Caxias vs Ipatinga: result 1-2 and analysis
Serie CRegular Season - 11Kick-off on August 24, 2013 at 10:00 PM (UTC)Estádio Francisco Stédile, Caxias do Sul, Rio Grande do Sul
Full time
What was the result of Caxias vs Ipatinga?
Ipatinga won 1-2 on August 24, 2013.
Goalscorers
- 7′WescleyIpatinga
- 29′M. TrípodiCaxias
- 55′CristianoIpatinga
What is the recent form of both teams?
Over their last 15 matches in all competitions, Caxias have 7 wins, 5 draws and 3 defeats; Ipatinga have 4, 3 and 8.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 17, 2013 | Macaé(away) | 0-2 | Serie C |
| Aug 10, 2013 | Duque de Caxias(home) | 0-0 | Serie C |
| Aug 7, 2013 | Grêmio Barueri(away) | 2-0 | Serie C |
| Aug 4, 2013 | Vila Nova(away) | 0-4 | Serie C |
| Jul 28, 2013 | Madureira(home) | 0-0 | Serie C |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 18, 2013 | CRAC(home) | 3-2 | Serie C |
| Aug 10, 2013 | Mogi Mirim(away) | 0-2 | Serie C |
| Aug 7, 2013 | Madureira(home) | 1-0 | Serie C |
| Aug 3, 2013 | Guarani Campinas(home) | 0-1 | Serie C |
| Jul 28, 2013 | Vila Nova(away) | 0-0 | Serie C |
What does the head-to-head say?
In the last meeting: 1 Caxias win, 0 draws, 0 Ipatinga wins.
| Date | Score | Competition |
|---|---|---|
| Jun 8, 2013 | Ipatinga 0-1 Caxias | Serie C |
How many goals should we expect?
Caxias score 0.9 and concede 0.7 goals per match over their last 15; Ipatinga score 1.0 and concede 1.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Caxias | 0.9 | 0.7 | 10 | 3/15 | 4/15 |
| Ipatinga | 1.0 | 1.5 | 4 | 6/15 | 7/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 14 | Caxias | 19 | 6 | 7 | 6 | 17 | 16 | 25 |
A question about Caxias vs Ipatinga?
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