Bulgaria · Second PFL · Sat 25 Oct 2025 13:00 UTC · All tips 25 Oct

Belasitsa Petrich Belasitsa Petrich
0 – 1
Full time
Marek Dupnitsa Marek Dupnitsa

Belasitsa Petrich vs Marek Dupnitsa betting tips

Belasitsa Petrich vs Marek Dupnitsa finished 0-1. Moderate historical data available. Strong lean toward Under 3.5 based on recent scoring patterns.

What are the tips for Belasitsa Petrich vs Marek Dupnitsa?

Over/Under 3.5
Pick: Under 3.5 · Odds 1.14 · Prob 74%
VIP Won
Away to Score
Pick: Away Over 0.5 · Prob 71%
VIP Won
Home Over/Under 1.5
Pick: Home Under 1.5 · Prob 67%
VIP Won
Over/Under 2.5
Pick: Under 2.5 · Odds 1.52 · Prob 60%
VIP Won
Both Teams To Score
Pick: BTTS No · Odds 1.68 · Prob 57%
VIP Won
1X2
Pick: Final Time 2 · Odds 1.97 · Prob 48%
VIP Won

Match insights: form, goals and model lean

Model lean

Under 3.5 74% Other 26%

Head to head (4)

1Belasitsa Petrich
1Draws
2Marek Dupnitsa

Recent form

Belasitsa Petrich
L L L D L L D L D L
3 pts / 10
Marek Dupnitsa
D D D L L D W D L W
11 pts / 10

Goals (avg last matches)

0.3 / 1.8 Belasitsa Petrich scored / conceded
0.8 / 0.8 Marek Dupnitsa scored / conceded

Tip analysis

Moderate historical data available. Strong lean toward Under 3.5 based on recent scoring patterns.

Previous meetings and recent results

Who will win Belasitsa Petrich vs Marek Dupnitsa?

45 community votes

42% Belasitsa Petrich
18% Draw
40% Marek Dupnitsa

Voting closed

Frequently asked questions

Who will win Belasitsa Petrich vs Marek Dupnitsa?

Our model currently leans Under 3.5 with about 74% confidence. See free and VIP markets below.

What are the odds for Belasitsa Petrich vs Marek Dupnitsa?

The featured free market shows odds around 1.14 (decimal). Switch odds format in the header if you prefer American or Fractional.

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 8 Nov 2026 23:04 UTC · Insights built from Betting Tips historical predictions · Data quality: thin