Worked example
How much does this lineup change matter?
A lineup decision has two versions: the projected team and the team after a change. This example compares them over the same 100 simulated games, then shows the inputs and limits behind the difference.
Spurs v Crystal Palace
Kickoff
Scenario engine (approximate): not calibrated on held-out matches
1The decision being tested
Out: Jan Paul van Hecke (DEF, 38.0 FPL season points) · In: Ben Davies (DEF, 8.0 FPL season points)
Out: Sandro Tonali (MID, 30.0 FPL season points) · In: Mohammed Kudus (MID, 19.0 FPL season points)
Out: Andrew Robertson (DEF, 28.0 FPL season points) · In: Marcos Senesi Barón (DEF, 5.0 FPL season points)
For Spurs.
The rule: The home team's three top-scoring starters are taken out and the best available player at the same position comes in. Everything else is unchanged. We fixed it before running anything and ran it for 2 upcoming games. This is the next game on the schedule, shown whatever it moved; in a typical game it moved 4.5 points.
2 · What the simulation showed
Taking out Jan Paul van Hecke, Sandro Tonali and Andrew Robertson (Ben Davies, Mohammed Kudus and Marcos Senesi Barón in): these runs do not establish a clear change in the simulated result.
The biggest shift was Crystal Palace win, from 20% to 27%; the 95% interval for that change runs from −5.4 to +19.2 points, which includes zero. That is not proof of no effect, only that 100 runs cannot tell.
Approximate scenario result. The engine has not been calibrated on held-out matches. These percentages describe its runs, not verified match-outcome probabilities. The 95% intervals measure simulation sampling variability; they exclude model and player-input error.
| Outcome | Before | After | Change, 95% interval | Reading |
|---|---|---|---|---|
| Spurs win | 55% | 55% (±0) | −13.9 to +13.9 pts | not clear |
| Draw | 25% | 18% (−7) | −18.6 to +4.8 pts | not clear |
| Crystal Palace win | 20% | 27% (+7) | −5.4 to +19.2 pts | not clear |
3Inspect the paired runs
The opponent and random seeds are unchanged; only the listed lineup swaps differ.
Projected lineup · 100 games
- Spurs win 55
- Draw 25
- Crystal Palace win 20
Changed lineup · the same 100 games
- Spurs win 55
- Draw 18
- Crystal Palace win 27
Every game we ran
- Spurs v Crystal Palace: Spurs win 55% → 55% (±0)
- Aston Villa v Fulham: Aston Villa win 36% → 45% (+9)
What the comparison can tell you
Match forecast when this example was saved (Live logit model, Fri 30 Oct, 09:15 UTC): Spurs 34.5% · Draw 30.4% · Crystal Palace 35.1%.
The match forecast is the kind of number the sport pages and the forecast record show: a statistical model of final scores, fitted and checked against games played before kickoff. The one above is a saved snapshot; the forecast on the sport page is the current one and moves with new results, so the two can differ. See the current forecast.
The scenario engine (approximate) above is a different model, built to compare one lineup against another. It plays the game out with the chosen players and has not been calibrated on held-out matches, so its percentages can sit far from the forecast (here Spurs 55% against 34.5%). Use it to explore how the model responds to the listed change. It does not establish the true effect of a player, a recruitment decision or the chance of a result.
How this example was made
- The game
- Spurs v Crystal Palace: of the 2 upcoming games from the published schedule that we ran, the first one on the schedule, kept whatever the change did to it.
- Paired runs
- Game i in each lineup uses the same random seed. The 95% change intervals use Newcombe’s paired score interval with continuity correction. They describe sampling variability within this simulation.
- The model
- Complete physical games (sim/physical, production profile). Complete physical games, played without drawing.
- Status
- Engine games are not yet calibrated on held-out results; see the engine lab report.
- What it is not
- 100 complete games played by the simulation engine without drawing them, from the same saved players. Sampling intervals do not include model error. Not bookmaker prices.
- Squad data
- Official FPL squad snapshot: projected, not confirmed starters.
- Computed
- Fri 30 Oct, 09:23 UTC. Shown until Sat 31 Oct, 17:30 UTC, then hidden until a new one is built.
- Starting lineups
- Spurs
- Antonín Kinský
- Jan Paul van Hecke
- Micky van de Ven
- Andrew Robertson
- Pedro Porro Sauceda
- Sandro Tonali
- Archie Gray
- Mateus Fernandes
- Omar Marmoush
- Dominic Solanke-Mitchell
- Mathys Tel
Crystal Palace- Walter Benítez
- Chris Richards
- Tyrick Mitchell
- Anan Khalaili
- Jaydee Canvot
- Adam Wharton
- Daichi Kamada
- Yéremy Pino Santos
- Jørgen Strand Larsen
- Eddie Nketiah
- Jean-Philippe Mateta
Honest About Uncertainty
A lineup comparison is an estimate from a model, never a guarantee or betting advice. The scenario engine has not been calibrated on held-out matches, and its intervals cover sampling only.
- The same opponent and random seeds in both lineups
- The selection rule fixed before anything was run
- The match forecast is checked separately, on the forecast record
Try your own change
Editing and saving a lineup is free. Running it uses simulations from a plan, and what you get back reads like the example above.
Get a Second Opinion Before Game Time
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