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SharpXI©
Track record

How the EFL Cup model actually performs

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

17,581
predictions graded, out of sample
12/18
markets beat a base-rate baseline
76
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
1,238 predictions
said 20%happened 25%
✓ Sharp +22%
1+ tackle
1,238 predictions
said 54%happened 60%
✓ Sharp +19%
2+ tackles
1,238 predictions
said 29%happened 31%
✓ Sharp +17%
3+ shots
1,238 predictions
said 10%happened 14%
✓ Sharp +17%
1+ shot
1,238 predictions
said 42%happened 52%
✓ Sharp +16%
1+ shot on target
1,238 predictions
said 20%happened 26%
✓ Sharp +12%
1+ foul committed
1,238 predictions
said 48%happened 50%
✓ Sharp +12%
2+ shots on target
1,238 predictions
said 6%happened 7%
✓ Sharp +11%
1+ foul won
1,238 predictions
said 45%happened 48%
✓ Sharp +10%
2+ fouls won
1,238 predictions
said 19%happened 19%
✓ Sharp +8%
3+ fouls won
1,238 predictions
said 8%happened 7%
✓ Sharp +6%
2+ fouls committed
1,238 predictions
said 20%happened 18%
Slim edge +3%
3+ fouls committed
1,238 predictions
said 8%happened 5%
≈ No real edge
To be carded
1,238 predictions
said 12%happened 10%
✗ No edge
5+ saves
83 predictions
said 20%happened 14%
✗ No edge
3+ saves
83 predictions
said 48%happened 46%
✗ No edge
4+ saves
83 predictions
said 32%happened 26%
✗ No edge
Team & match markets
Match Over 3.5 cards
75 predictions
said 42%happened 36%
✗ 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 1,238 12% 10% 0.096 0.093 -3.5%
1+ shot on target 1,238 20% 26% 0.169 0.192 +12.3%
2+ shots on target 1,238 6% 7% 0.059 0.066 +11.1%
1+ shot 1,238 42% 52% 0.209 0.249 +16.2%
2+ shots 1,238 20% 25% 0.148 0.189 +21.6%
3+ shots 1,238 10% 14% 0.098 0.118 +16.8%
1+ foul committed 1,238 48% 50% 0.221 0.250 +11.8%
2+ fouls committed 1,238 20% 18% 0.144 0.148 +3.1%
3+ fouls committed 1,238 8% 5% 0.051 0.051 +0.2%
1+ foul won 1,238 45% 48% 0.226 0.250 +9.6%
2+ fouls won 1,238 19% 19% 0.142 0.155 +8.5%
3+ fouls won 1,238 8% 7% 0.062 0.066 +6.5%
1+ tackle 1,238 54% 60% 0.196 0.240 +18.6%
2+ tackles 1,238 29% 31% 0.176 0.213 +17.0%
3+ saves 83 48% 46% 0.308 0.248 -24.2%
4+ saves 83 32% 26% 0.245 0.195 -25.8%
5+ saves 83 20% 14% 0.153 0.124 -23.5%
Team & match markets
Match Over 3.5 cards 75 42% 36% 0.303 0.230 -31.4%

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%
7% 622
15%
13% 413
24%
18% 141
34%
11% 46
1+ shot on target
Model saidhow often it happenedActualPicks
5%
10% 311
15%
18% 379
25%
29% 255
35%
45% 166
44%
58% 95
2+ shots on target
Model saidhow often it happenedActualPicks
3%
3% 972
14%
16% 203
24%
33% 51
1+ shot
Model saidhow often it happenedActualPicks
1%
1% 92
16%
29% 83
26%
36% 169
35%
43% 210
45%
56% 210
55%
66% 193
65%
82% 179
74%
76% 88
2+ shots
Model saidhow often it happenedActualPicks
4%
6% 401
15%
15% 312
25%
28% 195
35%
45% 144
44%
59% 116
54%
70% 54
3+ shots
Model saidhow often it happenedActualPicks
3%
4% 770
14%
20% 227
24%
31% 146
34%
44% 63
1+ foul committed
Model saidhow often it happenedActualPicks
2%
0% 84
16%
29% 42
26%
34% 104
36%
44% 158
45%
47% 227
55%
61% 253
65%
64% 233
74%
70% 114
2+ fouls committed
Model saidhow often it happenedActualPicks
4%
6% 340
15%
17% 326
25%
22% 265
35%
27% 184
44%
31% 90
3+ fouls committed
Model saidhow often it happenedActualPicks
4%
3% 841
14%
9% 280
23%
14% 88
1+ foul won
Model saidhow often it happenedActualPicks
15%
28% 110
25%
29% 163
34%
39% 186
45%
45% 224
55%
57% 249
64%
64% 191
74%
81% 79
2+ fouls won
Model saidhow often it happenedActualPicks
5%
8% 427
15%
17% 282
25%
24% 264
34%
27% 166
45%
46% 69
3+ fouls won
Model saidhow often it happenedActualPicks
4%
3% 869
14%
12% 258
24%
24% 79
1+ tackle
Model saidhow often it happenedActualPicks
2%
2% 82
26%
27% 74
35%
51% 98
45%
53% 147
55%
59% 192
65%
70% 280
75%
79% 274
83%
94% 62
2+ tackles
Model saidhow often it happenedActualPicks
4%
7% 240
15%
15% 186
25%
20% 195
35%
38% 233
45%
46% 221
54%
62% 122
64%
78% 32

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 22% 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+ fouls committed, 3+ saves, 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.