# | Team | MP | BTTS | BTTS% |
---|---|---|---|---|
1 | ![]() Tromsø | 30 | 14 | 47% |
2 | ![]() Sogndal | 31 | 17 | 55% |
3 | ![]() Lillestrøm | 30 | 14 | 47% |
4 | ![]() Strømmen | 30 | 21 | 70% |
5 | ![]() Åsane | 32 | 24 | 75% |
6 | ![]() Ullensaker - Kisa IL | 30 | 20 | 67% |
7 | ![]() Ranheim | 32 | 20 | 63% |
8 | ![]() Kongsvinger | 30 | 17 | 57% |
9 | ![]() Jerv | 30 | 18 | 60% |
10 | ![]() Sandnes Ulf | 30 | 21 | 70% |
11 | ![]() HamKam | 30 | 23 | 77% |
12 | ![]() Raufoss | 31 | 20 | 65% |
13 | ![]() KFUM | 30 | 20 | 67% |
14 | ![]() Stjørdals-Blink | 30 | 24 | 80% |
15 | ![]() Grorud | 30 | 22 | 73% |
16 | ![]() Øygarden | 30 | 19 | 63% |
# | Team | MP | BTTS | BTTS% |
---|---|---|---|---|
1 | ![]() Tromsø | 15 | 7 | 47% |
2 | ![]() Sogndal | 16 | 8 | 50% |
3 | ![]() Lillestrøm | 15 | 6 | 40% |
4 | ![]() Strømmen | 15 | 11 | 73% |
5 | ![]() Åsane | 16 | 13 | 81% |
6 | ![]() Ullensaker - Kisa IL | 15 | 7 | 47% |
7 | ![]() Ranheim | 16 | 12 | 75% |
8 | ![]() Kongsvinger | 15 | 9 | 60% |
9 | ![]() Jerv | 15 | 9 | 60% |
10 | ![]() Sandnes Ulf | 15 | 13 | 87% |
11 | ![]() HamKam | 15 | 12 | 80% |
12 | ![]() Raufoss | 15 | 10 | 67% |
13 | ![]() KFUM | 15 | 10 | 67% |
14 | ![]() Stjørdals-Blink | 15 | 12 | 80% |
15 | ![]() Grorud | 15 | 9 | 60% |
16 | ![]() Øygarden | 15 | 9 | 60% |
# | Team | MP | BTTS | BTTS% |
---|---|---|---|---|
1 | ![]() Tromsø | 15 | 7 | 47% |
2 | ![]() Sogndal | 15 | 9 | 60% |
3 | ![]() Lillestrøm | 15 | 8 | 53% |
4 | ![]() Strømmen | 15 | 10 | 67% |
5 | ![]() Åsane | 16 | 11 | 69% |
6 | ![]() Ullensaker - Kisa IL | 15 | 13 | 87% |
7 | ![]() Ranheim | 16 | 8 | 50% |
8 | ![]() Kongsvinger | 15 | 8 | 53% |
9 | ![]() Jerv | 15 | 9 | 60% |
10 | ![]() Sandnes Ulf | 15 | 8 | 53% |
11 | ![]() HamKam | 15 | 11 | 73% |
12 | ![]() Raufoss | 16 | 10 | 63% |
13 | ![]() KFUM | 15 | 10 | 67% |
14 | ![]() Stjørdals-Blink | 15 | 12 | 80% |
15 | ![]() Grorud | 15 | 13 | 87% |
16 | ![]() Øygarden | 15 | 10 | 67% |
This section shows the statistics on how many times Lillestrøm and Ullensaker - Kisa IL have both scored and conceded in the same match in the First Division.
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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