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Serie B
Spal
T S T T U
0–0
Full-time
Pisa
U S S 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 Pisa
Last 6 — all competitions · 6/6 matches
Win Ø 50%
33%
67%
Points per game
1,2
2,2
Over 2.5 Ø 34%
50%
17%
Both score Ø 42%
50%
33%
Average goals
2,7
1,8
Scored
0,8
1,2
Conceded
1,8
0,7
Goal diff per game
-1,0
+0,5
This season — Serie B · 19/19 matches
Win Ø 42%
26%
58%
Points per game
1,1
2,0
Over 2.5 Ø 37%
47%
26%
Both score Ø 56%
58%
53%
Average goals
2,6
2,2
Scored
1,2
1,4
Conceded
1,4
0,8
Goal diff per game
-0,2
+0,6
🔒 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 9
0 Shots on target 3
5 Corners 2
17 Free kicks against 22
3 Yellow cards 4
0 Red cards 0
The table before the match Spal 15. · Pisa 1.
# Team K V U T +/− P
1 Pisa 19 11 5 3 +12 38
2 Brescia 19 11 4 4 +12 37
3 Benevento 19 10 5 4 +15 35
4 Cremonese 19 10 5 4 +12 35
5 Lecce 18 9 7 2 +15 34
6 Frosinone 20 8 10 2 +14 34
7 Monza 19 8 8 3 +6 32
8 Cittadella 18 8 5 5 +3 29
9 Ascoli 19 8 5 6 +0 29
10 Perugia 19 6 10 3 +3 28
11 Como 19 6 7 6 +1 25
12 Parma 19 5 8 6 -1 23
13 Ternana 19 6 5 8 -2 23
14 Reggina 19 6 5 8 -10 23
15 Spal 19 5 6 8 -4 21
16 Alessandria 18 5 2 11 -10 17
17 Cosenza 18 4 4 10 -14 16
18 Crotone 18 2 5 11 -12 11
19 Pordenone 19 1 5 13 -23 8
20 Vicenza 17 2 1 14 -17 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
2,74
U ✓
3,08
B
2,63
Over/under goals
U1,5 ✓
O2,5
2,02
U2,5 ✓
1,77
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.