Issy W vs Juvisy Sur Orge W: result 1-5 and analysis
Feminine Division 1Feminine Division 1 - Round 12Kick-off on December 7, 2014 at 01:30 PM (UTC)
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What was the result of Issy W vs Juvisy Sur Orge W?
Juvisy Sur Orge W won 1-5 on December 7, 2014.
What is the recent form of both teams?
Over their last 11 matches in all competitions, Issy W have 1 win, 2 draws and 8 defeats; Juvisy Sur Orge W have 12, 1 and 2.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 30, 2014 | Metz W(away) | 1-1 | Feminine Division 1 |
| Nov 16, 2014 | Guingamp W(home) | 0-4 | Feminine Division 1 |
| Nov 9, 2014 | Arras W(away) | 1-3 | Feminine Division 1 |
| Nov 2, 2014 | Rodez W(home) | 2-3 | Feminine Division 1 |
| Oct 19, 2014 | AS Saint-Etienne W(away) | 2-1 | Feminine Division 1 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 16, 2014 | Metz W(home) | 4-0 | Feminine Division 1 |
| Nov 9, 2014 | Guingamp W(away) | 6-1 | Feminine Division 1 |
| Nov 2, 2014 | Arras W(home) | 4-0 | Feminine Division 1 |
| Oct 18, 2014 | Rodez W(away) | 1-0 | Feminine Division 1 |
| Oct 11, 2014 | AS Saint-Etienne W(home) | 3-0 | Feminine Division 1 |
What does the head-to-head say?
In the last meeting: 0 Issy W wins, 0 draws, 1 Juvisy Sur Orge W win.
| Date | Score | Competition |
|---|---|---|
| Sep 7, 2014 | Juvisy Sur Orge W 3-1 Issy W | Feminine Division 1 |
Last archived meeting: Juvisy Sur Orge W vs Issy W on Sep 7, 2014
How many goals should we expect?
Issy W score 0.7 and concede 2.5 goals per match over their last 11; Juvisy Sur Orge W score 3.5 and concede 0.8.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Issy W | 0.7 | 2.5 | 1 | 6/11 | 7/11 |
| Juvisy Sur Orge W | 3.5 | 0.8 | 9 | 5/15 | 13/15 |
Over the last 11 matches in all competitions.
A question about Issy W vs Juvisy Sur Orge W?
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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