Africa Cup of Nations 1957

All Games

#	Team	GP	W	T	L	GF	GA	Diff	Pts	Pts/G	W%	ØGF	ØGA
1.	Egypt	2	2	0	0	6	1	+5	6	3.00	100%	3.00	0.50
2.	Sudan	1	0	0	1	1	2	-1	0	0.00	0%	1.00	2.00
3.	Ethiopia	1	0	0	1	0	4	-4	0	0.00	0%	0.00	4.00

Click on any column to sort table
Mouseover percentages (%) to see value odds

Select Season

2023
2021
2019
2017
2015
2013
2012
2010
2008
2006
2004
2000
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
1968
1965
1963
1962
1959
1957

Official Site

Wikipedia

Saturday 16. February 1957

Africa Cup of Nations		1957	Odds 1x2
Egypt	4 - 0	Ethiopia

Sunday 10. February 1957

Sudan	1 - 2	Egypt

More Results

February 1957

Egypt
Ethiopia
Sudan

Select Season

2023
2021
2019
2017
2015
2013
2012
2010
2008
2006
2004
2000
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
1968
1965
1963
1962
1959
1957

Official Site

Wikipedia

Last 6 Games

#	Team	GP	W	T	L	GF	GA	Diff	Pts	Pts/G	W%	ØGF	ØGA
1.	Egypt	2	2	0	0	6	1	+5	6	3.00	100%	3.00	0.50
2.	Sudan	1	0	0	1	1	2	-1	0	0.00	0%	1.00	2.00
3.	Ethiopia	1	0	0	1	0	4	-4	0	0.00	0%	0.00	4.00

Season		Games	1	x	2	¦	1	2	¦	Over 2.5	Under 2.5	Over 1.5	Under 1.5	Home Advantage
2023	Group Stage	36	36.1%	41.7%	22.2%	¦	61.9%	38.1%	¦	41.7%	58.3%	72.2%	27.8%	23.8%
2023	Playoffs	16	43.8%	37.5%	18.8%	¦	56.3%	43.8%	¦	25.0%	75.0%	62.5%	37.5%	12.5%
2021	Group Stage	36	41.7%	27.8%	30.6%	¦	57.7%	42.3%	¦	27.8%	72.2%	47.2%	52.8%	15.4%
2021	Playoffs	16	31.3%	43.8%	25.0%	¦	50.0%	50.0%	¦	31.3%	68.8%	56.3%	43.8%	0.0%
2019	Group Stage	36	41.7%	27.8%	30.6%	¦	57.7%	42.3%	¦	22.2%	77.8%	55.6%	44.4%	15.4%
2019	Playoffs	16	31.3%	31.3%	37.5%	¦	43.8%	56.3%	¦	37.5%	62.5%	56.3%	43.8%	-12.5%
2017	Group Stage	24	37.5%	41.7%	20.8%	¦	64.3%	35.7%	¦	33.3%	66.7%	62.5%	37.5%	28.6%
2017	Playoffs	8	50.0%	25.0%	25.0%	¦	50.0%	50.0%	¦	25.0%	75.0%	62.5%	37.5%	0.0%
2015	Group Stage	24	12.5%	54.2%	33.3%	¦	27.3%	72.7%	¦	20.8%	79.2%	75.0%	25.0%	-45.5%
2015	Playoffs	8	37.5%	37.5%	25.0%	¦	62.5%	37.5%	¦	62.5%	37.5%	75.0%	25.0%	25.0%
2013	Group Stage	24	33.3%	54.2%	12.5%	¦	72.7%	27.3%	¦	33.3%	66.7%	70.8%	29.2%	45.5%
2013	Playoffs	8	37.5%	37.5%	25.0%	¦	62.5%	37.5%	¦	37.5%	62.5%	75.0%	25.0%	25.0%
2012	Group Stage	24	54.2%	12.5%	33.3%	¦	61.9%	38.1%	¦	50.0%	50.0%	70.8%	29.2%	23.8%
2012	Playoffs	8	37.5%	37.5%	25.0%	¦	62.5%	37.5%	¦	25.0%	75.0%	62.5%	37.5%	25.0%
2010	Group Stage	21	47.6%	33.3%	19.0%	¦	71.4%	28.6%	¦	47.6%	52.4%	66.7%	33.3%	42.9%
2010	Playoffs	8	25.0%	37.5%	37.5%	¦	37.5%	62.5%	¦	25.0%	75.0%	37.5%	62.5%	-25.0%
2008	Group Stage	24	54.2%	29.2%	16.7%	¦	76.5%	23.5%	¦	54.2%	45.8%	79.2%	20.8%	52.9%
2008	Playoffs	8	62.5%	12.5%	25.0%	¦	62.5%	37.5%	¦	75.0%	25.0%	75.0%	25.0%	25.0%
2006	Group Stage	24	54.2%	12.5%	33.3%	¦	61.9%	38.1%	¦	41.7%	58.3%	70.8%	29.2%	23.8%
2006	Playoffs	8	25.0%	37.5%	37.5%	¦	50.0%	50.0%	¦	37.5%	62.5%	50.0%	50.0%	0.0%
2004	Group Stage	24	41.7%	29.2%	29.2%	¦	58.8%	41.2%	¦	58.3%	41.7%	83.3%	16.7%	17.6%
2004	Playoffs	8	62.5%	25.0%	12.5%	¦	87.5%	12.5%	¦	62.5%	37.5%	87.5%	12.5%	75.0%
2000	Group Stage	24	33.3%	37.5%	29.2%	¦	53.3%	46.7%	¦	29.2%	70.8%	62.5%	37.5%	6.7%
2000	Playoffs	8	37.5%	37.5%	25.0%	¦	62.5%	37.5%	¦	50.0%	50.0%	75.0%	25.0%	25.0%
1998	Group Stage	24	50.0%	20.8%	29.2%	¦	63.2%	36.8%	¦	58.3%	41.7%	75.0%	25.0%	26.3%
1998	Playoffs	8	12.5%	50.0%	37.5%	¦	25.0%	75.0%	¦	25.0%	75.0%	75.0%	25.0%	-50.0%
1996	Regular Season	29	51.7%	13.8%	34.5%	¦	60.0%	40.0%	¦	51.7%	48.3%	79.3%	20.7%	20.0%
1994	Regular Season	20	65.0%	20.0%	15.0%	¦	82.4%	17.6%	¦	50.0%	50.0%	65.0%	35.0%	64.7%
1992	Regular Season	20	60.0%	30.0%	10.0%	¦	85.7%	14.3%	¦	35.0%	65.0%	50.0%	50.0%	71.4%
1990	Regular Season	16	87.5%	12.5%	0.0%	¦	100.0%	0.0%	¦	25.0%	75.0%	50.0%	50.0%	100.0%
1988	Regular Season	16	37.5%	56.3%	6.3%	¦	87.5%	12.5%	¦	12.5%	87.5%	50.0%	50.0%	75.0%
1986	Regular Season	16	68.8%	25.0%	6.3%	¦	91.7%	8.3%	¦	25.0%	75.0%	50.0%	50.0%	83.3%
1984	Regular Season	16	56.3%	31.3%	12.5%	¦	83.3%	16.7%	¦	56.3%	43.8%	68.8%	31.3%	66.7%
1982	Regular Season	16	56.3%	43.8%	0.0%	¦	100.0%	0.0%	¦	37.5%	62.5%	62.5%	37.5%	100.0%
1980	Regular Season	16	68.8%	31.3%	0.0%	¦	100.0%	0.0%	¦	37.5%	62.5%	56.3%	43.8%	100.0%
1978	Regular Season	16	68.8%	31.3%	0.0%	¦	100.0%	0.0%	¦	43.8%	56.3%	75.0%	25.0%	100.0%
1976	Regular Season	18	61.1%	33.3%	5.6%	¦	91.7%	8.3%	¦	55.6%	44.4%	88.9%	11.1%	83.3%
1974	Regular Season	17	76.5%	17.6%	5.9%	¦	92.9%	7.1%	¦	64.7%	35.3%	88.2%	11.8%	85.7%
1972	Regular Season	16	37.5%	56.3%	6.3%	¦	87.5%	12.5%	¦	37.5%	62.5%	93.8%	6.3%	75.0%
1970	Regular Season	16	62.5%	31.3%	6.3%	¦	92.3%	7.7%	¦	50.0%	50.0%	81.3%	18.8%	84.6%
1968	Regular Season	16	81.3%	12.5%	6.3%	¦	86.7%	13.3%	¦	81.3%	18.8%	81.3%	18.8%	73.3%
1965	Regular Season	8	75.0%	25.0%	0.0%	¦	85.7%	14.3%	¦	75.0%	25.0%	75.0%	25.0%	71.4%
1963	Regular Season	8	62.5%	25.0%	12.5%	¦	83.3%	16.7%	¦	75.0%	25.0%	100.0%	0.0%	66.7%
1962	Regular Season	4	75.0%	25.0%	0.0%	¦	100.0%	0.0%	¦	100.0%	0.0%	100.0%	0.0%	100.0%
1959	Regular Season	3	100.0%	0.0%	0.0%	¦	100.0%	0.0%	¦	66.7%	33.3%	66.7%	33.3%	100.0%
1957	Regular Season	2	50.0%	0.0%	50.0%	¦	50.0%	50.0%	¦	100.0%	0.0%	100.0%	0.0%	0.0%

Click on any column to sort table
Mouseover percentages (%) to see value odds

AnnaBet Power Ratings

Updated 2025-04-03 10:51:48

#	Team	Rating
1.	Egypt	1249
2.	Sudan	1028
3.	Ethiopia	833

Our ratings are currently calculated from games played after 1.1.2000

In football our ratings are similar to World Football Elo Ratings but we have tuned up the formula. For example when goal difference is low or game is tied and we have shots on goal statistics available for the game, we’ll then analyze the shots ratio to have some effect on the ratings. For example if a game was tied 1-1 but home team outshoot away team by 10-2 you might say the home team was the better team despite the result.

In ice hockey the ratings are similar but we have taken account the higher number of goals scored and “home” team (first mentioned team) line change advantage. For example if ice hockey game Sweden – Finland was played at Finland but Sweden had the line change advantage it is then taken account when calculating ratings.

Some examples how ratings are adjusted after each game

In the beginning each team has starting rating of 1000 points. After each game played the sum of points change is 0: if home team gets +20 points then away team gets -20 pts deducted. Amount is always based on the weight/importance of the tournament: in friendlies teams get much less points than in World Cup finals.

Two equal teams meet: winner gets some decent points and loser looses the same amount. Example +20 / -20.
Heavy favorite (much higher rating) wins by few goals: gets only few points because it was very expected result. Your points rises very slowly by beating much poorer teams than you. Example +3 / -3.
Heavy favorite ties a game: favorite loses small amount of points because it was expected that the team should win, the opponent get some points. Example -3 / +3 points.
Heavy favorite loses a game: loses lots of rating points, winner gets lots of points. Example -40 / +40.

Sample Winning Expectancies

Difference in Ratings	Higher Rated	Lower Rated
0	0.500	0.500
10	0.514	0.486
20	0.529	0.471
30	0.543	0.457
40	0.557	0.443
50	0.571	0.429
60	0.585	0.415
70	0.599	0.401
80	0.613	0.387
90	0.627	0.373
100	0.640	0.360
110	0.653	0.347
120	0.666	0.334
130	0.679	0.321
140	0.691	0.309
150	0.703	0.297
160	0.715	0.285
170	0.727	0.273
180	0.738	0.262
190	0.749	0.251
200	0.760	0.240

Table by Eloratings.net

Why are Power Ratings better than winning percentage or league table?

Let’s say we have 2 teams whose performance we are analyzing: Finland and Sweden. Both teams have played 8 games and Finland has 6 wins and 2 losses, Sweden 5 wins and 3 losses. You might say Finland is the better team based on that info? What if Finland has won 4 games against poor teams, 2 against mediocre and lost 2 against better teams. Sweden on the other hand had win 3 games against better teams, 2 against mediocre and then 3 narrow losses against mediocre teams. Putting it that way, you might not believe Finland should be a favorite here after all. Would our Power Ratings tell you the exactly same thing:

Finland starting rating 1000:

1. game 4-0 win against poor team +10 pts (1010)
2. game 3-1 win against poor team +6 pts (1016)
3. game 0-2 loss against better team -10 pts (1006)
4. game 4-3 win against mediocre team +15 pts (1021)
5. game 5-3 win against mediocre team +18 pts (1039)
6. game 3-5 loss against better team -10 pts (1029)
7. game 2-0 win against poor team +6 pts (1035)
8. game 5-2 win against poor team +8 pts (1043)
Current rating 1043

Sweden starting rating 1000:

1. game 3-2 win against better team +25 pts (1025)
2. game 2-3 loss against mediocre team -12 pts (1013)
3. game 4-2 win against better team +30 pts (1043)
4. game 3-0 win against mediocre team +20 pts (1063)
5. game 3-5 loss against mediocre team -15 pts (1048)
6. game 3-4 loss against mediocre team -12 pts (1036)
7. game 4-1 win against better team +35 pts (1071)
8. game 3-1 win against mediocre team +16 pts (1087)
Current rating 1087

These are just rough examples for you to get the idea.

Finland vs Sweden Power Ratings: 1043 – 1087, ratings difference 44 and by looking at the table above you can see that this game should be about Finland 46% winning chance and Sweden 54%. Note that home advantage is usually about 100 points so 46%-54% would be only at neutral venue.

It is not always about how many games you have won but rather which teams and by how many goals that tells more about your true Power. But still remember these are only computer calculated estimations and does not take account real world situations like injuries, weather etc. Also note Power Ratings being much less accurate when teams have a big difference between number of games played and/or quality/diversity of tournaments where they have played.

For example in ice hockey USA and Canada plays only few friendly matches before major tournaments and European teams plays a lots of smaller tournaments - and also playing many games against couple of selected opponents only. Smaller tournaments and friendly matches makes of course smaller changes to Power Ratings than major tournaments but when you play a lot of smaller games it can add up.