Montpellier II vs Tarbes: result 1-2 and analysis
National 2 - Group DRegular Season - 19Kick-off on February 11, 2017 at 05:00 PM (UTC)Stade Bernard Gasset Terrain n°7, Montpellier
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What was the result of Montpellier II vs Tarbes?
Tarbes won 1-2 on February 11, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Montpellier II have 4 wins, 4 draws and 7 defeats; Tarbes have 7, 3 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Feb 4, 2017 | Colomiers(away) | 0-3 | National 2 - Group D |
| Jan 21, 2017 | Toulon(home) | 1-0 | National 2 - Group D |
| Jan 14, 2017 | Marignane(away) | 2-1 | National 2 - Group D |
| Dec 21, 2016 | Le Pontet US(away) | 1-1 | National 2 - Group D |
| Dec 17, 2016 | Stade Montois(home) | 0-0 | National 2 - Group D |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Feb 4, 2017 | Le Pontet US(home) | 2-2 | National 2 - Group D |
| Jan 21, 2017 | Stade Montois(away) | 0-1 | National 2 - Group D |
| Jan 14, 2017 | Rodez(home) | 0-2 | National 2 - Group D |
| Jan 7, 2017 | Hyères(away) | 0-3 | National 2 - Group D |
| Dec 16, 2016 | Martigues(home) | 0-0 | National 2 - Group D |
What does the head-to-head say?
In the last meeting: 1 Montpellier II win, 0 draws, 0 Tarbes wins.
| Date | Score | Competition |
|---|---|---|
| Sep 10, 2016 | Tarbes 1-2 Montpellier II | National 2 - Group D |
Last archived meeting: Tarbes vs Montpellier II on Sep 10, 2016
How many goals should we expect?
Montpellier II score 0.7 and concede 1.4 goals per match over their last 15; Tarbes score 1.3 and concede 1.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Montpellier II | 0.7 | 1.4 | 3 | 5/15 | 6/15 |
| Tarbes | 1.3 | 1.1 | 5 | 5/15 | 7/15 |
Over the last 15 matches in all competitions.
A question about Montpellier II vs Tarbes?
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