How does scoring work?
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@ftxcommando I might have to do 1v1 and 2v2, etc, because it's going to take 3000 years to get my rating back up otherwise.
Maybe at the same time you might consider a partial fix to what I still consider broken game scoring, i.e. someone on my same team gets 20x or more rating increase than me when I was indicated as the game winner -- maybe there could be some sort of smoothing on rating changes given to the winning team where someone can't get 20x+ the rating increase?
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No, that makes the system worse. People aren’t “gaining” huge rating. They already have it. A new player has 1500 mu and 500 sigma. This gives them a shown rating of 0. If they beat a 1200 mu 100 sigma player, their mu moves slightly while their sigma drastically decreases. This gives them the illusion of “gaining” rating in terms of shown rating when instead they haven’t gained much rating at all in terms of what trueskill is concerned with. Smoothing out rating gains is just a misunderstanding of how new players are integrated into the distribution of players.
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Thanks for the response.
How is mu adjusted for players? You said 'slightly'. Is it a set amount, and is it adjusted the same for all players, regardless of rating, and then the overall apparent rating change as you explained is based on mu and sigma?
Or is mu adjusted based on the players net rating?
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Only things that matter in FAF are whether you win or loss, who you won or lost against, and how certain the system is of your placement.
Thats why the tactic of suicide is should be allowed. You killing your opponent no matter what, the fact that you killed him.
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@eternal Thanks for the info. I get that. I'm now interested in understanding how mu is adjusted. i.e. same for all players on winning team, or different?
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It's calculated for each player individually. The actual math gets pretty complicated. Here is a very detailed explanation: https://www.moserware.com/assets/computing-your-skill/The Math Behind TrueSkill.pdf
I found a shorter explanation once, but I can't find it right now. You can just google for trueskill and will find all sorts of explanations. -
Is there a simpler answer than a 57-page word doc?
Seems like you're saying that even though no information is collected to assess player performance, players are given different mu adjustments.
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There is no 'player performance' collected because it is meaningless. It doesn't matter how you won, what is relevant is that you did. If we introduce 'player performance' then people stop playing the game and start playing the rating system.
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Players are given different mu adjustments when their deviation is different. There is an exact formula for it, but it's complicated and I can't find it quickly. Your best bet is to google it yourself if you want more details, I've been doing the same.
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Trueskill was developed by Microsoft so I suggest we all contact Microsoft support and tell them to change the algorithm.
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@ginandtonicbot said in How does scoring work?:
Thanks for the info. I get that. I'm now interested in understanding how mu is adjusted. i.e. same for all players on winning team, or different?
It is different.
Is there a simpler answer than a 57-page word doc?
Yes.
Seems like you're saying that even though no information is collected to assess player performance, players are given different mu adjustments.
The after game rating changes that you see are changes in displayed rating, which can basically be thought of as "base rating (mu) - uncertainty (3 * sigma) = displayed rating". The higher the sigma value, the lower the displayed rating and the more uncertain a rating is. So, new players start at "1500 base rating - 1500 uncertainty = 0 displayed rating". A typical player with a lot of games has around 250-300 rating uncertainty. Playing rated games lowers uncertainty to around 100-350 uncertainty as a stable level whose exact value largely depends on whether the player plays a lot of 1v1's (less uncertainty), 3v3's, 8v8's (more uncertainty), etc. Since players start with 1500 uncertainty, their ratings are initially more volatile and they more readily gain/lose rating. As they play more rated games, the uncertainty decreases and their ratings stabilize more, resulting in smaller rating changes from individual games. Additionally, if a player wins a game that was balanced in the player's favor, then the player gains a smaller amount of base rating (mu) than if the game was balanced against the player's favor (based on rating). Also, smaller game sizes (ie: 1v1's) generally have more impact than larger game sizes (ie: 8v8's).
