RES Roma W vs Sassuolo W: result 0-1 and analysis
Serie A WomenSerie A Women - Round 8Kick-off on December 9, 2017 at 12:30 PM (UTC)
Full time
What was the result of RES Roma W vs Sassuolo W?
Sassuolo W won 0-1 on December 9, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, RES Roma W have 5 wins, 3 draws and 7 defeats; Sassuolo W have 0, 0 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Dec 2, 2017 | Bari Pink W(away) | 0-1 | Serie A Women |
| Nov 18, 2017 | Verona W(home) | 3-0 | Serie A Women |
| Nov 11, 2017 | Empoli W(away) | 4-0 | Serie A Women |
| Nov 4, 2017 | Tavagnacco W(away) | 1-2 | Serie A Women |
| Oct 28, 2017 | Mozzanica W(home) | 0-1 | Serie A Women |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Dec 2, 2017 | Mozzanica W(home) | 1-2 | Serie A Women |
| Nov 18, 2017 | Juventus W(away) | 0-2 | Serie A Women |
| Nov 11, 2017 | Chievo Verona W(home) | 0-1 | Serie A Women |
| Nov 4, 2017 | Ravenna W(away) | 0-2 | Serie A Women |
| Oct 28, 2017 | Fiorentina W(home) | 2-4 | Serie A Women |
How many goals should we expect?
RES Roma W score 1.2 and concede 1.1 goals per match over their last 15; Sassuolo W score 0.6 and concede 2.4.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| RES Roma W | 1.2 | 1.1 | 6 | 4/15 | 9/15 |
| Sassuolo W | 0.6 | 2.4 | 0 | 3/7 | 4/7 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 12 | Sassuolo W | 6 | 0 | 2 | 4 | 5 | 13 | 2 |
A question about RES Roma W vs Sassuolo 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