# | Team | MP | BTTS | BTTS% |
---|---|---|---|---|
1 |
![]() Ivory Coast |
4 | 1 | 25% |
2 |
![]() Ghana |
3 | 3 | 100% |
3 |
![]() Nigeria |
5 | 1 | 20% |
4 |
![]() Cameroon |
4 | 3 | 75% |
5 |
![]() Algeria |
3 | 2 | 67% |
6 |
![]() Senegal |
4 | 2 | 50% |
7 |
![]() South Africa |
4 | 0 | 0% |
8 |
![]() Guinea |
5 | 2 | 40% |
9 |
![]() Angola |
5 | 2 | 40% |
10 |
![]() Burkina |
4 | 2 | 50% |
11 |
![]() Tanzania |
3 | 1 | 33% |
12 |
![]() Morocco |
4 | 1 | 25% |
13 |
![]() Egypt |
4 | 4 | 100% |
14 |
![]() Tunisia |
3 | 1 | 33% |
15 |
![]() Mauritania |
4 | 1 | 25% |
16 |
![]() Namibia |
4 | 0 | 0% |
17 |
![]() Mali |
4 | 2 | 50% |
18 |
![]() Equatorial Guinea |
4 | 2 | 50% |
19 |
![]() Zambia |
3 | 2 | 67% |
20 |
![]() Gambia |
3 | 1 | 33% |
21 |
![]() Congo DR |
5 | 4 | 80% |
22 |
![]() Cape Verde Islands |
4 | 2 | 50% |
23 |
![]() Guinea-Bissau |
3 | 1 | 33% |
24 |
![]() Mozambique |
3 | 2 | 67% |
25 |
![]() 3rd Group A/C/D |
0 | 0 | 0% |
26 |
![]() 2nd Group F |
0 | 0 | 0% |
27 |
![]() 3rd Group C/D/E |
0 | 0 | 0% |
28 |
![]() 3rd Group A/B/F |
0 | 0 | 0% |
# | Team | MP | BTTS | BTTS% |
---|---|---|---|---|
1 |
![]() Ivory Coast |
2 | 0 | 0% |
2 |
![]() Ghana |
1 | 1 | 100% |
3 |
![]() Nigeria |
3 | 1 | 33% |
4 |
![]() Cameroon |
1 | 1 | 100% |
5 |
![]() Algeria |
2 | 2 | 100% |
6 |
![]() Senegal |
3 | 2 | 67% |
7 |
![]() South Africa |
2 | 0 | 0% |
8 |
![]() Guinea |
2 | 0 | 0% |
9 |
![]() Angola |
2 | 0 | 0% |
10 |
![]() Burkina |
1 | 0 | 0% |
11 |
![]() Tanzania |
1 | 0 | 0% |
12 |
![]() Morocco |
3 | 1 | 33% |
13 |
![]() Egypt |
3 | 3 | 100% |
14 |
![]() Tunisia |
2 | 1 | 50% |
15 |
![]() Mauritania |
2 | 1 | 50% |
16 |
![]() Namibia |
1 | 0 | 0% |
17 |
![]() Mali |
2 | 1 | 50% |
18 |
![]() Equatorial Guinea |
3 | 1 | 33% |
19 |
![]() Zambia |
2 | 1 | 50% |
20 |
![]() Gambia |
1 | 1 | 100% |
21 |
![]() Congo DR |
2 | 2 | 100% |
22 |
![]() Cape Verde Islands |
3 | 1 | 33% |
23 |
![]() Guinea-Bissau |
1 | 0 | 0% |
24 |
![]() Mozambique |
1 | 1 | 100% |
25 |
![]() 3rd Group A/C/D |
0 | 0 | 0% |
26 |
![]() 2nd Group F |
0 | 0 | 0% |
27 |
![]() 3rd Group C/D/E |
0 | 0 | 0% |
28 |
![]() 3rd Group A/B/F |
0 | 0 | 0% |
# | Team | MP | BTTS | BTTS% |
---|---|---|---|---|
1 |
![]() Ivory Coast |
2 | 1 | 50% |
2 |
![]() Ghana |
2 | 2 | 100% |
3 |
![]() Nigeria |
2 | 0 | 0% |
4 |
![]() Cameroon |
3 | 2 | 67% |
5 |
![]() Algeria |
1 | 0 | 0% |
6 |
![]() Senegal |
1 | 0 | 0% |
7 |
![]() South Africa |
2 | 0 | 0% |
8 |
![]() Guinea |
3 | 2 | 67% |
9 |
![]() Angola |
3 | 2 | 67% |
10 |
![]() Burkina |
3 | 2 | 67% |
11 |
![]() Tanzania |
2 | 1 | 50% |
12 |
![]() Morocco |
1 | 0 | 0% |
13 |
![]() Egypt |
1 | 1 | 100% |
14 |
![]() Tunisia |
1 | 0 | 0% |
15 |
![]() Mauritania |
2 | 0 | 0% |
16 |
![]() Namibia |
3 | 0 | 0% |
17 |
![]() Mali |
2 | 1 | 50% |
18 |
![]() Equatorial Guinea |
1 | 1 | 100% |
19 |
![]() Zambia |
1 | 1 | 100% |
20 |
![]() Gambia |
2 | 0 | 0% |
21 |
![]() Congo DR |
3 | 2 | 67% |
22 |
![]() Cape Verde Islands |
1 | 1 | 100% |
23 |
![]() Guinea-Bissau |
2 | 1 | 50% |
24 |
![]() Mozambique |
2 | 1 | 50% |
25 |
![]() 3rd Group A/C/D |
0 | 0 | 0% |
26 |
![]() 2nd Group F |
0 | 0 | 0% |
27 |
![]() 3rd Group C/D/E |
0 | 0 | 0% |
28 |
![]() 3rd Group A/B/F |
0 | 0 | 0% |
This section shows the statistics on how many times Equatorial Guinea and Guinea-Bissau have both scored and conceded in the same match in the Africa Cup of Nations.
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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