Honda vs Sagawa Shiga: result 2-2 and analysis
J3 LeagueRegular Season - 25Kick-off on September 15, 2012 at 09:00 AM (UTC)Honda Miyakoda Soccer Stadium, Hamamatsu
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What was the result of Honda vs Sagawa Shiga?
Honda and Sagawa Shiga drew 2-2 on September 15, 2012.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Honda have 7 wins, 1 draw and 7 defeats; Sagawa Shiga have 9, 3 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 11, 2012 | Parceiro Nagano(away) | 0-5 | J3 League |
| Aug 4, 2012 | V-varen Nagasaki(home) | 1-0 | J3 League |
| Jul 29, 2012 | Hoyo Oita(away) | 1-6 | J3 League |
| Jul 21, 2012 | Kanazawa(away) | 1-2 | J3 League |
| Jul 14, 2012 | Honda Lock(home) | 1-1 | J3 League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 8, 2012 | Vissel Kobe(away) | 2-1 | Emperor Cup |
| Aug 12, 2012 | Kanazawa(home) | 0-0 | J3 League |
| Aug 4, 2012 | Honda Lock(away) | 1-1 | J3 League |
| Jul 29, 2012 | FC Ryukyu(home) | 4-3 | J3 League |
| Jul 21, 2012 | Tochigi Uva(away) | 3-2 | J3 League |
What does the head-to-head say?
In the last meeting: 0 Honda wins, 0 draws, 1 Sagawa Shiga win.
| Date | Score | Competition |
|---|---|---|
| Jun 10, 2012 | Sagawa Shiga 4-0 Honda | J3 League |
Last archived meeting: Sagawa Shiga vs Honda on Jun 10, 2012
How many goals should we expect?
Honda score 1.3 and concede 1.6 goals per match over their last 15; Sagawa Shiga score 2.2 and concede 1.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Honda | 1.3 | 1.6 | 6 | 4/15 | 8/15 |
| Sagawa Shiga | 2.2 | 1.1 | 6 | 8/15 | 11/15 |
Over the last 15 matches in all competitions.
A question about Honda vs Sagawa Shiga?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
Sign-in required. No odds displayed, no affiliation: the method is published and the accuracy is measured.
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