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Track record

How the UEFA Nations League model actually performs

A model is only worth its calibration. Every number below is an out-of-sample prediction for a 26/27 UEFA Nations League 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.

18,497
predictions graded, out of sample
15/19
markets beat a base-rate baseline
103
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
1,210 predictions
said 23%happened 29%
✓ Sharp +20%
1+ tackle
1,210 predictions
said 52%happened 53%
✓ Sharp +20%
3+ shots
1,210 predictions
said 13%happened 13%
✓ Sharp +19%
1+ shot
1,210 predictions
said 44%happened 57%
✓ Sharp +17%
2+ tackles
1,210 predictions
said 28%happened 26%
✓ Sharp +16%
2+ fouls won
1,210 predictions
said 19%happened 21%
✓ Sharp +16%
1+ foul won
1,210 predictions
said 44%happened 51%
✓ Sharp +15%
1+ shot on target
1,210 predictions
said 22%happened 28%
✓ Sharp +14%
1+ foul committed
1,210 predictions
said 47%happened 51%
✓ Sharp +14%
2+ shots on target
1,210 predictions
said 7%happened 9%
✓ Sharp +12%
3+ fouls won
1,210 predictions
said 8%happened 8%
✓ Sharp +10%
2+ fouls committed
1,210 predictions
said 20%happened 22%
✓ Sharp +6%
said 9%happened 11%
✓ Sharp +6%
3+ saves
116 predictions
said 53%happened 57%
✓ Sharp +5%
3+ fouls committed
1,210 predictions
said 8%happened 6%
Slim edge +4%
4+ saves
116 predictions
said 36%happened 40%
✗ No edge
5+ saves
116 predictions
said 22%happened 27%
✗ No edge
To be carded
1,210 predictions
said 14%happened 10%
✗ No edge
Team & match markets
Match Over 3.5 cards
103 predictions
said 62%happened 30%
✗ 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 1,210 14% 10% 0.099 0.092 -7.2%
1+ shot on target 1,210 22% 28% 0.172 0.200 +13.9%
2+ shots on target 1,210 7% 9% 0.069 0.079 +11.7%
1+ shot 1,210 44% 57% 0.203 0.245 +17.2%
2+ shots 1,210 23% 29% 0.164 0.206 +20.4%
3+ shots 1,210 13% 13% 0.093 0.115 +19.3%
1+ foul committed 1,210 47% 51% 0.215 0.250 +13.9%
2+ fouls committed 1,210 20% 22% 0.159 0.169 +5.6%
3+ fouls committed 1,210 8% 6% 0.058 0.060 +3.5%
1+ foul won 1,210 44% 51% 0.213 0.250 +14.6%
2+ fouls won 1,210 19% 21% 0.140 0.166 +15.8%
3+ fouls won 1,210 8% 8% 0.064 0.071 +10.4%
1+ tackle 1,210 52% 53% 0.199 0.249 +20.1%
2+ tackles 1,210 28% 26% 0.162 0.193 +16.2%
1+ outside-box shot on target 1,209 9% 11% 0.092 0.098 +5.6%
3+ saves 116 53% 57% 0.232 0.245 +5.3%
4+ saves 116 36% 40% 0.242 0.239 -1.2%
5+ saves 116 22% 27% 0.202 0.196 -2.9%
Team & match markets
Match Over 3.5 cards 103 62% 30% 0.353 0.210 -67.8%

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%
8% 524
15%
12% 406
24%
14% 193
34%
9% 70
1+ shot on target
Model saidhow often it happenedActualPicks
4%
6% 282
15%
21% 322
24%
27% 267
35%
42% 185
45%
64% 113
54%
61% 36
2+ shots on target
Model saidhow often it happenedActualPicks
3%
4% 873
14%
15% 212
24%
22% 99
1+ shot
Model saidhow often it happenedActualPicks
0%
2% 122
16%
24% 50
26%
47% 137
35%
50% 193
45%
54% 192
55%
73% 199
64%
76% 166
74%
92% 131
2+ shots
Model saidhow often it happenedActualPicks
4%
6% 354
15%
19% 251
25%
29% 209
35%
44% 167
45%
56% 108
54%
70% 88
3+ shots
Model saidhow often it happenedActualPicks
3%
4% 663
15%
13% 235
24%
19% 144
35%
41% 106
44%
56% 45
1+ foul committed
Model saidhow often it happenedActualPicks
1%
2% 118
26%
30% 89
36%
45% 136
45%
59% 219
55%
60% 286
64%
65% 231
74%
67% 100
2+ fouls committed
Model saidhow often it happenedActualPicks
4%
6% 333
15%
22% 304
25%
28% 300
34%
29% 174
44%
35% 74
3+ fouls committed
Model saidhow often it happenedActualPicks
4%
4% 838
14%
11% 278
24%
16% 76
1+ foul won
Model saidhow often it happenedActualPicks
15%
19% 123
25%
32% 140
35%
41% 197
45%
53% 219
55%
56% 214
64%
76% 204
74%
88% 72
2+ fouls won
Model saidhow often it happenedActualPicks
5%
6% 398
15%
14% 306
25%
27% 218
34%
41% 180
44%
46% 69
3+ fouls won
Model saidhow often it happenedActualPicks
3%
2% 811
14%
16% 283
24%
19% 75
1+ tackle
Model saidhow often it happenedActualPicks
3%
2% 122
16%
13% 38
25%
43% 72
35%
42% 103
46%
39% 118
56%
58% 180
65%
62% 275
74%
75% 237
83%
86% 64
2+ tackles
Model saidhow often it happenedActualPicks
3%
2% 297
15%
14% 153
25%
28% 183
35%
30% 243
45%
44% 187
55%
50% 105
64%
74% 39
1+ outside-box shot on target
Model saidhow often it happenedActualPicks
3%
6% 795
15%
16% 238
24%
21% 114
34%
22% 37

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, 4+ saves, 5+ saves and Match Over 3.5 cards 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.