# | Team | MP | BTTS | BTTS% |
---|---|---|---|---|
1 |
![]() South Africa Women |
5 | 1 | 20% |
2 |
![]() Cameroon Women |
1 | 1 | 100% |
3 |
![]() England Women |
2 | 0 | 0% |
4 |
![]() France Women |
4 | 2 | 50% |
5 |
![]() Sweden Women |
4 | 2 | 50% |
6 |
![]() Spain Women |
5 | 1 | 20% |
7 |
![]() Jamaica Women |
1 | 0 | 0% |
8 |
![]() Norway Women |
2 | 2 | 100% |
9 |
![]() Chile Women |
8 | 2 | 25% |
10 |
![]() Scotland Women |
4 | 1 | 25% |
11 |
![]() Argentina Women |
7 | 1 | 14% |
12 |
![]() Australia Women |
5 | 0 | 0% |
13 |
![]() Brazil Women |
7 | 2 | 29% |
14 |
![]() Italy Women |
3 | 1 | 33% |
15 |
![]() Thailand Women |
3 | 1 | 33% |
16 |
![]() Germany Women |
5 | 3 | 60% |
17 |
![]() Netherlands Women |
5 | 2 | 40% |
18 |
![]() Nigeria Women |
5 | 1 | 20% |
19 |
![]() Japan Women |
6 | 2 | 33% |
20 |
![]() China Women |
8 | 4 | 50% |
21 |
![]() Canada Women |
5 | 1 | 20% |
22 |
![]() United States Women |
11 | 1 | 9% |
23 |
![]() New Zealand Women |
13 | 2 | 15% |
24 |
![]() South Korea Women |
3 | 2 | 67% |
25 |
![]() Russia W |
7 | 2 | 29% |
26 |
![]() Bosnia-Herzegovina W |
5 | 1 | 20% |
27 |
![]() Singapore W |
3 | 0 | 0% |
28 |
![]() Taiwan W |
2 | 0 | 0% |
29 |
![]() Iran W |
2 | 0 | 0% |
30 |
![]() Lebanon W |
6 | 3 | 50% |
31 |
![]() India W |
5 | 3 | 60% |
32 |
![]() Nepal W |
4 | 2 | 50% |
33 |
![]() Hong Kong W |
1 | 0 | 0% |
34 |
![]() Bangladesh W |
4 | 1 | 25% |
35 |
![]() Jordan W |
2 | 1 | 50% |
36 |
![]() Indonesia W |
2 | 1 | 50% |
37 |
![]() Palestine W |
2 | 1 | 50% |
38 |
![]() Vietnam Women |
3 | 1 | 33% |
39 |
![]() Uzbekistan W |
3 | 3 | 100% |
40 |
![]() Slovakia W |
5 | 0 | 0% |
41 |
![]() Belgium W |
3 | 2 | 67% |
42 |
![]() Kosovo W |
4 | 0 | 0% |
43 |
![]() Croatia W |
2 | 2 | 100% |
44 |
![]() Denmark Women |
3 | 0 | 0% |
45 |
![]() Czech Republic W |
4 | 0 | 0% |
46 |
![]() Estonia W |
4 | 2 | 50% |
47 |
![]() Finland W |
4 | 2 | 50% |
48 |
![]() Faroe Islands W |
2 | 2 | 100% |
49 |
![]() North Macedonia W |
3 | 2 | 67% |
50 |
![]() Turkey W |
4 | 1 | 25% |
This section shows the statistics on how many times Latvia W and Azerbaijan W have both scored and conceded in the same match in the International Friendlies Women.
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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