Australia vs Japan: result 0-1 and analysis
Asian CupFinalKick-off on January 29, 2011 at 03:00 PM (UTC)CommBank Stadium, Sydney
Full time
What was the result of Australia vs Japan?
Japan won 0-1 on January 29, 2011.
Goalscorers
- 109′T. LeeJapan
Official lineup for Australia vs Japan
The starting elevens fielded at kick-off.
Australia
- 3D. Carney
- 4T. Cahill
- 10Harry Kewell
- 14B. Holman
- 15M. Jedinak
- 16C. Valeri
- 17M. McKay
- 6S. Ognenovski
- 2Lucas Neill
- 8L. Wilkshire
- 1Mark Schwarzer
Japan
- 9S. Okazaki
- 11Ryoichi Maeda
- 7Y. Endō
- 14Jungo Fujimoto
- 18Keisuke Honda
- 4Y. Konno
- 5Y. Nagatomo
- 6Atsuto Uchida
- 17M. Hasebe
- 22M. Yoshida
- 1E. Kawashima
What is the recent form of both teams?
Over their last 8 matches in all competitions, Australia have 5 wins, 2 draws and 1 defeat; Japan have 5, 3 and 1.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jan 25, 2011 | Uzbekistan(away) | 6-0 | Asian Cup |
| Jan 22, 2011 | Iraq(home) | 1-0 | Asian Cup |
| Jan 18, 2011 | Bahrain(home) | 1-0 | Asian Cup |
| Jan 14, 2011 | South Korea(home) | 1-1 | Asian Cup |
| Jan 10, 2011 | India(away) | 4-0 | Asian Cup |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jan 25, 2011 | South Korea(home) | 3-3 | Asian Cup |
| Jan 21, 2011 | Qatar(home) | 3-2 | Asian Cup |
| Jan 17, 2011 | Saudi Arabia(away) | 5-0 | Asian Cup |
| Jan 13, 2011 | Syria(away) | 2-1 | Asian Cup |
| Jan 9, 2011 | Jordan(home) | 1-1 | Asian Cup |
How many goals should we expect?
Australia score 2.0 and concede 0.9 goals per match over their last 8; Japan score 2.0 and concede 1.0.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Australia | 2.0 | 0.9 | 4 | 3/8 | 4/8 |
| Japan | 2.0 | 1.0 | 3 | 5/9 | 5/9 |
Over the last 8 matches in all competitions.
A question about Australia vs Japan?
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