Updated daily through the season. Spot something off? Tell usUpdated daily. Tell us
SharpXI©
Track record

How the Eredivisie model actually performs

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

26,359
predictions graded, out of sample
16/18
markets beat a base-rate baseline
72
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
1,853 predictions
said 23%happened 28%
✓ Sharp +25%
1+ shot
1,853 predictions
said 45%happened 54%
✓ Sharp +23%
3+ shots
1,853 predictions
said 13%happened 14%
✓ Sharp +21%
1+ tackle
1,853 predictions
said 54%happened 59%
✓ Sharp +18%
1+ shot on target
1,853 predictions
said 24%happened 27%
✓ Sharp +18%
2+ tackles
1,853 predictions
said 29%happened 29%
✓ Sharp +16%
2+ shots on target
1,853 predictions
said 8%happened 8%
✓ Sharp +14%
1+ foul won
1,853 predictions
said 43%happened 47%
✓ Sharp +14%
1+ foul committed
1,853 predictions
said 46%happened 49%
✓ Sharp +13%
2+ fouls won
1,853 predictions
said 17%happened 18%
✓ Sharp +10%
4+ saves
139 predictions
said 42%happened 42%
✓ Sharp +9%
3+ fouls won
1,853 predictions
said 7%happened 6%
✓ Sharp +9%
2+ fouls committed
1,853 predictions
said 19%happened 19%
✓ Sharp +7%
5+ saves
139 predictions
said 28%happened 30%
✓ Sharp +7%
3+ fouls committed
1,853 predictions
said 7%happened 6%
Slim edge +3%
3+ saves
139 predictions
said 59%happened 57%
≈ No real edge
To be carded
1,853 predictions
said 10%happened 10%
✗ No edge
Team & match markets
Match Over 3.5 cards
72 predictions
said 42%happened 32%
✓ Sharp +6%
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 1,853 10% 10% 0.088 0.088 -0.3%
1+ shot on target 1,853 24% 27% 0.160 0.195 +18.0%
2+ shots on target 1,853 8% 8% 0.062 0.072 +13.8%
1+ shot 1,853 45% 54% 0.191 0.248 +23.0%
2+ shots 1,853 23% 28% 0.153 0.203 +24.6%
3+ shots 1,853 13% 14% 0.095 0.121 +21.4%
1+ foul committed 1,853 46% 49% 0.217 0.250 +13.3%
2+ fouls committed 1,853 19% 19% 0.142 0.153 +7.2%
3+ fouls committed 1,853 7% 6% 0.053 0.055 +3.2%
1+ foul won 1,853 43% 47% 0.215 0.249 +13.5%
2+ fouls won 1,853 17% 18% 0.136 0.151 +9.9%
3+ fouls won 1,853 7% 6% 0.051 0.056 +8.7%
1+ tackle 1,853 54% 59% 0.198 0.242 +18.3%
2+ tackles 1,853 29% 29% 0.174 0.207 +16.0%
3+ saves 139 59% 57% 0.241 0.245 +1.9%
4+ saves 139 42% 42% 0.222 0.244 +9.1%
5+ saves 139 28% 30% 0.193 0.208 +7.2%
Team & match markets
Match Over 3.5 cards 72 42% 32% 0.205 0.217 +5.8%

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
6%
7% 1,028
14%
13% 652
24%
12% 158
1+ shot on target
Model saidhow often it happenedActualPicks
4%
5% 341
15%
12% 536
25%
30% 357
35%
37% 264
45%
53% 234
54%
65% 106
2+ shots on target
Model saidhow often it happenedActualPicks
3%
3% 1,307
15%
12% 332
24%
29% 171
33%
46% 39
1+ shot
Model saidhow often it happenedActualPicks
1%
1% 142
16%
15% 91
26%
30% 184
35%
44% 342
45%
52% 298
55%
67% 246
65%
78% 269
74%
87% 230
82%
96% 51
2+ shots
Model saidhow often it happenedActualPicks
4%
5% 521
14%
16% 463
25%
28% 260
35%
42% 215
45%
60% 214
55%
72% 123
64%
82% 50
3+ shots
Model saidhow often it happenedActualPicks
3%
3% 1,068
14%
14% 295
25%
27% 240
34%
40% 153
44%
56% 78
1+ foul committed
Model saidhow often it happenedActualPicks
1%
2% 140
16%
18% 39
25%
31% 176
36%
36% 201
45%
52% 375
55%
55% 469
64%
66% 359
73%
76% 85
2+ fouls committed
Model saidhow often it happenedActualPicks
4%
5% 497
15%
16% 522
25%
25% 491
34%
34% 270
43%
35% 57
3+ fouls committed
Model saidhow often it happenedActualPicks
4%
3% 1,365
14%
12% 422
23%
15% 52
1+ foul won
Model saidhow often it happenedActualPicks
7%
13% 87
16%
15% 128
25%
26% 238
35%
40% 270
45%
50% 449
55%
57% 371
64%
72% 218
74%
81% 79
2+ fouls won
Model saidhow often it happenedActualPicks
5%
6% 614
15%
17% 560
24%
22% 381
34%
38% 184
44%
44% 84
3+ fouls won
Model saidhow often it happenedActualPicks
4%
3% 1,405
14%
12% 317
24%
21% 99
1+ tackle
Model saidhow often it happenedActualPicks
2%
4% 128
16%
36% 33
25%
30% 105
35%
41% 179
45%
48% 202
55%
62% 296
65%
71% 387
75%
80% 415
83%
80% 107
2+ tackles
Model saidhow often it happenedActualPicks
4%
5% 369
15%
14% 283
25%
28% 310
35%
30% 309
45%
46% 336
54%
63% 174
64%
53% 66

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 ones that don’t, too. To be carded and 3+ saves 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 3,376 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 2026-10-14. 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.