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  South Asian Games Women 2021 @ Vietnam

Group A

# Tým Z V R P VG OG Diff B B/Z V% ØVG ØOG
1. Vietnam W 1 1 0 0 7 0 +7 3 3.00 100% 7.00 0.00
2. Kambodža W 1 0 0 1 0 7 -7 0 0.00 0% 0.00 7.00

Group B
# Tým Z V R P VG OG Diff B B/Z V% ØVG ØOG
1. Thajsko W 2 1 1 0 6 1 +5 4 2.00 50% 3.00 0.50
2. Myanmar W 2 1 1 0 2 1 +1 4 2.00 50% 1.00 0.50
3. Singapur W 2 1 0 1 1 1 0 3 1.50 50% 0.50 0.50
4. Laos W 2 0 0 2 0 6 -6 0 0.00 0% 0.00 3.00


Klikněte na vybraný sloupec, aby ste seřadili tabulku
Mouseover percentages (%) to see value odds

Vybrát sezónu


2023
2021
2019
2016


Oficiální stránka

Wikipedia

Sobota 21. květen 2022
   
South Asian Games Women - Playoffs - Finals2021 Kurzy 1x2
Vietnam W    1 - 0    Thajsko W2.272.783.03
South Asian Games Women - Playoffs - Bronze2021 Kurzy 1x2
Myanmar W    1 - 2    Filipíny W2.673.122.47
   
Středa 18. květen 2022
   
South Asian Games Women - Playoffs - 1/2 Finals2021 Kurzy 1x2
Vietnam W    1 - 0    Myanmar W1.493.905.42
Thajsko W    3 - 0    Filipíny W1.623.814.36
   
Neděle 15. květen 2022
   
South Asian Games Women - Group B2021 Kurzy 1x2
Laos W    0 - 5    Thajsko W
Singapur W    0 - 1    Myanmar W
   
Sobota 14. květen 2022
   
South Asian Games Women - Group A2021 Kurzy 1x2
Kambodža W    0 - 7    Vietnam W
   
Pátek 13. květen 2022
   
South Asian Games Women - Group B2021 Kurzy 1x2
Thajsko W    1 - 1    Myanmar W2.333.092.84
Laos W    0 - 1    Singapur W1.873.154.05

Více výsledků


květen 2022

Filipíny W
Kambodža W
Laos W
Myanmar W
Singapur W
Thajsko W
Vietnam W


Vybrát sezónu


2023
2021
2019
2016


Oficiální stránka

Wikipedia

# Tým Z V R P VG OG Diff B B/Z V% ØVG ØOG
1. Vietnam W 3 3 0 0 9 0 +9 9 3.00 100% 3.00 0.00
2. Thajsko W 4 2 1 1 9 2 +7 7 1.75 50% 2.25 0.50
3. Myanmar W 4 1 1 2 3 4 -1 4 1.00 25% 0.75 1.00
4. Singapur W 2 1 0 1 1 1 0 3 1.50 50% 0.50 0.50
5. Filipíny W 2 1 0 1 2 4 -2 3 1.50 50% 1.00 2.00
6. Laos W 2 0 0 2 0 6 -6 0 0.00 0% 0.00 3.00
7. Kambodža W 1 0 0 1 0 7 -7 0 0.00 0% 0.00 7.00

-
Sezóna Zápasů 1 x 2  ¦  1 2  ¦  Víc než 2.5 Méně než 2.5 Víc než 1.5 Méně než 1.5 Výhoda domácích
2023Playoff2 50.0% 0.0% 50.0%  ¦  50.0% 50.0%  ¦  50.0% 50.0% 100.0% 0.0% 0.0%
2021Group Stage5 0.0% 20.0% 80.0%  ¦  0.0% 100.0%  ¦  40.0% 60.0% 60.0% 40.0% -100.0%
2021Playoff4 75.0% 0.0% 25.0%  ¦  75.0% 25.0%  ¦  50.0% 50.0% 50.0% 50.0% 50.0%
2019Základní část6 66.7% 0.0% 33.3%  ¦  66.7% 33.3%  ¦  66.7% 33.3% 66.7% 33.3% 33.3%
2019Playoff3 33.3% 33.3% 33.3%  ¦  33.3% 66.7%  ¦  33.3% 66.7% 66.7% 33.3% -33.3%
2016Základní část10 60.0% 20.0% 20.0%  ¦  75.0% 25.0%  ¦  60.0% 40.0% 80.0% 20.0% 50.0%
2016Playoff1 100.0% 0.0% 0.0%  ¦  100.0% 0.0%  ¦  100.0% 0.0% 100.0% 0.0% 100.0%

Klikněte na vybraný sloupec, aby ste seřadili tabulku
Mouseover percentages (%) to see value odds

AnnaBet Sila výkonnosti

Updated 2025-02-17 11:25:39
#Tým Rating
1. Vietnam W 1232
2. Myanmar W 1177
3. Filipíny W 1165
4. Thajsko W 1093
5. Kambodža W 837
6. Singapur W 767
7. Laos W 757


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.