Redo Teamgame Elo

Hello,

right now teamgame elo is absolutely not viable to judge players skill level. it is way to easy for rather weak players to get to 2500 or even a bit higher. and since matchmaking only takes the teamgame elo into consideration when trying to make a balanced game - that should ofcourse be the case but does not work at the moment - a lot of games that on paper have even ratings are absolutely onesided because there are some 2500 players that are actually decent but there are also a lot that are pretty noobish.

but what is the problem: right now the elo a player wins or loses is only done in consideration of the highest elo of the opponents. what that does is making it very easy to win points, but very hard to ever drop significantly in rating.

An easy example:

Team A: 4 Players: A1: 2000 A2: 2000 A3: 2000 A4: 2000 Team elo: 8000, average 2000
Team B: 4 Players: B1: 2800 B2: 1700 B3: 1700 B4: 1700 Team elo: 7900, average 1975

this would propably be a pretty unbalanced TG in the current ladder, since i think that the 2k8 player should be able to carry his team, but i only use this as an rather extrem example to show the current issue.

If Team A wins: A1, A2, A3 and A4 gain 15 elo, B1 loses 15 elo, B2, B3 and B4 lose 5.
If Team A loses: A1, A2 A3 and A4 lose 1 elo, B1 wins 1elo, B2, B3 and B4 win 10 elo

the numbers of elo won or lose are just made up, since i do not know the exact way they are calculated, but that does not change anything. The point is still clear.

As you can see: if those teams match up against each other quite often and both teams win 50% of the games player B1keeps his elo, but everyone else closes in to 2800 without needing to improve the skill.

I hope that this made the issue clear to everyone.

How elo should work is that the average team elo is taken (2000 vs 1975 in my example) and every single player of one team loses or wins the same amount of points - and also the winning team only wins as many points as the losing team loses. That way elo would not rise forever, and also elo will actually tell you about players ratings.

What i would like to see from the devs is to completely redo the TG matchmaking, reset it (either to everyones 1v1 ratings or just let everyone start from 1000 again) and have it calculated properly so that we can enjoy TGs again.

7 Likes

Yes, this. It has been covered in previous threads, but they haven’t taken up the advice yet.

The only thing I would change from what you suggest is that it should be some measure of team strength, but not necessarily the average ELO. But the strength should be a single number for the team, and the ELOs of each team member should change by the same amount, equal and opposite for the winning and losing teams. For example, a measure of team strength that gives more weight to higher rated players could be used.

The current system assumes that the higher rated players in a winning team are more likely to be at their correct ELO than the lower rated players, and gives more ELO to the lower rated players. But I’m not convinced this is more likely than the lower ELO players being the over-rated ones, and the higher ELO players being the under-rated ones. The way it currently works, in that situation, the lower ELO players just keep getting more over-rated, and the under-rating of the higher ELO players doesn’t get fixed. For example, I’ve seen team games where a lower rated player is playing at maybe 500 ELO above their true rating, whereas the higher rated players are playing at 500 ELO below their true rating. The situation just never gets fixed, because when they win, the higher rated players hardly gain any ELO, while the lower rated player whose ELO is inflated just keeps gaining ELO.

3 Likes

this could be done but that would only change the highest elo that can realistically be reached. so i would not mind if they do not put effort into this. but what they really need to put effort in is to redo this whole TG rating. because as it is now, TGs are just very unbalanced.

Team game elo is broken in general and needs to be fixed.

This is my own thread about this subject. In the current system it isnt even fun to play team games any more.

didnt see your post, but i think it is good to have several topics facing that issue. maybe we get the devs attention that way. also i think my post answers quite a few of the questions you were having there.

I was playing with the numbers on Team Elo and how it is distributed.
For me the Elo 1v1 system works great (maybe I would argue about the k factor of 32 which is fine but could be better, k = 32 for newcomers to the game with less than 10 games and then go to k = 16 more or less)
The Elo team on the other hand is a disaster, with inflation due to the non-uniform distribution of the points in the game between the teams and between the players of each team.
My proposal is to continue balancing Team Elo as 1v1 Elo but distribute the points unevenly to the players:
-If your team wins, distribute the points in a weighted average way where the player with the fewest Elo Team points gets more points than the other players
-If your team loses, then take the points in a weighted average way where the player with the most Elo Team points would lose more points than the rest of the team.
The weighted average would be made according to the Team Elo points of each player within the Team.

Example 4v4:

  • Team A:

    • Player 1: 2200 Team Elo
    • Player 2: 1500 Team Elo
    • Player 3: 800 Team Elo
    • Player 4: 300 Team Elo
      - Average Team A: 1200
  • Team B:

    • Player 1: 1650 Team Elo
    • Player 2: 1350 Team Elo
    • Player 3: 1250 Team Elo
    • Player 4: 1000 Team Elo
      - Average Team B: 1312
      Team A has a 34% chance of beating team B based on the average Elo team.
  • If Team A wins, then 21.01 points must be taken from Team B to Team A (as 1v1):
    -Team A:

    • Player 1: 8% of the points β†’ +1.67 β†’ New Team Elo = 2202 Team Elo (was 2200)
    • Player 2: 12% of the points β†’ +2.46 β†’ New Team Elo = 1502 Team Elo (1500)
    • Player 3: 22% of the points β†’ +4.60 β†’ New Team Elo = 805 Team Elo (800)
    • Player 4: 58% of the points β†’ +12.28 β†’ New Team Elo = 300 Team Elo (312)
      - Average New Team A: 1205 (5 point increase)
      -Team B:
    • Player 1: 31% of the points β†’ -6.60 β†’ New Team Elo = 1643 Team Elo (was 1650)
    • Player 2: 26% of the points β†’ -5.40 β†’ New Team Elo = 1345 Team Elo (1350)
    • Player 3: 24% of the points β†’ -5.00 β†’ New Team Elo = 1245 Team Elo (1250)
    • Player 4: 19% of the points β†’ -4.00 β†’ New Team Elo = 996 Team Elo (1000)
      - New team B average: 1307 (decrease of 5 points)
  • Now if team A loses, 10.99 points must be awarded from team A to team B (as 1v1):
    -Team A:

    • Player 1: 46% of the points β†’ -5.04 β†’ New Team Elo = 2195 Team Elo (was 2200)
    • Player 2: 31% of the points β†’ -3.44 β†’ New Team Elo = 1497 Team Elo (1500)
    • Player 3: 17% of the points β†’ -1.83 β†’ New Team Elo = 798 Team Elo (800)
    • Player 4: 6% of the points β†’ -0.69 β†’ New Team Elo = 299 Team Elo (312)
      - New team average A: 1197 (decrease of 3 points)
      -Team B:
    • Player 1: 19% of the points β†’ +2.12 β†’ New Team Elo = 1652 Team Elo (was 1650)
    • Player 2: 24% of the points β†’ +2.59 β†’ New Team Elo = 1353 Team Elo (1350)
    • Player 3: 25% of the points β†’ +2.79 β†’ New Team Elo = 1253 Team Elo (1250)
    • Player 4: 32% of the points β†’ +3.49 β†’ New Team Elo = 1003 Team Elo (1000)
      - New team B average: 1315 (3 point increase)

This weighted average distribution model punishes the highest Elo player within each team the most and rewards the lowest Elo player within each team; and the points distributed (taken or earned) are the same without putting any inflation in the system
What you think? What are its weak points?

Example 2v2:

  • Team A:

    • Player 1: 2200 Team Elo
    • Player 2: 1000 Team Elo
      - Average Team A: 1600
  • Team B:

    • Player 1: 1650 Team Elo
    • Player 2: 1550 Team Elo
      - Average Team B: 1600
      Both team have 50% chance of beating the other team based on the average Elo team.
  • If Team A wins, then 16 points must be taken from Team B to Team A (as 1v1):
    -Team A:

    • Player 1: 31% of the points β†’ +5 β†’ New Team Elo = 2205 Team Elo (was 2200)
    • Player 2: 69% of the points β†’ +11 β†’ New Team Elo = 1011 Team Elo (1000)
      - Average New Team A: 1608 (8 point increase)
      -Team B:
    • Player 1: 52% of the points β†’ -8.25 β†’ New Elo team = 1642 Team Elo (was 1650)
    • Player 2: 48% of the points β†’ -7.75 β†’ New Elo team = 1542 Team Elo (1550)
      - New team B average: 1592 (decrease of 8 points)
  • Now if team A loses, the same 16 points must be awarded from team A to team B (as 1v1):
    -Team A:

    • Player 1: 69% of the points β†’ -11 β†’ New Team Elo = 2189 Team Elo (was 2200)
    • Player 2: 31% of the points β†’ -5 β†’ New Team Elo = 995 Team Elo (1000)
      - Average New Team A: 1592 (8 point decrease)
      -Team B:
    • Player 1: 48% of the points β†’ +7.75 β†’ New Elo team = 1658 Team Elo (was 1650)
    • Player 2: 52% of the points β†’ +8.25 β†’ New Elo team = 1558 Team Elo (1550)
      - New team B average: 1608 (increase of 8 points)
1 Like

I think weighten the team elo is the better approach. This calc ignores the characteristics of elo calculation. Tough it may reduce smurfs it does it in a not justificable way cause it distorts individual elo calc without any explanation.

1 Like