Kaposvar vs Majosi: result 1-0 and analysis
NB III - SouthwestSouthwest - 9Kick-off on October 1, 2023 at 01:00 PM (UTC)Rákóczi Stadion, Kaposvár
Full time
What was the result of Kaposvar vs Majosi?
Kaposvar won 1-0 on October 1, 2023.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Kaposvar have 5 wins, 6 draws and 4 defeats; Majosi have 5, 1 and 9.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 24, 2023 | Ferencváros II(away) | 0-1 | NB III - Southwest |
| Sep 17, 2023 | PTE-PEAC(away) | 2-0 | Magyar Kupa |
| Sep 9, 2023 | Szekszárd(home) | 2-0 | NB III - Southwest |
| Sep 3, 2023 | Paksi SE II(away) | 4-1 | NB III - Southwest |
| Aug 30, 2023 | Nagykanizsai ULE(home) | 0-0 | NB III - Southwest |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 24, 2023 | Mohácsi TE(home) | 1-3 | NB III - Southwest |
| Sep 17, 2023 | Kelen(away) | 0-1 | Magyar Kupa |
| Sep 9, 2023 | Dunaújváros-Pálhalma(away) | 0-1 | NB III - Southwest |
| Sep 3, 2023 | Iváncsa(home) | 2-3 | NB III - Southwest |
| Aug 30, 2023 | MTK Budapest II(away) | 1-1 | NB III - Southwest |
How many goals should we expect?
Kaposvar score 1.1 and concede 1.2 goals per match over their last 15; Majosi score 1.4 and concede 1.8.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Kaposvar | 1.1 | 1.2 | 7 | 6/15 | 5/15 |
| Majosi | 1.4 | 1.8 | 2 | 10/15 | 9/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
Kaposvar sit 2nd in NB III - Southwest (25 points from 12 matches) and Majosi sit 5th (21 points from 12 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 2 | Kaposvar | 12 | 8 | 1 | 3 | 35 | 17 | 25 |
| 5 | Majosi | 12 | 6 | 3 | 3 | 26 | 24 | 21 |
A question about Kaposvar vs Majosi?
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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