# | Team | MP | BTTS | BTTS% |
---|---|---|---|---|
1 |
![]() Ivory Coast |
6 | 2 | 33% |
2 |
![]() Ghana |
8 | 3 | 38% |
3 |
![]() Nigeria |
8 | 3 | 38% |
4 |
![]() Cameroon |
8 | 3 | 38% |
5 |
![]() Algeria |
8 | 4 | 50% |
6 |
![]() Senegal |
8 | 4 | 50% |
7 |
![]() Kenya |
6 | 3 | 50% |
8 |
![]() Central African Republic |
6 | 3 | 50% |
9 |
![]() South Africa |
6 | 1 | 17% |
10 |
![]() Guinea |
6 | 4 | 67% |
11 |
![]() Seychelles |
2 | 0 | 0% |
12 |
![]() Swaziland |
2 | 1 | 50% |
13 |
![]() Uganda |
6 | 1 | 17% |
14 |
![]() Angola |
8 | 4 | 50% |
15 |
![]() Lesotho |
2 | 1 | 50% |
16 |
![]() Libya |
6 | 2 | 33% |
17 |
![]() Botswana |
2 | 0 | 0% |
18 |
![]() Burkina |
6 | 3 | 50% |
19 |
![]() Comoros |
2 | 1 | 50% |
20 |
![]() São Tomé e Príncipe |
2 | 1 | 50% |
21 |
![]() Tanzania |
8 | 5 | 63% |
22 |
![]() Togo |
8 | 4 | 50% |
23 |
![]() Morocco |
8 | 3 | 38% |
24 |
![]() Egypt |
8 | 3 | 38% |
25 |
![]() Tunisia |
8 | 1 | 13% |
26 |
![]() Mauritania |
6 | 2 | 33% |
27 |
![]() Mauritius |
2 | 0 | 0% |
28 |
![]() Namibia |
8 | 5 | 63% |
29 |
![]() Sierra Leone |
2 | 1 | 50% |
30 |
![]() Mali |
8 | 0 | 0% |
31 |
![]() Malawi |
8 | 1 | 13% |
32 |
![]() Madagascar |
6 | 2 | 33% |
33 |
![]() Equatorial Guinea |
8 | 3 | 38% |
34 |
![]() Zambia |
6 | 3 | 50% |
35 |
![]() Zimbabwe |
8 | 3 | 38% |
36 |
![]() Gambia |
2 | 1 | 50% |
37 |
![]() Congo DR |
8 | 4 | 50% |
38 |
![]() Sudan |
8 | 4 | 50% |
39 |
![]() Chad |
2 | 1 | 50% |
40 |
![]() Cape Verde Islands |
6 | 5 | 83% |
41 |
![]() Benin |
6 | 1 | 17% |
42 |
![]() Liberia |
8 | 3 | 38% |
43 |
![]() Niger |
6 | 4 | 67% |
44 |
![]() Djibouti |
8 | 3 | 38% |
45 |
![]() Guinea-Bissau |
8 | 3 | 38% |
46 |
![]() Eritrea |
2 | 1 | 50% |
47 |
![]() Ethiopia |
8 | 4 | 50% |
48 |
![]() Burundi |
2 | 2 | 100% |
49 |
![]() South Sudan |
2 | 1 | 50% |
50 |
![]() Gabon |
6 | 4 | 67% |
# | Team | MP | BTTS | BTTS% |
---|---|---|---|---|
1 |
![]() Ivory Coast |
3 | 2 | 67% |
2 |
![]() Ghana |
4 | 1 | 25% |
3 |
![]() Nigeria |
4 | 2 | 50% |
4 |
![]() Cameroon |
4 | 1 | 25% |
5 |
![]() Algeria |
4 | 3 | 75% |
6 |
![]() Senegal |
4 | 1 | 25% |
7 |
![]() Kenya |
3 | 1 | 33% |
8 |
![]() Central African Republic |
3 | 1 | 33% |
9 |
![]() South Africa |
3 | 0 | 0% |
10 |
![]() Guinea |
3 | 2 | 67% |
11 |
![]() Seychelles |
1 | 0 | 0% |
12 |
![]() Swaziland |
1 | 0 | 0% |
13 |
![]() Uganda |
3 | 1 | 33% |
14 |
![]() Angola |
4 | 3 | 75% |
15 |
![]() Lesotho |
1 | 1 | 100% |
16 |
![]() Libya |
3 | 2 | 67% |
17 |
![]() Botswana |
1 | 0 | 0% |
18 |
![]() Burkina |
3 | 2 | 67% |
19 |
![]() Comoros |
1 | 1 | 100% |
20 |
![]() São Tomé e Príncipe |
1 | 0 | 0% |
21 |
![]() Tanzania |
4 | 2 | 50% |
22 |
![]() Togo |
4 | 2 | 50% |
23 |
![]() Morocco |
4 | 1 | 25% |
24 |
![]() Egypt |
4 | 1 | 25% |
25 |
![]() Tunisia |
4 | 1 | 25% |
26 |
![]() Mauritania |
3 | 2 | 67% |
27 |
![]() Mauritius |
1 | 0 | 0% |
28 |
![]() Namibia |
4 | 2 | 50% |
29 |
![]() Sierra Leone |
1 | 0 | 0% |
30 |
![]() Mali |
4 | 0 | 0% |
31 |
![]() Malawi |
4 | 0 | 0% |
32 |
![]() Madagascar |
3 | 1 | 33% |
33 |
![]() Equatorial Guinea |
4 | 0 | 0% |
34 |
![]() Zambia |
3 | 1 | 33% |
35 |
![]() Zimbabwe |
4 | 2 | 50% |
36 |
![]() Gambia |
1 | 0 | 0% |
37 |
![]() Congo DR |
4 | 2 | 50% |
38 |
![]() Sudan |
4 | 2 | 50% |
39 |
![]() Chad |
1 | 1 | 100% |
40 |
![]() Cape Verde Islands |
3 | 2 | 67% |
41 |
![]() Benin |
3 | 1 | 33% |
42 |
![]() Liberia |
4 | 3 | 75% |
43 |
![]() Niger |
3 | 1 | 33% |
44 |
![]() Djibouti |
4 | 2 | 50% |
45 |
![]() Guinea-Bissau |
4 | 2 | 50% |
46 |
![]() Eritrea |
1 | 1 | 100% |
47 |
![]() Ethiopia |
4 | 2 | 50% |
48 |
![]() Burundi |
1 | 1 | 100% |
49 |
![]() South Sudan |
1 | 1 | 100% |
50 |
![]() Gabon |
3 | 1 | 33% |
# | Team | MP | BTTS | BTTS% |
---|---|---|---|---|
1 |
![]() Ivory Coast |
3 | 0 | 0% |
2 |
![]() Ghana |
4 | 2 | 50% |
3 |
![]() Nigeria |
4 | 1 | 25% |
4 |
![]() Cameroon |
4 | 2 | 50% |
5 |
![]() Algeria |
4 | 1 | 25% |
6 |
![]() Senegal |
4 | 3 | 75% |
7 |
![]() Kenya |
3 | 2 | 67% |
8 |
![]() Central African Republic |
3 | 2 | 67% |
9 |
![]() South Africa |
3 | 1 | 33% |
10 |
![]() Guinea |
3 | 2 | 67% |
11 |
![]() Seychelles |
1 | 0 | 0% |
12 |
![]() Swaziland |
1 | 1 | 100% |
13 |
![]() Uganda |
3 | 0 | 0% |
14 |
![]() Angola |
4 | 1 | 25% |
15 |
![]() Lesotho |
1 | 0 | 0% |
16 |
![]() Libya |
3 | 0 | 0% |
17 |
![]() Botswana |
1 | 0 | 0% |
18 |
![]() Burkina |
3 | 1 | 33% |
19 |
![]() Comoros |
1 | 0 | 0% |
20 |
![]() São Tomé e Príncipe |
1 | 1 | 100% |
21 |
![]() Tanzania |
4 | 3 | 75% |
22 |
![]() Togo |
4 | 2 | 50% |
23 |
![]() Morocco |
4 | 2 | 50% |
24 |
![]() Egypt |
4 | 2 | 50% |
25 |
![]() Tunisia |
4 | 0 | 0% |
26 |
![]() Mauritania |
3 | 0 | 0% |
27 |
![]() Mauritius |
1 | 0 | 0% |
28 |
![]() Namibia |
4 | 3 | 75% |
29 |
![]() Sierra Leone |
1 | 1 | 100% |
30 |
![]() Mali |
4 | 0 | 0% |
31 |
![]() Malawi |
4 | 1 | 25% |
32 |
![]() Madagascar |
3 | 1 | 33% |
33 |
![]() Equatorial Guinea |
4 | 3 | 75% |
34 |
![]() Zambia |
3 | 2 | 67% |
35 |
![]() Zimbabwe |
4 | 1 | 25% |
36 |
![]() Gambia |
1 | 1 | 100% |
37 |
![]() Congo DR |
4 | 2 | 50% |
38 |
![]() Sudan |
4 | 2 | 50% |
39 |
![]() Chad |
1 | 0 | 0% |
40 |
![]() Cape Verde Islands |
3 | 3 | 100% |
41 |
![]() Benin |
3 | 0 | 0% |
42 |
![]() Liberia |
4 | 0 | 0% |
43 |
![]() Niger |
3 | 3 | 100% |
44 |
![]() Djibouti |
4 | 1 | 25% |
45 |
![]() Guinea-Bissau |
4 | 1 | 25% |
46 |
![]() Eritrea |
1 | 0 | 0% |
47 |
![]() Ethiopia |
4 | 2 | 50% |
48 |
![]() Burundi |
1 | 1 | 100% |
49 |
![]() South Sudan |
1 | 0 | 0% |
50 |
![]() Gabon |
3 | 3 | 100% |
This section shows the statistics on how many times Guinea-Bissau and Sudan have both scored and conceded in the same match in the WC Qualification Africa.
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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