Pisa won 1 of the last 5DLDDW8th3–3Palermo won 3 of the last 5DWDWW1st
Match statistics
Full-time statistics
Pisa
Palermo
12
Shots
13
6
Shots on target
5
5
Corners
3
10
Fouls
9
2
Yellow cards
0
0
Red cards
0
5
Offsides
1
466
Passes
416
53%
Possession %
47%
2.50
xG
1.32
20%
22%
58%
1 · PisaXPalermo · 2
Over 1.5
83%
Over 2.5
62%
Over 3.5
40%
Both score
60%
Model pick
Palermo 58%
Likely score
1-1 10%
Expected goals
1.14 – 2.05
Advised bets
No advised bet on this fixture. The available prices are close enough to our own numbers that there is nothing worth backing. Most fixtures end up here, and manufacturing a selection for every game is exactly how tipster records get destroyed.
Our probabilities against the market
Our probability and fair price for every market we publish, next to the best price we last captured and the probability it implies (bookmaker margin included).
Market
Selection
Ours
Fair
Best price
Implied
Gap
Match result
Pisa
20.3%
4.94
2.50 Betano
40.0%
-19.7
Match result
Draw
22.1%
4.53
3.50 BetVictor
28.6%
-6.5
Match result
Palermo
57.7%
1.73
3.00 Betfair
33.3%
+24.4
Total goals
Over 1.5
83.2%
1.20
1.24 Betano
80.6%
+2.6
Total goals
Under 1.5
16.8%
5.96
4.33 Bet365
23.1%
-6.3
Total goals
Over 2.5
61.8%
1.62
1.73 Bet365
57.8%
+4.0
Total goals
Under 2.5
38.2%
2.62
2.18 Betano
45.9%
-7.7
Total goals
Over 3.5
39.5%
2.53
2.88 Betfair
34.7%
+4.8
Total goals
Under 3.5
60.5%
1.65
1.50 Betano
66.7%
-6.2
Both teams to score
Both teams to score — Yes
59.8%
1.67
1.62 William Hill
61.7%
-1.9
Both teams to score
Both teams to score — No
40.2%
2.49
2.45 Betfair
40.8%
-0.6
A positive gap means our probability is higher than the price implies. That is information, not a recommendation: a pick is only published where the gap clears our bar after allowing for model error, and those appear above.
Palermo favoured against Pisa
Our model makes Pisa 20% to win this Serie B fixture, with the draw at 22% and Palermo at 58%. The goal projection is 1.14 for Pisa against 2.05 for Palermo — a commanding edge to Palermo on expected output. A combined 3.19 goals points to a high-tempo game with chances at both ends, which puts over 2.5 at 62% and both teams to score at 60%. The single most likely scoreline is 1-1 at 10%, though no individual scoreline is ever likely in absolute terms — that is the nature of a low-scoring sport. This sits in the awkward middle of the distribution, where the model has a view but not a strong one. All figures come from a Dixon–Coles adjusted Poisson model fitted on recent results and expected goals. They are estimates, not forecasts of fact.
Most likely scores
1-1 10%
1-2 10%
0-2 9%
0-1 8%
1-3 7%
This season
Season records for Pisa and Palermo
Pisa
Palermo
11
Played
11
4-4-3
W-D-L
8-3-0
1.45
Pts / game
2.45
1.82
Goals for / game
2.27
1.55
Goals against / game
1.18
73%
Over 2.5
64%
64%
BTTS
82%
18%
Clean sheets
18%
18%
Failed to score
0%
2-2-2
Home record
5-0-0
2-2-1
Away record
3-3-0
D1
Streak
D1
2026/27 league matches only, computed from results on record. Pisa · Palermo
Full-match statistics, per game this season
Produced
Season per-match averages, produced
15.7
Shots
20.0
5.3
Shots on target
6.5
7.0
Corners
3.7
2.29
Cards
0.83
9.6
Fouls
9.8
53
Possession %
47
2.00
xG
2.42
7 matches
sample
6 matches
Conceded
Season per-match averages, conceded
12.4
Shots
11.2
3.4
Shots on target
3.5
5.1
Corners
4.2
1.71
Cards
1.00
11.6
Fouls
12.0
47
Possession %
53
1.11
xG
1.72
7 matches
sample
6 matches
Form comparison
Per-match averages over the last 5 matches (5 in sample), captured when this prediction was published and never recomputed since.
Pisa
Metric
Palermo
1.60
Goals scored
2.40 (better)
1.60
Goals conceded
1.00 (better)
2.41 (better)
Expected goals (xG)
2.30
—
Big chances *
—
4.75
Shots on target
6.40 (better)
14.25
Total shots
18.60 (better)
—
Touches in opp. box *
—
6.00 (better)
Corners
4.00
48.0
Possession %
51.0 (better)
429
Passes
451 (better)
—
Tackles
—
10.00 (better)
Fouls
11.40
1.00 (better)
Offsides
1.40
—
Throw-ins *
—
2.50
Yellow cards
1.40 (better)
0.00
Red cards
0.00
* Big chances, Touches in opp. box, Throw-ins are not supplied by our current data provider (api-football). Rather than estimate them and present the estimate as a measurement, we show nothing.
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