Kashima vs Mito Hollyhock: result 1-0 and analysis
Friendlies ClubsClub Friendlies 3Kick-off on February 10, 2024 at 05:00 AM (UTC)Kashima Soccer Stadium, Kashima
Full time
What was the result of Kashima vs Mito Hollyhock?
Kashima won 1-0 on February 10, 2024.
Goalscorers
- 21′Y. HiguchiKashima
What is the recent form of both teams?
Over their last 15 matches in all competitions, Kashima have 5 wins, 5 draws and 5 defeats; Mito Hollyhock have 3, 7 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Dec 3, 2023 | Yokohama FC(home) | 2-1 | J1 League |
| Nov 24, 2023 | Kawasaki Frontale(away) | 0-3 | J1 League |
| Nov 11, 2023 | Kashiwa Reysol(home) | 1-1 | J1 League |
| Oct 28, 2023 | Urawa(home) | 0-0 | J1 League |
| Oct 21, 2023 | Vissel Kobe(away) | 1-3 | J1 League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 12, 2023 | Shimizu S-pulse(home) | 1-1 | J2 League |
| Nov 4, 2023 | Jubilo Iwata(away) | 0-5 | J2 League |
| Oct 28, 2023 | Fujieda MYFC(away) | 0-1 | J2 League |
| Oct 22, 2023 | Thespakusatsu Gunma(home) | 1-2 | J2 League |
| Oct 8, 2023 | JEF United Chiba(away) | 1-1 | J2 League |
What does the head-to-head say?
In the last meeting: 0 Kashima wins, 1 draw, 0 Mito Hollyhock wins.
| Date | Score | Competition |
|---|---|---|
| Oct 14, 2015 | Kashima 0-0 Mito Hollyhock | Emperor Cup |
Last archived meeting: Kashima vs Mito Hollyhock on Oct 14, 2015
How many goals should we expect?
Kashima score 1.1 and concede 1.1 goals per match over their last 15; Mito Hollyhock score 1.1 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Kashima | 1.1 | 1.1 | 5 | 8/15 | 8/15 |
| Mito Hollyhock | 1.1 | 1.3 | 4 | 8/15 | 7/15 |
Over the last 15 matches in all competitions.
A question about Kashima vs Mito Hollyhock?
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