09.05.2019 - 18:45
Stadium : Stade Marcel-Verchère
Finished
# | Team | MP | BTTS | BTTS% |
---|---|---|---|---|
1 | Bourg-en-Bresse | 34 | 12 | 35% |
2 | Laval | 34 | 20 | 59% |
3 | Tours | 34 | 9 | 26% |
4 | Quevilly Rouen | 34 | 18 | 53% |
5 | Dunkerque | 34 | 16 | 47% |
6 | Boulogne | 34 | 16 | 47% |
7 | Lyon Duchère | 34 | 21 | 62% |
8 | Chambly | 34 | 15 | 44% |
9 | Concarneau | 34 | 17 | 50% |
10 | Cholet | 34 | 21 | 62% |
11 | Rodez | 34 | 16 | 47% |
12 | Entente SSG | 34 | 19 | 56% |
13 | Avranches | 34 | 15 | 44% |
14 | Pau | 34 | 16 | 47% |
15 | Villefranche | 34 | 20 | 59% |
16 | Drancy JA | 34 | 11 | 32% |
17 | Marignane Gignac | 34 | 16 | 47% |
18 | Le Mans | 34 | 16 | 47% |
# | Team | MP | BTTS | BTTS% |
---|---|---|---|---|
1 | Bourg-en-Bresse | 17 | 7 | 41% |
2 | Laval | 17 | 10 | 59% |
3 | Tours | 17 | 6 | 35% |
4 | Quevilly Rouen | 17 | 8 | 47% |
5 | Dunkerque | 17 | 8 | 47% |
6 | Boulogne | 17 | 7 | 41% |
7 | Lyon Duchère | 17 | 8 | 47% |
8 | Chambly | 17 | 9 | 53% |
9 | Concarneau | 17 | 8 | 47% |
10 | Cholet | 17 | 10 | 59% |
11 | Rodez | 17 | 8 | 47% |
12 | Entente SSG | 17 | 10 | 59% |
13 | Avranches | 17 | 8 | 47% |
14 | Pau | 17 | 7 | 41% |
15 | Villefranche | 17 | 11 | 65% |
16 | Drancy JA | 17 | 5 | 29% |
17 | Marignane Gignac | 17 | 8 | 47% |
18 | Le Mans | 17 | 9 | 53% |
# | Team | MP | BTTS | BTTS% |
---|---|---|---|---|
1 | Bourg-en-Bresse | 17 | 5 | 29% |
2 | Laval | 17 | 10 | 59% |
3 | Tours | 17 | 3 | 18% |
4 | Quevilly Rouen | 17 | 10 | 59% |
5 | Dunkerque | 17 | 8 | 47% |
6 | Boulogne | 17 | 9 | 53% |
7 | Lyon Duchère | 17 | 13 | 76% |
8 | Chambly | 17 | 6 | 35% |
9 | Concarneau | 17 | 9 | 53% |
10 | Cholet | 17 | 11 | 65% |
11 | Rodez | 17 | 8 | 47% |
12 | Entente SSG | 17 | 9 | 53% |
13 | Avranches | 17 | 7 | 41% |
14 | Pau | 17 | 9 | 53% |
15 | Villefranche | 17 | 9 | 53% |
16 | Drancy JA | 17 | 6 | 35% |
17 | Marignane Gignac | 17 | 8 | 47% |
18 | Le Mans | 17 | 7 | 41% |
This section shows the statistics on how many times Bourg-en-Bresse and Boulogne have both scored and conceded in the same match in the National.
The “Both Teams to Score” stat is a good data point to use for seeing whether or not a match will feature many (or any) goals. If both teams have a high rate of both scoring and conceding goals, then there is a good chance that a couple of goals will go in. But if one or both teams have low BTTS rates, then their match could be a lower-scoring affair.
Check out the BTTS (both teams to score) stats for the match:
It’s important to consider BTTS statistics when analysing teams as they provide insight into the teams’ overall approach and performance in matches. Teams with a high percentage of both teams scoring usually have more attacking approaches, whilst a lower rate of both teams scoring could point to a slightly more conservative gameplan for the most part.
And of course, this information should prove quite valuable when picking bets on the “Both Teams to Score” market and other goal-related markets
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