing two pools assumes they have the same level, which is never guaranteed.
- An 80% forecast is wrong one time in five, by definition. Upsets are part of the game.
2025 Spring Tour GRENOBLE
Accuracy by division and stage
| Scope | Games | Model |
|---|---|---|
| Whole tournament | 60 | 73.3% |
| Open | 40 | 75.0% |
| Women's | 20 | 70.0% |
| Pools and crossovers | 48 | 79.2% |
| Brackets and placements | 12 | 50.0% |
12 games without a forecast: one of the two teams had not played yet.
Each dot groups the games of one percentage band; the bigger the dot, the more games. On the dashed line, the percentages are exact.
Ranking by strength
Strength measured at the end of the tournament, next to the final standing.
| # | Team | Strength | Final standing |
|---|---|---|---|
| 1 | Iznogood France | +5.9 | 2 |
| 2 | Quijotes Spain | +5.3 | 1 |
| 3 | Jetset Belgium | +4.2 | 5 |
| 4 | SMOG Great Britain | +2.4 | 4 |
| 5 | Freezzz Beezzz Belgium | +2.3 | 6 |
| 6 | Flying Angels Bern Switzerland | +2.2 | 3 |
| 7 | Monkey France | +1.4 | 7 |
| 8 | UFO Netherlands | −0.3 | 8 |
| 9 | Mr Friz France | −0.9 | 10 |
| 10 | Ka-Pow! Great Britain | −1.4 | 9 |
| 11 | Black Birds Belgium | −1.6 | 13 |
| 12 | SOLENT Great Britain | −2.5 | 11 |
| 13 | AUT Beefree Italy | −2.9 | 14 |
| 14 | Moustix France | −4.0 | 15 |
| 15 | Révolution'Air France | −4.5 | 12 |
| 16 | Løsanson Switzerland | −5.3 | 16 |
Every game, with its forecast
For each game, the forecast made before its round and the verdict. Filter by division, stage, day or team. Sort by "Biggest upsets" to find the shocks.
| Date | Stage | Game | Pre-game forecast | Verdict |
|---|---|---|---|---|
| Sun 27 Apr16:05 | OpenPool H | AUT Beefree 70% | Favourite won | |
| Sun 27 Apr16:05 | OpenPool H | Black Birds 54% | Favourite won | |
| Sun 27 Apr16:05 | Women'sBracket 1-8 Finals | Hot Mess Express 59% | Upset | |
| Sun 27 Apr16:05 | Women'sBracket 1-8 Finals | Heidees Synergy 56% | Upset | |
| Sun 27 Apr16:05 | Women'sBracket 1-8 Finals | Mooncup 81% | Upset | |
| Sun 27 Apr16:05 | Women'sBracket 1-8 Finals | GRUT 64% | Upset | |
| Sun 27 Apr14:40 | OpenPool G | Mr Friz 58% | Favourite won | |
| Sun 27 Apr14:40 | OpenPool G | SOLENT 50% | Upset | |
| Sun 27 Apr14:40 | OpenPool F | Jetset 73% | Favourite won | |
| Sun 27 Apr14:40 | OpenPool F | Freezzz Beezzz 70% | Favourite won | |
| Sun 27 Apr14:40 | OpenPool E | SMOG 67% | Upset | |
| Sun 27 Apr14:40 | OpenPool E | Iznogood 66% | Upset | |
| Sun 27 Apr13:15 | OpenPool H | Black Birds 59% | Favourite won | |
| Sun 27 Apr13:15 | OpenPool H | Moustix 75% | Upset | |
| Sun 27 Apr13:15 | Women'sBracket 1-8 Semifinals | Hot Mess Express 63% | Upset | |
| Sun 27 Apr13:15 | Women'sBracket 1-8 Semifinals | FABulous 67% | Upset | |
| Sun 27 Apr13:15 | Women'sBracket 1-8 Semifinals | BFD Shout 82% | Favourite won | |
| Sun 27 Apr13:15 | Women'sBracket 1-8 Semifinals | GRUT 92% | Favourite won | |
| Sun 27 Apr11:50 | OpenPool G | SOLENT 51% | Favourite won | |
| Sun 27 Apr11:50 | OpenPool G | Mr Friz 55% | Upset | |
| Sun 27 Apr11:50 | OpenPool F | Monkey 57% | Upset | |
| Sun 27 Apr11:50 | OpenPool F | Jetset 88% | Favourite won | |
| Sun 27 Apr11:50 | OpenPool E | Iznogood 71% | Favourite won | |
| Sun 27 Apr11:50 | OpenPool E | Quijotes 84% | Favourite won | |
| Sun 27 Apr10:25 | OpenPool H | Black Birds 57% | Favourite won | |
| Sun 27 Apr10:25 | OpenPool H | Moustix 68% | Favourite won | |
| Sun 27 Apr10:25 | Women'sBracket 1-8 | BFD Shout 99% | Favourite won | |
| Sun 27 Apr10:25 | Women'sBracket 1-8 | Tequila Boom Boom 59% | Favourite won | |
| Sun 27 Apr10:25 | Women'sBracket 1-8 | Mooncup 88% | Favourite won | |
| Sun 27 Apr10:25 | Women'sBracket 1-8 | GRUT 100% | Favourite won | |
| Sun 27 Apr09:00 | OpenPool G | Mr Friz 53% | Favourite won | |
| Sun 27 Apr09:00 | OpenPool G | Ka-Pow! 64% | Upset | |
| Sun 27 Apr09:00 | OpenPool F | Jetset 76% | Favourite won | |
| Sun 27 Apr09:00 | OpenPool F | Monkey 74% | Favourite won | |
| Sun 27 Apr09:00 | OpenPool E | Iznogood 76% | Favourite won | |
| Sun 27 Apr09:00 | OpenPool E | SMOG 56% | Upset | |
| Sat 26 Apr17:30 | OpenPool C | Mr Friz 85% | Favourite won | |
| Sat 26 Apr17:30 | OpenPool C | Jetset 90% | Upset | |
| Sat 26 Apr17:30 | Women'sPool B | Hot Mess Express 85% | Favourite won | |
| Sat 26 Apr17:30 | Women'sPool B | BFD Shout 85% | Favourite won |
Times in the tournament's local time. Data: official results published by the organisers (Ultiorganizer, WFDF); forecasts issued before each round, using completed games only.