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Track record

How the Championship model actually performs

A model is only worth its calibration. Every number below is an out-of-sample prediction for a 26/27 Championship fixture, made before kick-off from earlier data only, then checked against what actually happened. No cherry-picking, no hindsight.

Read this first. This page measures two things: whether our probabilities are honest — do the events we call 30% happen about 30% of the time? — and whether the prices we flag as value beat the closing line. It is not a profit record: calibration proves the numbers are sound, closing line value proves they beat the market, and neither is a promise of profit. We grade everything against a baseline so a confident-looking model can't hide.

38,051
predictions graded, out of sample
15/20
markets beat a base-rate baseline
96
26/27 fixtures scored as-of kick-off

Every market — does the model call it straight, and beat guessing?

Two honest questions per market. First, are our percentages true — when we say something happens 30% of the time, does it? The bar shows it: grey is what we said, green is what actually happened; the closer they sit, the straighter the call. Second, is the model genuinely sharper than just predicting the season average for everyone? That's the badge.

✓ Sharp — clearly beats guessing (the model genuinely knows more here).  Slim edge — beats it, but only just; near the base rate.  ≈ No real edge — no better than guessing: the noisiest markets, where even a sharp model has little to add. The % is skill over a base-rate baseline — not a claim about beating a bookmaker. We leave the weak ones in, because a record you only show when it flatters you isn't one.
MarketWe said → it happenedSharper than guessing?
2+ shots
2,500 predictions
said 22%happened 25%
✓ Sharp +20%
1+ shot
2,500 predictions
said 44%happened 52%
✓ Sharp +20%
1+ tackle
2,500 predictions
said 53%happened 57%
✓ Sharp +19%
3+ shots
2,500 predictions
said 11%happened 11%
✓ Sharp +18%
2+ tackles
2,500 predictions
said 27%happened 28%
✓ Sharp +14%
1+ foul committed
2,500 predictions
said 48%happened 52%
✓ Sharp +14%
1+ shot on target
2,500 predictions
said 21%happened 23%
✓ Sharp +13%
1+ foul won
2,500 predictions
said 46%happened 50%
✓ Sharp +12%
2+ fouls won
2,500 predictions
said 19%happened 21%
✓ Sharp +11%
2+ shots on target
2,500 predictions
said 6%happened 5%
✓ Sharp +9%
2+ fouls committed
2,500 predictions
said 20%happened 20%
✓ Sharp +8%
3+ fouls won
2,500 predictions
said 8%happened 7%
✓ Sharp +7%
said 7%happened 8%
✓ Sharp +6%
3+ fouls committed
2,500 predictions
said 8%happened 6%
Slim edge +4%
To be carded
2,500 predictions
said 13%happened 13%
≈ No real edge
4+ saves
188 predictions
said 31%happened 30%
✗ No edge
3+ saves
188 predictions
said 50%happened 48%
✗ No edge
5+ saves
188 predictions
said 18%happened 13%
✗ No edge
Team & match markets
Match Over 3.5 cards
67 predictions
said 52%happened 51%
✓ Sharp +9%
Match Over 2.5 goals
67 predictions
said 43%happened 64%
✗ No edge
Show the full numbers — predictions, Brier score, baseline

Brier score measures per-prediction accuracy (lower is better); the baseline is what you'd score by predicting the same base rate for everyone. Skill is how far the model beats that baseline — the maths behind the badge above.

MarketPredictionsModel avg ActualBrierBaseline Skill
To be carded 2,500 13% 13% 0.116 0.116 +0.4%
1+ shot on target 2,500 21% 23% 0.155 0.179 +13.4%
2+ shots on target 2,500 6% 5% 0.047 0.051 +8.7%
1+ shot 2,500 44% 52% 0.200 0.249 +19.8%
2+ shots 2,500 22% 25% 0.149 0.186 +19.9%
3+ shots 2,500 11% 11% 0.080 0.098 +17.6%
1+ foul committed 2,500 48% 52% 0.216 0.250 +13.6%
2+ fouls committed 2,500 20% 20% 0.149 0.161 +7.8%
3+ fouls committed 2,500 8% 6% 0.059 0.061 +3.6%
1+ foul won 2,500 46% 50% 0.220 0.250 +12.1%
2+ fouls won 2,500 19% 21% 0.147 0.165 +10.7%
3+ fouls won 2,500 8% 7% 0.059 0.063 +6.9%
1+ tackle 2,500 53% 57% 0.197 0.244 +19.4%
2+ tackles 2,500 27% 28% 0.174 0.203 +14.0%
1+ outside-box shot on target 2,487 7% 8% 0.069 0.073 +5.7%
3+ saves 188 50% 48% 0.275 0.250 -10.2%
4+ saves 188 31% 30% 0.222 0.211 -5.2%
5+ saves 188 18% 13% 0.123 0.111 -10.6%
Team & match markets
Match Over 2.5 goals 67 43% 64% 0.263 0.230 -14.2%
Match Over 3.5 cards 67 52% 51% 0.227 0.250 +9.4%

Calibration, up close

The aggregate can look right while the details are wrong, so here's the finer view. We sort every prediction into groups by how confident the model was — all the ~20% calls, all the ~30% calls, and so on — then check how often each group actually happened. The model is well calibrated when the two line up: when the things it calls 30% happen about 30% of the time. In each row, grey is what the model said and green is what actually happened — the closer they are, the better. Tap any market to open it.

What the model said What actually happened
To be carded
Model saidhow often it happenedActualPicks
5%
9% 1,067
14%
15% 960
24%
19% 357
34%
20% 96
1+ shot on target
Model saidhow often it happenedActualPicks
4%
5% 537
15%
15% 784
25%
26% 524
35%
40% 357
44%
53% 241
54%
61% 54
2+ shots on target
Model saidhow often it happenedActualPicks
3%
2% 1,958
15%
15% 413
24%
20% 113
1+ shot
Model saidhow often it happenedActualPicks
1%
3% 212
16%
21% 111
26%
34% 258
35%
44% 462
45%
50% 398
55%
63% 360
65%
74% 394
74%
89% 266
82%
92% 39
2+ shots
Model saidhow often it happenedActualPicks
4%
6% 737
14%
15% 621
25%
26% 375
35%
37% 318
45%
56% 265
54%
66% 145
64%
67% 36
3+ shots
Model saidhow often it happenedActualPicks
3%
3% 1,479
15%
11% 472
25%
27% 305
34%
40% 174
44%
44% 59
1+ foul committed
Model saidhow often it happenedActualPicks
1%
0% 187
16%
26% 65
25%
32% 209
35%
46% 279
45%
49% 449
55%
59% 582
65%
66% 456
74%
75% 227
82%
87% 45
2+ fouls committed
Model saidhow often it happenedActualPicks
4%
7% 685
15%
15% 659
25%
26% 594
34%
32% 338
44%
41% 157
54%
47% 57
3+ fouls committed
Model saidhow often it happenedActualPicks
4%
4% 1,785
14%
12% 522
24%
19% 145
33%
15% 40
1+ foul won
Model saidhow often it happenedActualPicks
7%
15% 39
16%
24% 199
25%
23% 353
35%
43% 330
45%
47% 476
55%
60% 506
64%
70% 395
74%
78% 185
2+ fouls won
Model saidhow often it happenedActualPicks
5%
7% 808
15%
17% 648
25%
28% 529
34%
37% 306
44%
47% 161
54%
45% 40
3+ fouls won
Model saidhow often it happenedActualPicks
3%
3% 1,748
14%
11% 534
24%
22% 173
33%
27% 37
1+ tackle
Model saidhow often it happenedActualPicks
2%
2% 197
15%
26% 65
26%
33% 132
35%
38% 229
46%
51% 282
56%
62% 403
65%
69% 649
74%
80% 466
82%
88% 77
2+ tackles
Model saidhow often it happenedActualPicks
4%
5% 525
15%
17% 379
25%
27% 418
35%
36% 530
44%
43% 438
54%
58% 172
63%
69% 36
1+ outside-box shot on target
Model saidhow often it happenedActualPicks
4%
5% 1,775
14%
13% 577
23%
30% 126

Where the model earns its keep

The shots, fouls and tackles markets are the bulk of what the tool prices, and it beats a base-rate baseline by up to 20% on them — scored using only matches played before each game, so nothing is fitted with hindsight. That's most of the board, and the part the tool is built to price.

We show the ones that don’t, too. To be carded, 3+ saves, 4+ saves, 5+ saves and Match Over 2.5 goals came out no better than guessing the league average this season — the noisiest markets on the board, where even a sharp model has little to add. We leave them on the page because a track record you only show when it flatters you isn't one.

Closing line value

Whether our prices beat the market's own closing view is measured across every league at once, not per competition — the Championship has the most legs of any single league and still sits below the sample a closing-line read needs. Pooled, the record covers 3,186 legs.

See the full closing line value record

Method: player markets scored as-of each kick-off using only prior matches (the recency-weighted rate never sees the future); team markets fit on earlier seasons and evaluated on 26/27. Regenerated from source data on 2026-10-12. Full method on the methodology page.

The scoreboard above is free, and it always will be. The paid tool is that same model, pointed at this week's prices — the edge, and the confidence, on every leg.