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Serie B
Spal
U T S T S
0–2
Full-time
Brescia
S S T S T

Retrospective analysis — the model is trained only on matches played before this one.

🔒 Who wins? Pro

The model's probabilities for a home win, draw and away win — with reasoning and recommended markets.

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Team trends

Spal Brescia
Last 6 — all competitions · 6/6 matches
Win Ø 50%
33%
67%
Points per game
1,2
2,0
Over 2.5 Ø 42%
67%
17%
Both score Ø 50%
83%
17%
Average goals
3,0
1,8
Scored
1,3
1,0
Conceded
1,7
0,8
Goal diff per game
-0,3
+0,2
This season — Serie B · 16/16 matches
Win Ø 44%
31%
56%
Points per game
1,3
1,9
Over 2.5 Ø 47%
50%
44%
Both score Ø 57%
63%
50%
Average goals
2,6
2,9
Scored
1,4
1,7
Conceded
1,3
1,2
Goal diff per game
+0,1
+0,5
🔒 Goal markets Pro

Expected goals, over/under and both teams to score — priced by the model before kick-off.

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🔒 Most likely result Pro

The model's top final scores with the best bookmaker odds.

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Match stats

Half-time score: 0–0

15 Shots 14
3 Shots on target 7
7 Corners 3
7 Free kicks against 16
1 Yellow cards 2
0 Red cards 0
The table before the match Spal 14. · Brescia 4.
# Team K V U T +/− P
1 Pisa 16 9 5 2 +11 32
2 Lecce 16 8 7 1 +15 31
3 Benevento 17 9 4 4 +13 31
4 Brescia 16 9 3 4 +8 30
5 Cremonese 17 8 5 4 +7 29
6 Monza 16 7 7 2 +7 28
7 Ascoli 16 7 5 4 +3 26
8 Frosinone 16 5 10 1 +8 25
9 Perugia 16 6 7 3 +3 25
10 Cittadella 16 7 4 5 +1 25
11 Ternana 17 6 4 7 +0 22
12 Reggina 16 6 4 6 -4 22
13 Como 16 5 6 5 +2 21
14 Spal 16 5 5 6 +2 20
15 Parma 16 4 7 5 -2 19
16 Cosenza 16 4 3 9 -12 15
17 Alessandria 16 4 2 10 -12 14
18 Crotone 17 1 5 11 -15 8
19 Vicenza 16 2 1 13 -16 7
20 Pordenone 16 1 4 11 -19 7

Calculated from our results data. “xG +/−” is expected goal difference — a positive number with a low league position suggests an undervalued team. Ties on points are sorted by goal difference; some leagues use other rules.

Odds comparison

Green columns are the outcomes that came in.

1X2
H
2,73
U
3,27
B ✓
2,53
Over/under goals
O1,5 ✓
O2,5
1,93
U2,5 ✓
1,86
U3,5 ✓
Both teams to score
BLS ja
BLS nei ✓

The analysis is a statistical estimate based on the teams' results and underlying performances (xG) — not a guarantee. See the model's results.