Betting 
Palermo
2 – 1
Full time
Mantova
Palermo vs Mantova betting tips
Palermo vs Mantova finished 2-1. Limited historical data available. Strong lean toward Home Over 0.5 based on this side's recent goal averages.
What are the tips for Palermo vs Mantova?
Home to Score
Pick: Home Over 0.5
· Prob 84%
VIP
Won
Away Over/Under 1.5
Pick: Away Under 1.5
· Prob 76%
VIP
Won
Home Over/Under 1.5
Pick: Home Over 1.5
· Prob 64%
VIP
Won
Over/Under 2.5
Pick: Over 2.5
· Odds 1.74
· Prob 57%
VIP
Won
1X2
Pick: Final Time 1
· Odds 1.49
· Prob 57%
VIP
Won
Match insights: form, goals and model lean
Limited historical data available. Strong lean toward Home Over 0.5 based on this side's recent goal averages.
Previous meetings and recent results
Head to head
Palermo recent
1 Mar 2026
Pescara vs Palermo
2-1
21 Feb 2026
Palermo vs Sudtirol
3-0
14 Feb 2026
Palermo vs Entella
3-0
10 Feb 2026
Sampdoria vs Palermo
3-3
7 Feb 2026
Palermo vs Empoli
3-2
30 Jan 2026
Bari vs Palermo
0-3
24 Jan 2026
Modena vs Palermo
0-0
18 Jan 2026
Palermo vs Spezia
1-0
11 Jan 2026
Mantova vs Palermo
1-1
27 Dec 2025
Palermo vs Padova
1-0
Mantova recent
1 Mar 2026
Mantova vs Carrarese
1-1
21 Feb 2026
Mantova vs Sampdoria
2-1
14 Feb 2026
Catanzaro vs Mantova
2-0
10 Feb 2026
Reggiana 1919 vs Mantova
1-0
7 Feb 2026
Mantova vs Bari
2-1
31 Jan 2026
Pescara vs Mantova
2-2
24 Jan 2026
Mantova vs Venezia
2-5
17 Jan 2026
Padova vs Mantova
1-2
11 Jan 2026
Mantova vs Palermo
1-1
27 Dec 2025
Carrarese vs Mantova
0-0
Who will win Palermo vs Mantova?
Frequently asked questions
Who will win Palermo vs Mantova?
Our model currently leans Home Over 0.5 with about 84% confidence. See free and VIP markets below.
What are the odds for Palermo vs Mantova?
Odds appear next to unlocked free tips. VIP odds unlock in the app or after full time.
Where can I see H2H and recent form?
Scroll to Insights and H2H on this page for head-to-head results, recent W/D/L form, and goal averages when enough history is available.
Last updated 28 Oct 2026 06:49 UTC · Insights built from Betting Tips historical predictions · Data quality: insufficient