# | Team | MP | BTTS | BTTS% |
---|---|---|---|---|
1 |
![]() Ivory Coast |
7 | 0 | 0% |
2 |
![]() Ghana |
7 | 3 | 43% |
3 |
![]() Nigeria |
6 | 5 | 83% |
4 |
![]() Cameroon |
7 | 4 | 57% |
5 |
![]() Algeria |
7 | 6 | 86% |
6 |
![]() Senegal |
7 | 1 | 14% |
7 |
![]() Kenya |
7 | 5 | 71% |
8 |
![]() Central African Republic |
7 | 4 | 57% |
9 |
![]() South Africa |
7 | 3 | 43% |
10 |
![]() Guinea |
7 | 2 | 29% |
11 |
![]() Seychelles |
7 | 2 | 29% |
12 |
![]() Swaziland |
7 | 2 | 29% |
13 |
![]() Uganda |
7 | 3 | 43% |
14 |
![]() Angola |
7 | 3 | 43% |
15 |
![]() Lesotho |
7 | 2 | 29% |
16 |
![]() Libya |
7 | 4 | 57% |
17 |
![]() Botswana |
7 | 4 | 57% |
18 |
![]() Burkina |
7 | 5 | 71% |
19 |
![]() Comoros |
7 | 2 | 29% |
20 |
![]() São Tomé e Príncipe |
7 | 3 | 43% |
21 |
![]() Tanzania |
5 | 0 | 0% |
22 |
![]() Togo |
7 | 3 | 43% |
23 |
![]() Morocco |
6 | 2 | 33% |
24 |
![]() Egypt |
7 | 2 | 29% |
25 |
![]() Tunisia |
7 | 0 | 0% |
26 |
![]() Mauritania |
7 | 1 | 14% |
27 |
![]() Mauritius |
7 | 3 | 43% |
28 |
![]() Namibia |
7 | 3 | 43% |
29 |
![]() Sierra Leone |
7 | 4 | 57% |
30 |
![]() Mali |
7 | 3 | 43% |
31 |
![]() Malawi |
7 | 2 | 29% |
32 |
![]() Madagascar |
7 | 2 | 29% |
33 |
![]() Equatorial Guinea |
7 | 2 | 29% |
34 |
![]() Zambia |
5 | 3 | 60% |
35 |
![]() Zimbabwe |
7 | 4 | 57% |
36 |
![]() Gambia |
7 | 5 | 71% |
37 |
![]() Congo DR |
7 | 2 | 29% |
38 |
![]() Sudan |
7 | 2 | 29% |
39 |
![]() Chad |
7 | 2 | 29% |
40 |
![]() Cape Verde Islands |
7 | 2 | 29% |
41 |
![]() Benin |
7 | 3 | 43% |
42 |
![]() Liberia |
7 | 2 | 29% |
43 |
![]() Niger |
5 | 2 | 40% |
44 |
![]() Djibouti |
7 | 4 | 57% |
45 |
![]() Guinea-Bissau |
7 | 5 | 71% |
46 |
![]() Eritrea |
0 | 0 | 0% |
47 |
![]() Ethiopia |
7 | 2 | 29% |
48 |
![]() Burundi |
7 | 4 | 57% |
49 |
![]() South Sudan |
7 | 3 | 43% |
50 |
![]() Gabon |
7 | 4 | 57% |
# | Team | MP | BTTS | BTTS% |
---|---|---|---|---|
1 |
![]() Ivory Coast |
4 | 0 | 0% |
2 |
![]() Ghana |
3 | 1 | 33% |
3 |
![]() Nigeria |
3 | 3 | 100% |
4 |
![]() Cameroon |
4 | 2 | 50% |
5 |
![]() Algeria |
4 | 4 | 100% |
6 |
![]() Senegal |
4 | 1 | 25% |
7 |
![]() Kenya |
4 | 3 | 75% |
8 |
![]() Central African Republic |
3 | 1 | 33% |
9 |
![]() South Africa |
3 | 2 | 67% |
10 |
![]() Guinea |
3 | 1 | 33% |
11 |
![]() Seychelles |
3 | 1 | 33% |
12 |
![]() Swaziland |
4 | 1 | 25% |
13 |
![]() Uganda |
4 | 1 | 25% |
14 |
![]() Angola |
4 | 2 | 50% |
15 |
![]() Lesotho |
3 | 0 | 0% |
16 |
![]() Libya |
3 | 3 | 100% |
17 |
![]() Botswana |
4 | 2 | 50% |
18 |
![]() Burkina |
3 | 3 | 100% |
19 |
![]() Comoros |
4 | 1 | 25% |
20 |
![]() São Tomé e Príncipe |
3 | 1 | 33% |
21 |
![]() Tanzania |
2 | 0 | 0% |
22 |
![]() Togo |
3 | 2 | 67% |
23 |
![]() Morocco |
3 | 1 | 33% |
24 |
![]() Egypt |
4 | 1 | 25% |
25 |
![]() Tunisia |
4 | 0 | 0% |
26 |
![]() Mauritania |
4 | 0 | 0% |
27 |
![]() Mauritius |
3 | 1 | 33% |
28 |
![]() Namibia |
4 | 3 | 75% |
29 |
![]() Sierra Leone |
3 | 2 | 67% |
30 |
![]() Mali |
4 | 3 | 75% |
31 |
![]() Malawi |
3 | 1 | 33% |
32 |
![]() Madagascar |
4 | 1 | 25% |
33 |
![]() Equatorial Guinea |
3 | 0 | 0% |
34 |
![]() Zambia |
2 | 1 | 50% |
35 |
![]() Zimbabwe |
3 | 2 | 67% |
36 |
![]() Gambia |
3 | 2 | 67% |
37 |
![]() Congo DR |
3 | 0 | 0% |
38 |
![]() Sudan |
4 | 2 | 50% |
39 |
![]() Chad |
3 | 1 | 33% |
40 |
![]() Cape Verde Islands |
3 | 0 | 0% |
41 |
![]() Benin |
4 | 1 | 25% |
42 |
![]() Liberia |
4 | 1 | 25% |
43 |
![]() Niger |
3 | 2 | 67% |
44 |
![]() Djibouti |
3 | 1 | 33% |
45 |
![]() Guinea-Bissau |
4 | 3 | 75% |
46 |
![]() Eritrea |
0 | 0 | 0% |
47 |
![]() Ethiopia |
4 | 1 | 25% |
48 |
![]() Burundi |
4 | 2 | 50% |
49 |
![]() South Sudan |
3 | 1 | 33% |
50 |
![]() Gabon |
3 | 2 | 67% |
# | Team | MP | BTTS | BTTS% |
---|---|---|---|---|
1 |
![]() Ivory Coast |
3 | 0 | 0% |
2 |
![]() Ghana |
4 | 2 | 50% |
3 |
![]() Nigeria |
3 | 2 | 67% |
4 |
![]() Cameroon |
3 | 2 | 67% |
5 |
![]() Algeria |
3 | 2 | 67% |
6 |
![]() Senegal |
3 | 0 | 0% |
7 |
![]() Kenya |
3 | 2 | 67% |
8 |
![]() Central African Republic |
4 | 3 | 75% |
9 |
![]() South Africa |
4 | 1 | 25% |
10 |
![]() Guinea |
4 | 1 | 25% |
11 |
![]() Seychelles |
4 | 1 | 25% |
12 |
![]() Swaziland |
3 | 1 | 33% |
13 |
![]() Uganda |
3 | 2 | 67% |
14 |
![]() Angola |
3 | 1 | 33% |
15 |
![]() Lesotho |
4 | 2 | 50% |
16 |
![]() Libya |
4 | 1 | 25% |
17 |
![]() Botswana |
3 | 2 | 67% |
18 |
![]() Burkina |
4 | 2 | 50% |
19 |
![]() Comoros |
3 | 1 | 33% |
20 |
![]() São Tomé e Príncipe |
4 | 2 | 50% |
21 |
![]() Tanzania |
3 | 0 | 0% |
22 |
![]() Togo |
4 | 1 | 25% |
23 |
![]() Morocco |
3 | 1 | 33% |
24 |
![]() Egypt |
3 | 1 | 33% |
25 |
![]() Tunisia |
3 | 0 | 0% |
26 |
![]() Mauritania |
3 | 1 | 33% |
27 |
![]() Mauritius |
4 | 2 | 50% |
28 |
![]() Namibia |
3 | 0 | 0% |
29 |
![]() Sierra Leone |
4 | 2 | 50% |
30 |
![]() Mali |
3 | 0 | 0% |
31 |
![]() Malawi |
4 | 1 | 25% |
32 |
![]() Madagascar |
3 | 1 | 33% |
33 |
![]() Equatorial Guinea |
4 | 2 | 50% |
34 |
![]() Zambia |
3 | 2 | 67% |
35 |
![]() Zimbabwe |
4 | 2 | 50% |
36 |
![]() Gambia |
4 | 3 | 75% |
37 |
![]() Congo DR |
4 | 2 | 50% |
38 |
![]() Sudan |
3 | 0 | 0% |
39 |
![]() Chad |
4 | 1 | 25% |
40 |
![]() Cape Verde Islands |
4 | 2 | 50% |
41 |
![]() Benin |
3 | 2 | 67% |
42 |
![]() Liberia |
3 | 1 | 33% |
43 |
![]() Niger |
2 | 0 | 0% |
44 |
![]() Djibouti |
4 | 3 | 75% |
45 |
![]() Guinea-Bissau |
3 | 2 | 67% |
46 |
![]() Eritrea |
0 | 0 | 0% |
47 |
![]() Ethiopia |
3 | 1 | 33% |
48 |
![]() Burundi |
3 | 2 | 67% |
49 |
![]() South Sudan |
4 | 2 | 50% |
50 |
![]() Gabon |
4 | 2 | 50% |
This section shows the statistics on how many times São Tomé e Príncipe and Namibia 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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