Martfűi LSE vs Csepel: result 1-0 and analysis
NB III - SoutheastSoutheast - 12Kick-off on October 19, 2025 at 11:00 AM (UTC)Martfű LSE Sporttelep, Martfű
Full time
What was the result of Martfűi LSE vs Csepel?
Martfűi LSE won 1-0 on October 19, 2025.
Goalscorers
- 2′640552Martfűi LSE
What is the recent form of both teams?
Over their last 15 matches in all competitions, Martfűi LSE have 5 wins, 1 draw and 9 defeats; Csepel have 6, 2 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 12, 2025 | Monori Se(away) | 0-5 | NB III - Southeast |
| Oct 5, 2025 | Tiszaföldvár(home) | 1-0 | NB III - Southeast |
| Sep 28, 2025 | III. Kerületi TUE(away) | 0-4 | NB III - Southeast |
| Sep 21, 2025 | Hódmezővásárhely(home) | 1-5 | NB III - Southeast |
| Sep 14, 2025 | Dombóvári(home) | 3-3 | Magyar Kupa |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 12, 2025 | Dunaharaszti MTK(home) | 6-1 | NB III - Southeast |
| Oct 5, 2025 | Vasas II(away) | 0-1 | NB III - Southeast |
| Sep 28, 2025 | Szeged-Csanád II(home) | 1-0 | NB III - Southeast |
| Sep 21, 2025 | Dabas(away) | 0-3 | NB III - Southeast |
| Sep 7, 2025 | Békéscsaba II(away) | 2-1 | NB III - Southeast |
How many goals should we expect?
Martfűi LSE score 1.1 and concede 2.4 goals per match over their last 15; Csepel score 1.4 and concede 1.4.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Martfűi LSE | 1.1 | 2.4 | 3 | 7/15 | 13/15 |
| Csepel | 1.4 | 1.4 | 3 | 6/15 | 7/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 8 | Csepel | 15 | 5 | 5 | 5 | 27 | 24 | 20 |
A question about Martfűi LSE vs Csepel?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
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How does Footlab AI compute this prediction?
The model combines both teams' Elo ratings (anchored by competition pool), their recent form weighted by opponent strength, home advantage and a Poisson matrix for scorelines. When bookmakers publish odds for the match, their consensus is built into the calculation: that is what proved most accurate on past matches. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy