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  AFF U19 Championship 2024 @ Indonésie

Group A

# Tým Z V R P VG OG Diff B B/Z V% ØVG ØOG
1. Indonésie U19 3 3 0 0 14 2 +12 9 3.00 100% 4.67 0.67
2. Kambodža U19 3 1 0 2 3 5 -2 3 1.00 33% 1.00 1.67
3. Východní Timor U19 3 1 0 2 5 10 -5 3 1.00 33% 1.67 3.33
4. Filipíny U19 3 1 0 2 2 7 -5 3 1.00 33% 0.67 2.33

Group B
# Tým Z V R P VG OG Diff B B/Z V% ØVG ØOG
1. Austrálie U19 3 3 0 0 13 2 +11 9 3.00 100% 4.33 0.67
2. Vietnam U19 3 1 1 1 7 8 -1 4 1.33 33% 2.33 2.67
3. Myanmar U19 3 0 2 1 2 3 -1 2 0.67 0% 0.67 1.00
4. Laos U19 3 0 1 2 2 11 -9 1 0.33 0% 0.67 3.67

Group C
# Tým Z V R P VG OG Diff B B/Z V% ØVG ØOG
1. Malajsie U19 2 1 1 0 6 1 +5 4 2.00 50% 3.00 0.50
2. Singapur U19 2 1 0 1 2 5 -3 3 1.50 50% 1.00 2.50
3. Thajsko U19 1 0 1 0 1 1 0 1 1.00 0% 1.00 1.00
4. Brunej U19 1 0 0 1 0 2 -2 0 0.00 0% 0.00 2.00


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

Vybrát sezónu


2024
2022
2019
2018
2017
2016
2015
2014
2013


Oficiální stránka

Wikipedia

Pondělí 29. červenec 2024
   
AFF U19 Championship - Playoffs - Finals2024 Kurzy 1x2
Indonésie U19    1 - 0    Thajsko U192.022.833.32
AFF U19 Championship - Playoffs - Bronze2024 Kurzy 1x2
Austrálie U19    2 - 1 pen Malajsie U191.533.894.32
   
Sobota 27. červenec 2024
   
AFF U19 Championship - Playoffs - 1/2 Finals2024 Kurzy 1x2
Indonésie U19    1 - 0    Malajsie U191.773.573.87
Austrálie U19    0 - 1    Thajsko U191.324.787.94
   
Čtvrtek 25. červenec 2024
   
AFF U19 Championship - Group C2024 Kurzy 1x2
Malajsie U19    1 - 1    Thajsko U192.053.822.81
Singapur U19    2 - 0    Brunej U191.0412.7521.00
   
Středa 24. červenec 2024
   
AFF U19 Championship - Group B2024 Kurzy 1x2
Laos U19    1 - 4    Vietnam U19
Myanmar U19    0 - 1    Austrálie U19
   
Úterý 23. červenec 2024
   
AFF U19 Championship - Group A2024 Kurzy 1x2
Indonésie U19    6 - 2    Východní Timor U191.0216.0027.50
Kambodža U19    1 - 0    Filipíny U192.393.492.47
   
Pondělí 22. červenec 2024
   
AFF U19 Championship - Group C2024 Kurzy 1x2
Singapur U19    0 - 5    Malajsie U197.405.321.28
   
Neděle 21. červenec 2024
   
AFF U19 Championship - Group B2024 Kurzy 1x2
Myanmar U19    1 - 1    Laos U191.275.327.56
Austrálie U19    6 - 2    Vietnam U191.136.8911.55
   
Sobota 20. červenec 2024
   
AFF U19 Championship - Group A2024 Kurzy 1x2
Kambodža U19    0 - 2    Indonésie U1925.5015.001.03
Filipíny U19    2 - 0    Východní Timor U193.063.461.90
   
Čtvrtek 18. červenec 2024
   
AFF U19 Championship - Group B2024 Kurzy 1x2
Vietnam U19    1 - 1    Myanmar U191.215.708.93
Laos U19    0 - 6    Austrálie U1927.0015.501.02
   
Středa 17. červenec 2024
   
AFF U19 Championship - Group A2024 Kurzy 1x2
Indonésie U19    6 - 0    Filipíny U191.0314.0029.00
Východní Timor U19    3 - 2    Kambodža U194.003.731.65

Více výsledků


červenec 2024

Austrálie U19
Brunej U19
Filipíny U19
Indonésie U19
Kambodža U19
Laos U19
Malajsie U19
Myanmar U19
Singapur U19
Thajsko U19
Vietnam U19
Východní Timor U19


Vybrát sezónu


2024
2022
2019
2018
2017
2016
2015
2014
2013


Oficiální stránka

Wikipedia

# Tým Z V R P VG OG Diff B B/Z V% ØVG ØOG
1. Indonésie U19 5 5 0 0 16 2 +14 15 3.00 100% 3.20 0.40
2. Austrálie U19 5 3 0 1 15 4 +11 9 1.80 80% 2.80 0.80
3. Malajsie U19 4 1 1 1 7 4 +3 4 1.00 25% 1.75 0.75
4. Thajsko U19 3 1 1 1 2 2 0 4 1.33 33% 0.67 0.67
5. Vietnam U19 3 1 1 1 7 8 -1 4 1.33 33% 2.33 2.67
6. Kambodža U19 3 1 0 2 3 5 -2 3 1.00 33% 1.00 1.67
7. Singapur U19 2 1 0 1 2 5 -3 3 1.50 50% 1.00 2.50
8. Východní Timor U19 3 1 0 2 5 10 -5 3 1.00 33% 1.67 3.33
9. Filipíny U19 3 1 0 2 2 7 -5 3 1.00 33% 0.67 2.33
10. Myanmar U19 3 0 2 1 2 3 -1 2 0.67 0% 0.67 1.00
11. Laos U19 3 0 1 2 2 11 -9 1 0.33 0% 0.67 3.67
12. Brunej U19 1 0 0 1 0 2 -2 0 0.00 0% 0.00 2.00

-
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
2024Group Stage15 46.7% 20.0% 33.3%  ¦  58.3% 41.7%  ¦  46.7% 53.3% 86.7% 13.3% 16.7%
2024Playoff4 50.0% 25.0% 25.0%  ¦  75.0% 25.0%  ¦  0.0% 100.0% 25.0% 75.0% 50.0%
2022Group Stage25 36.0% 16.0% 48.0%  ¦  42.9% 57.1%  ¦  60.0% 40.0% 72.0% 28.0% -14.3%
2022Playoff4 25.0% 25.0% 50.0%  ¦  50.0% 50.0%  ¦  25.0% 75.0% 100.0% 0.0% 0.0%
2019Group Stage30 46.7% 10.0% 43.3%  ¦  51.9% 48.1%  ¦  66.7% 33.3% 76.7% 23.3% 3.7%
2019Playoff4 50.0% 25.0% 25.0%  ¦  50.0% 50.0%  ¦  75.0% 25.0% 75.0% 25.0% 0.0%
2018Group Stage25 52.0% 16.0% 32.0%  ¦  61.9% 38.1%  ¦  68.0% 32.0% 80.0% 20.0% 23.8%
2018Playoff4 0.0% 25.0% 75.0%  ¦  25.0% 75.0%  ¦  50.0% 50.0% 75.0% 25.0% -50.0%
2017Group Stage25 44.0% 8.0% 48.0%  ¦  47.8% 52.2%  ¦  80.0% 20.0% 96.0% 4.0% -4.3%
2017Playoff4 50.0% 50.0% 0.0%  ¦  75.0% 25.0%  ¦  25.0% 75.0% 50.0% 50.0% 50.0%
2016Group Stage25 36.0% 12.0% 52.0%  ¦  40.9% 59.1%  ¦  84.0% 16.0% 96.0% 4.0% -18.2%
2016Playoff4 75.0% 0.0% 25.0%  ¦  75.0% 25.0%  ¦  100.0% 0.0% 100.0% 0.0% 50.0%
2015Group Stage20 40.0% 20.0% 40.0%  ¦  50.0% 50.0%  ¦  55.0% 45.0% 75.0% 25.0% 0.0%
2015Playoff4 50.0% 25.0% 25.0%  ¦  75.0% 25.0%  ¦  75.0% 25.0% 100.0% 0.0% 50.0%
2014Group Stage6 50.0% 0.0% 50.0%  ¦  50.0% 50.0%  ¦  83.3% 16.7% 83.3% 16.7% 0.0%
2014Playoff4 25.0% 0.0% 75.0%  ¦  25.0% 75.0%  ¦  50.0% 50.0% 50.0% 50.0% -50.0%
2013Group Stage25 60.0% 16.0% 24.0%  ¦  71.4% 28.6%  ¦  84.0% 16.0% 96.0% 4.0% 42.9%
2013Playoff4 25.0% 25.0% 50.0%  ¦  50.0% 50.0%  ¦  25.0% 75.0% 50.0% 50.0% 0.0%

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

AnnaBet Sila výkonnosti

Updated 2025-04-01 10:58:25
#Tým Rating
1. Austrálie U19 1264
2. Malajsie U19 1211
3. Indonésie U19 1178
4. Thajsko U19 1154
5. Vietnam U19 1131
6. Laos U19 951
7. Myanmar U19 945
8. Kambodža U19 864
9. Východní Timor U19 858
10. Singapur U19 763
11. Filipíny U19 703
12. Brunej U19 599


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.