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SharpXI©
Track record

How the UEFA Champions League model actually performs

A model is only worth its calibration. Every number below is an out-of-sample prediction for a 25/26 UEFA Champions 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.

56,126
predictions graded, out of sample
15/20
markets beat a base-rate baseline
189
25/26 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
3,688 predictions
said 24%happened 27%
✓ Sharp +28%
3+ shots
3,688 predictions
said 14%happened 14%
✓ Sharp +26%
1+ shot
3,688 predictions
said 45%happened 53%
✓ Sharp +25%
1+ tackle
3,688 predictions
said 55%happened 59%
✓ Sharp +23%
1+ shot on target
3,688 predictions
said 24%happened 29%
✓ Sharp +19%
2+ tackles
3,688 predictions
said 30%happened 32%
✓ Sharp +18%
2+ fouls won
3,688 predictions
said 19%happened 19%
✓ Sharp +16%
1+ foul won
3,688 predictions
said 45%happened 48%
✓ Sharp +16%
2+ shots on target
3,688 predictions
said 8%happened 8%
✓ Sharp +14%
1+ foul committed
3,688 predictions
said 48%happened 53%
✓ Sharp +14%
3+ fouls won
3,688 predictions
said 8%happened 7%
✓ Sharp +10%
said 8%happened 10%
✓ Sharp +8%
2+ fouls committed
3,688 predictions
said 20%happened 20%
✓ Sharp +8%
3+ fouls committed
3,688 predictions
said 8%happened 7%
Slim edge +4%
5+ saves
274 predictions
said 19%happened 23%
Slim edge +3%
4+ saves
274 predictions
said 31%happened 38%
≈ No real edge
To be carded
3,688 predictions
said 12%happened 13%
≈ No real edge
3+ saves
274 predictions
said 47%happened 57%
✗ No edge
Team & match markets
Match Over 2.5 goals
117 predictions
said 59%happened 65%
✗ No edge
Match Over 3.5 cards
117 predictions
said 58%happened 48%
✗ 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 3,688 12% 13% 0.112 0.113 +0.6%
1+ shot on target 3,688 24% 29% 0.167 0.205 +18.6%
2+ shots on target 3,688 8% 8% 0.066 0.077 +14.3%
1+ shot 3,688 45% 53% 0.187 0.249 +25.0%
2+ shots 3,688 24% 27% 0.141 0.195 +28.1%
3+ shots 3,688 14% 14% 0.090 0.120 +25.6%
1+ foul committed 3,688 48% 53% 0.215 0.249 +13.7%
2+ fouls committed 3,688 20% 20% 0.150 0.163 +7.7%
3+ fouls committed 3,688 8% 7% 0.061 0.064 +3.8%
1+ foul won 3,688 45% 48% 0.210 0.249 +15.6%
2+ fouls won 3,688 19% 19% 0.128 0.153 +16.5%
3+ fouls won 3,688 8% 7% 0.058 0.064 +9.9%
1+ tackle 3,688 55% 59% 0.186 0.242 +23.2%
2+ tackles 3,688 30% 32% 0.178 0.216 +17.7%
1+ outside-box shot on target 3,672 8% 10% 0.080 0.087 +8.3%
3+ saves 274 47% 57% 0.256 0.246 -4.1%
4+ saves 274 31% 38% 0.231 0.235 +1.4%
5+ saves 274 19% 23% 0.171 0.177 +3.2%
Team & match markets
Match Over 2.5 goals 117 59% 65% 0.245 0.228 -7.9%
Match Over 3.5 cards 117 58% 48% 0.284 0.249 -13.7%

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
5%
8% 1,802
14%
16% 1,205
24%
22% 478
34%
23% 159
44%
16% 37
1+ shot on target
Model saidhow often it happenedActualPicks
4%
6% 780
15%
17% 975
25%
27% 734
35%
43% 527
44%
58% 405
54%
71% 196
63%
75% 64
2+ shots on target
Model saidhow often it happenedActualPicks
3%
3% 2,559
15%
15% 663
24%
25% 301
34%
38% 125
43%
50% 34
1+ shot
Model saidhow often it happenedActualPicks
1%
2% 308
16%
16% 206
26%
34% 400
35%
42% 567
45%
49% 626
55%
63% 515
65%
78% 535
74%
92% 408
83%
98% 122
2+ shots
Model saidhow often it happenedActualPicks
4%
4% 1,049
15%
12% 835
25%
25% 570
35%
37% 421
45%
56% 407
55%
74% 246
64%
81% 130
3+ shots
Model saidhow often it happenedActualPicks
3%
2% 2,049
14%
13% 627
25%
24% 449
34%
42% 305
44%
53% 170
54%
79% 72
1+ foul committed
Model saidhow often it happenedActualPicks
2%
3% 280
16%
26% 125
26%
36% 289
35%
42% 426
45%
53% 581
55%
61% 814
65%
66% 782
74%
77% 341
83%
84% 49
2+ fouls committed
Model saidhow often it happenedActualPicks
4%
5% 1,017
15%
19% 867
25%
26% 843
34%
28% 618
44%
40% 250
54%
49% 77
3+ fouls committed
Model saidhow often it happenedActualPicks
4%
4% 2,454
14%
11% 918
24%
17% 249
33%
32% 54
1+ foul won
Model saidhow often it happenedActualPicks
7%
10% 114
15%
20% 316
25%
24% 469
35%
38% 565
45%
45% 674
55%
58% 699
65%
72% 539
74%
80% 272
82%
82% 40
2+ fouls won
Model saidhow often it happenedActualPicks
5%
4% 1,223
15%
13% 914
25%
21% 711
34%
37% 477
44%
53% 237
54%
59% 109
3+ fouls won
Model saidhow often it happenedActualPicks
3%
3% 2,491
14%
10% 781
24%
25% 283
34%
29% 111
1+ tackle
Model saidhow often it happenedActualPicks
2%
4% 275
16%
16% 99
25%
28% 198
35%
34% 276
45%
52% 359
55%
57% 536
65%
70% 752
75%
79% 889
83%
88% 299
2+ tackles
Model saidhow often it happenedActualPicks
3%
4% 742
15%
17% 479
25%
25% 557
35%
37% 633
45%
49% 629
54%
53% 464
64%
65% 157
1+ outside-box shot on target
Model saidhow often it happenedActualPicks
4%
5% 2,488
14%
17% 883
24%
25% 244
34%
43% 54
3+ saves
Model saidhow often it happenedActualPicks
36%
56% 52
45%
52% 58
55%
57% 58
64%
73% 44
4+ saves
Model saidhow often it happenedActualPicks
16%
22% 49
24%
37% 75
35%
33% 55
44%
54% 48
5+ saves
Model saidhow often it happenedActualPicks
6%
14% 71
14%
19% 94
26%
23% 65

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 28% 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, Match Over 2.5 goals 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 25/26. 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.