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Track record

How the La Liga model actually performs

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

27,649
predictions graded, out of sample
19/20
markets beat a base-rate baseline
70
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
1,846 predictions
said 21%happened 24%
✓ Sharp +25%
1+ shot
1,846 predictions
said 42%happened 48%
✓ Sharp +24%
3+ shots
1,846 predictions
said 11%happened 12%
✓ Sharp +23%
1+ tackle
1,846 predictions
said 55%happened 61%
✓ Sharp +20%
1+ shot on target
1,846 predictions
said 21%happened 24%
✓ Sharp +17%
2+ tackles
1,846 predictions
said 30%happened 32%
✓ Sharp +17%
2+ shots on target
1,846 predictions
said 7%happened 7%
✓ Sharp +16%
1+ foul won
1,846 predictions
said 46%happened 50%
✓ Sharp +16%
2+ fouls won
1,846 predictions
said 21%happened 21%
✓ Sharp +15%
1+ foul committed
1,846 predictions
said 50%happened 54%
✓ Sharp +14%
3+ fouls won
1,846 predictions
said 10%happened 8%
✓ Sharp +12%
2+ fouls committed
1,846 predictions
said 23%happened 22%
✓ Sharp +8%
4+ saves
140 predictions
said 31%happened 36%
✓ Sharp +6%
5+ saves
140 predictions
said 19%happened 25%
✓ Sharp +6%
said 9%happened 10%
✓ Sharp +5%
3+ fouls committed
1,846 predictions
said 10%happened 7%
Slim edge +3%
3+ saves
140 predictions
said 48%happened 54%
Slim edge +2%
To be carded
1,846 predictions
said 15%happened 15%
✗ No edge
Team & match markets
Match Over 2.5 goals
49 predictions
said 51%happened 59%
✓ Sharp +11%
Match Over 3.5 cards
49 predictions
said 67%happened 55%
Slim edge +3%
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 1,846 15% 15% 0.127 0.124 -2.1%
1+ shot on target 1,846 21% 24% 0.149 0.180 +17.4%
2+ shots on target 1,846 7% 7% 0.056 0.066 +16.2%
1+ shot 1,846 42% 48% 0.189 0.250 +24.5%
2+ shots 1,846 21% 24% 0.138 0.183 +24.7%
3+ shots 1,846 11% 12% 0.081 0.104 +22.6%
1+ foul committed 1,846 50% 54% 0.213 0.248 +14.2%
2+ fouls committed 1,846 23% 22% 0.156 0.170 +8.0%
3+ fouls committed 1,846 10% 7% 0.063 0.065 +3.0%
1+ foul won 1,846 46% 50% 0.211 0.250 +15.7%
2+ fouls won 1,846 21% 21% 0.141 0.165 +14.6%
3+ fouls won 1,846 10% 8% 0.062 0.070 +12.0%
1+ tackle 1,846 55% 61% 0.191 0.239 +20.2%
2+ tackles 1,846 30% 32% 0.179 0.216 +17.2%
1+ outside-box shot on target 1,385 9% 10% 0.083 0.088 +5.4%
3+ saves 140 48% 54% 0.243 0.249 +2.4%
4+ saves 140 31% 36% 0.216 0.230 +5.9%
5+ saves 140 19% 25% 0.177 0.188 +5.6%
Team & match markets
Match Over 2.5 goals 49 51% 59% 0.214 0.242 +11.3%
Match Over 3.5 cards 49 67% 55% 0.241 0.247 +2.7%

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
6%
12% 641
15%
15% 747
24%
17% 355
34%
23% 79
1+ shot on target
Model saidhow often it happenedActualPicks
5%
4% 480
15%
16% 516
24%
29% 382
35%
39% 222
44%
49% 162
54%
70% 61
2+ shots on target
Model saidhow often it happenedActualPicks
3%
3% 1,415
14%
11% 272
24%
35% 109
34%
50% 36
1+ shot
Model saidhow often it happenedActualPicks
1%
1% 167
16%
17% 119
25%
26% 235
35%
39% 338
45%
55% 308
55%
61% 250
65%
78% 240
74%
88% 150
84%
95% 38
2+ shots
Model saidhow often it happenedActualPicks
4%
4% 624
15%
16% 442
25%
26% 280
35%
38% 197
45%
57% 165
55%
77% 94
65%
78% 32
3+ shots
Model saidhow often it happenedActualPicks
3%
3% 1,142
14%
13% 313
25%
22% 197
34%
43% 114
44%
60% 52
1+ foul committed
Model saidhow often it happenedActualPicks
1%
1% 136
17%
14% 35
26%
39% 119
35%
39% 191
46%
56% 242
56%
59% 422
65%
65% 432
74%
75% 231
83%
82% 38
2+ fouls committed
Model saidhow often it happenedActualPicks
4%
8% 439
15%
17% 355
25%
20% 469
35%
32% 345
44%
38% 184
55%
61% 41
3+ fouls committed
Model saidhow often it happenedActualPicks
4%
3% 1,081
14%
10% 532
24%
18% 188
34%
18% 34
1+ foul won
Model saidhow often it happenedActualPicks
6%
8% 63
16%
18% 132
25%
27% 208
35%
38% 259
45%
51% 323
55%
58% 356
64%
70% 304
74%
80% 175
2+ fouls won
Model saidhow often it happenedActualPicks
5%
6% 550
15%
14% 433
25%
25% 370
34%
29% 259
45%
46% 154
54%
64% 62
3+ fouls won
Model saidhow often it happenedActualPicks
4%
2% 1,165
14%
10% 414
25%
19% 181
34%
39% 66
1+ tackle
Model saidhow often it happenedActualPicks
2%
4% 136
16%
29% 45
25%
32% 89
36%
41% 167
45%
58% 190
55%
59% 276
66%
68% 374
75%
83% 461
83%
87% 107
2+ tackles
Model saidhow often it happenedActualPicks
4%
4% 362
15%
17% 265
25%
28% 284
35%
33% 310
45%
48% 342
55%
61% 228
64%
65% 49
1+ outside-box shot on target
Model saidhow often it happenedActualPicks
4%
5% 918
14%
16% 325
24%
25% 104
34%
29% 31

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 25% 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 one that doesn’t, too. To be carded came out no better than guessing the league average this season — the noisiest market on the board, where even a sharp model has little to add. We leave it 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.