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  Kirin Cup 1995

# Equipo PJ PG PE PP GF GC DG PT Pts/G PG% ØGF ØGC
1. Japón 2 1 1 0 3 0 +3 4 2.00 50% 1.50 0.00
2. Escocia 2 1 1 0 2 1 +1 4 2.00 50% 1.00 0.50
3. Ecuador 2 0 0 2 1 5 -4 0 0.00 0% 0.50 2.50


Haga clic en cualquier columna para ordenar la tabla
Porcentajes mouseover (%) para ver las probabilidades de valor

Seleccione una temporada


2022
2016
2015
2013
2012
2011
2009
2000-2001
1999-2000
1998-1999
1997-1998
1996
1995
1994
1993
1992


Wikipedia

Domingo 28. mayo 1995
   
Kirin Cup1995 Cuotas 1x2
Japón    3 - 0    Ecuador
   
Miércoles 24. mayo 1995
   
Escocia    2 - 1    Ecuador
   
Domingo 21. mayo 1995
   
Japón    0 - 0    Escocia

Más resultados


mayo 1995

Ecuador
Escocia
Japón


Seleccione una temporada


2022
2016
2015
2013
2012
2011
2009
2000-2001
1999-2000
1998-1999
1997-1998
1996
1995
1994
1993
1992


Wikipedia

# Equipo PJ PG PE PP GF GC DG PT Pts/G PG% ØGF ØGC
1. Japón 2 1 1 0 3 0 +3 4 2.00 50% 1.50 0.00
2. Escocia 2 1 1 0 2 1 +1 4 2.00 50% 1.00 0.50
3. Ecuador 2 0 0 2 1 5 -4 0 0.00 0% 0.50 2.50

-
Temporada Juegos 1 x 2  ¦  1 2  ¦  Más 2.5 Menos de 2.5 Más 1.5 Menos de 1.5 Ventaja en casa
2022Playoffs4 25.0% 25.0% 50.0%  ¦  33.3% 66.7%  ¦  50.0% 50.0% 75.0% 25.0% -33.3%
2016Temporada regular4 50.0% 25.0% 25.0%  ¦  75.0% 25.0%  ¦  100.0% 0.0% 100.0% 0.0% 50.0%
2015Temporada regular1 100.0% 0.0% 0.0%  ¦  100.0% 0.0%  ¦  100.0% 0.0% 100.0% 0.0% 100.0%
2013Temporada regular2 0.0% 0.0% 100.0%  ¦  0.0% 100.0%  ¦  50.0% 50.0% 100.0% 0.0% -100.0%
2012Temporada regular1 100.0% 0.0% 0.0%  ¦  100.0% 0.0%  ¦  0.0% 100.0% 0.0% 100.0% 100.0%
2011Temporada regular3 0.0% 100.0% 0.0%  ¦   ¦  0.0% 100.0% 0.0% 100.0%
2009Temporada regular3 66.7% 33.3% 0.0%  ¦  100.0% 0.0%  ¦  66.7% 33.3% 100.0% 0.0% 100.0%
2000-2001Temporada regular3 66.7% 33.3% 0.0%  ¦  100.0% 0.0%  ¦  0.0% 100.0% 100.0% 0.0% 100.0%
1999-2000Temporada regular4 0.0% 100.0% 0.0%  ¦   ¦  0.0% 100.0% 50.0% 50.0%
1998-1999Temporada regular3 33.3% 66.7% 0.0%  ¦  100.0% 0.0%  ¦  0.0% 100.0% 33.3% 66.7% 100.0%
1997-1998Temporada regular3 66.7% 33.3% 0.0%  ¦  100.0% 0.0%  ¦  33.3% 66.7% 66.7% 33.3% 100.0%
1996Temporada regular2 100.0% 0.0% 0.0%  ¦  100.0% 0.0%  ¦  50.0% 50.0% 50.0% 50.0% 100.0%
1995Temporada regular3 66.7% 33.3% 0.0%  ¦  100.0% 0.0%  ¦  66.7% 33.3% 66.7% 33.3% 100.0%
1994Temporada regular3 0.0% 33.3% 66.7%  ¦  0.0% 100.0%  ¦  33.3% 66.7% 66.7% 33.3% -100.0%
1993Temporada regular3 33.3% 33.3% 33.3%  ¦  50.0% 50.0%  ¦  33.3% 66.7% 33.3% 66.7% 0.0%
1992Temporada regular3 33.3% 0.0% 66.7%  ¦  33.3% 66.7%  ¦  0.0% 100.0% 0.0% 100.0% -33.3%

Haga clic en cualquier columna para ordenar la tabla
Porcentajes mouseover (%) para ver las probabilidades de valor

AnnaBet Power Ratings

Actualizado 2025-03-15 10:22:19
#Equipo Rating
1. Japón 1441
2. Ecuador 1402
3. Escocia 1204


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.