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Serie B
Cittadella
S U T T S
2–0
Full-time
Pisa
S T U U U

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

Cittadella Pisa
Last 6 — all competitions · 6/6 matches
Win Ø 25%
33%
17%
Points per game
1,2
1,2
Over 2.5 Ø 25%
33%
17%
Both score Ø 58%
33%
83%
Average goals
1,5
2,2
Scored
0,7
1,2
Conceded
0,8
1,0
Goal diff per game
-0,2
+0,2
This season — Serie B · 11/11 matches
Win Ø 50%
45%
55%
Points per game
1,5
2,0
Over 2.5 Ø 36%
36%
36%
Both score Ø 55%
36%
73%
Average goals
2,2
2,5
Scored
1,0
1,7
Conceded
1,2
0,8
Goal diff per game
-0,2
+0,9
🔒 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

14 Shots 6
3 Shots on target 2
6 Corners 5
22 Free kicks against 13
3 Yellow cards 3
0 Red cards 3
The table before the match Cittadella 14. · Pisa 3.
# Team K V U T +/− P
1 Brescia 12 7 3 2 +9 24
2 Lecce 12 6 5 1 +11 23
3 Pisa 11 6 4 1 +10 22
4 Reggina 12 6 4 2 +4 22
5 Frosinone 12 5 6 1 +8 21
6 Benevento 12 5 4 3 +6 19
7 Como 12 5 4 3 +4 19
8 Cremonese 12 5 4 3 +4 19
9 Ascoli 12 5 3 4 +1 18
10 Monza 12 4 6 2 +1 18
11 Perugia 12 4 5 3 +0 17
12 Ternana 12 5 1 6 +1 16
13 Parma 12 4 4 4 -1 16
14 Cittadella 11 5 1 5 -2 16
15 Spal 12 3 5 4 +3 14
16 Cosenza 12 4 2 6 -6 14
17 Crotone 12 1 5 6 -9 8
18 Alessandria 12 2 2 8 -11 8
19 Vicenza 12 1 1 10 -14 4
20 Pordenone 12 0 3 9 -19 3

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 ✓
2,26
U
2,98
B
3,43
Over/under goals
O1,5 ✓
O2,5
2,16
U2,5 ✓
1,67
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.