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SharpXI©
Track record

How the Serie A model actually performs

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

20,066
predictions graded, out of sample
18/20
markets beat a base-rate baseline
50
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?
1+ tackle
1,326 predictions
said 53%happened 59%
✓ Sharp +22%
3+ shots
1,326 predictions
said 11%happened 12%
✓ Sharp +22%
2+ shots
1,326 predictions
said 21%happened 27%
✓ Sharp +21%
1+ shot
1,326 predictions
said 44%happened 53%
✓ Sharp +20%
1+ foul committed
1,326 predictions
said 51%happened 50%
✓ Sharp +16%
1+ shot on target
1,326 predictions
said 21%happened 26%
✓ Sharp +16%
2+ fouls won
1,326 predictions
said 20%happened 18%
✓ Sharp +15%
2+ tackles
1,326 predictions
said 28%happened 31%
✓ Sharp +14%
1+ foul won
1,326 predictions
said 46%happened 49%
✓ Sharp +14%
3+ fouls won
1,326 predictions
said 9%happened 7%
✓ Sharp +11%
2+ shots on target
1,326 predictions
said 6%happened 6%
✓ Sharp +9%
said 8%happened 10%
✓ Sharp +7%
5+ saves
96 predictions
said 20%happened 24%
✓ Sharp +6%
2+ fouls committed
1,326 predictions
said 22%happened 18%
Slim edge +5%
3+ saves
96 predictions
said 52%happened 64%
Slim edge +5%
4+ saves
96 predictions
said 34%happened 44%
Slim edge +3%
3+ fouls committed
1,326 predictions
said 9%happened 6%
≈ No real edge
To be carded
1,326 predictions
said 12%happened 11%
≈ No real edge
Team & match markets
Match Over 3.5 cards
50 predictions
said 49%happened 46%
✓ Sharp +11%
Match Over 2.5 goals
50 predictions
said 47%happened 54%
Slim edge +2%
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 1,326 12% 11% 0.097 0.099 +1.2%
1+ shot on target 1,326 21% 26% 0.161 0.191 +15.7%
2+ shots on target 1,326 6% 6% 0.051 0.057 +9.4%
1+ shot 1,326 44% 53% 0.201 0.249 +19.6%
2+ shots 1,326 21% 27% 0.155 0.196 +21.0%
3+ shots 1,326 11% 12% 0.084 0.107 +21.5%
1+ foul committed 1,326 51% 50% 0.210 0.250 +15.8%
2+ fouls committed 1,326 22% 18% 0.141 0.149 +4.9%
3+ fouls committed 1,326 9% 6% 0.059 0.059 +1.3%
1+ foul won 1,326 46% 49% 0.215 0.250 +13.9%
2+ fouls won 1,326 20% 18% 0.126 0.149 +15.2%
3+ fouls won 1,326 9% 7% 0.057 0.064 +10.9%
1+ tackle 1,326 53% 59% 0.187 0.241 +22.4%
2+ tackles 1,326 28% 31% 0.183 0.213 +14.1%
1+ outside-box shot on target 1,214 8% 10% 0.085 0.092 +7.1%
3+ saves 96 52% 64% 0.220 0.232 +4.9%
4+ saves 96 34% 44% 0.239 0.246 +2.7%
5+ saves 96 20% 24% 0.171 0.182 +6.0%
Team & match markets
Match Over 2.5 goals 50 47% 54% 0.242 0.248 +2.5%
Match Over 3.5 cards 50 49% 46% 0.222 0.248 +10.6%

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% 675
14%
12% 456
24%
23% 146
33%
17% 46
1+ shot on target
Model saidhow often it happenedActualPicks
5%
4% 306
15%
19% 404
25%
27% 287
34%
42% 163
45%
58% 125
54%
80% 39
2+ shots on target
Model saidhow often it happenedActualPicks
3%
3% 1,058
14%
14% 178
24%
22% 81
1+ shot
Model saidhow often it happenedActualPicks
1%
2% 106
16%
19% 70
25%
33% 151
35%
44% 241
45%
55% 228
55%
64% 198
64%
78% 167
74%
88% 139
2+ shots
Model saidhow often it happenedActualPicks
4%
6% 427
15%
18% 309
25%
29% 207
35%
44% 169
46%
52% 105
54%
74% 82
3+ shots
Model saidhow often it happenedActualPicks
3%
2% 809
15%
15% 244
24%
24% 122
34%
42% 104
44%
72% 36
1+ foul committed
Model saidhow often it happenedActualPicks
2%
2% 98
26%
32% 89
35%
34% 121
46%
43% 196
56%
55% 269
65%
63% 337
74%
75% 161
2+ fouls committed
Model saidhow often it happenedActualPicks
4%
5% 320
15%
13% 274
25%
20% 310
34%
28% 274
44%
36% 105
54%
33% 36
3+ fouls committed
Model saidhow often it happenedActualPicks
4%
3% 813
14%
9% 384
24%
15% 101
1+ foul won
Model saidhow often it happenedActualPicks
7%
19% 32
16%
19% 108
26%
29% 142
35%
34% 202
45%
45% 273
55%
65% 253
65%
70% 194
74%
75% 97
2+ fouls won
Model saidhow often it happenedActualPicks
5%
4% 401
15%
11% 360
25%
21% 258
34%
34% 163
44%
45% 91
54%
56% 39
3+ fouls won
Model saidhow often it happenedActualPicks
4%
2% 897
14%
12% 269
24%
26% 105
34%
28% 40
1+ tackle
Model saidhow often it happenedActualPicks
2%
6% 100
16%
17% 42
26%
26% 72
35%
44% 126
45%
45% 134
55%
62% 203
65%
74% 306
74%
82% 283
84%
90% 59
2+ tackles
Model saidhow often it happenedActualPicks
4%
7% 284
15%
17% 196
25%
27% 206
35%
42% 255
44%
46% 237
54%
54% 111
1+ outside-box shot on target
Model saidhow often it happenedActualPicks
4%
6% 828
14%
18% 311
24%
29% 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 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 and 3+ fouls committed 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.