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