Much Ado About Elo

Nice, thanks for writing!

Where have my skills gone? From 100 to 150! Do you think I play just for fun?
(I'll read it tomorrow...)

Hey, that sounds great! (And by the way, the whole Xonstat system is a true masterpiece )

Especially that "K-factor reflects playing time"-thing should solve a few problems. (It wasn't implemented that way before, was it?) But what about this: I've played some duels, and sometimes people will just quit mid-game (by purpose or by accident, doesn't matter), which means I wouldn't get any Elo points, although I would've won that match. With the new system, players still have to be in the game at the end of the match so that points are calculated, is that right?

And another question: This new system does not take the player's scores into account anymore, like it was before? So it doesn't matter if I play 30:1 or 30:29 against somebody? What's the reason for that? I won't say that it's a bad decision, it just feels like "one step back" imho

Thanks for taking the time to explain this Antibody.

Excellent Job and explanation!

One funny note : The Elo in Chess led in the early 80s and 90s the top players to very rarely join a tourney with many averagely weaker elo players,because their chances of losing more ELO points where more amplified as they might lose to an underdog . This system makes i guess the top players more like a trophy .

3 days ago I was something about 96 in CTF, today I am 188. I don't really mind because I am going to have a break from Xonotic, the longer the better. Unbalanced games are an inherent problem which is never going to be solved. I doubt that 5% of players who try the game stay for a second try. Everyone who stayed is either a pro and/or crazy.

I doubt that 5% of players who try the game stay for a second try. Everyone who stayed is either a pro and/or crazy.

Come to the bright land of instagib, where every noob gets some frags even against pros. Braindead and fun.

@zykure - yes, you have to be there at the end of the match (present on the scoreboard) for Elo points to count either way.

The algorithm was previously based on your points differential versus your opponents: actual score/(actual score + opponent's score). That didn't work for duel, so I changed the algorithm's S value. That's now not working the best for DM (and CTF isn't perfect either), so div and I have collaborated to create a "blended" Elo that will use win/loss for duels and score differential for other game types. Nothing is ever perfect and I'm fine-tuning the changes now, so expect them to hit the site in the next week or so.

i was going to make the elmo algorithm , that way everyone tops the ladder and feels warm and fuzzy inside

* chooksta wonders what ranking elmo would get if he played this game


t


:^

( btw anti , that was a great write up , even i got it )

yay!

I'm back. (I don't know about precise implementation and different game modes but if what you described above is the core, then this: )

After a week of not playing the game, my uber-pro skills of inactivity granted me CTF position of 74 (I was 200~ several days ago, ~95 before that).
I thought about elo a bit and I think that it is unfair. In other words - it doesn't reflect well the "reality" of Xonotic. It may be good for competitive and/or controlled play, but public in Xonotic is something different. First thing is that it takes into consideration only win or loss and that's quite black & white. Teams are usually not the same when the game started, there is often rebalancing by the time score hits 0:5. Playing well for one side means nothing if you lose. And if you play against hard odds and you manage 9:10 it means nothing. But achieving nothing and switching at the last second will give you the score? There is no incentive for oh-so-great-and-practical-voluntary-team-rebalancing. When somebody said that he is going to change teams before losing I thought he was joking...

Other aspect I now miss is playing for fun. Not worrying about the bad outcome, only if you made a difference or not.
More simple and intuitive would be measuring just how well you play in a certain gamemode. (average of score). Anything more complex would have to take into consideration player switching, quitting etc etc.

stuff:
- Perhaps being more active should be a bit more rewarding, or not playing should erode your score. Top CTF players are quite inactive.
- quantity problem, if you play alone and lose against 5 noobs it will treat it in the same way as if you lost to a noob in a duel.
- for duels, clan battles and maybe DM, elo is still good solution
- I don't know about DM, the way it works it should be more fair, because it doesn't matter that much how many people there are, who joins or leaves, only winning matters. Problem may be if you are 2# player who usually loses but still beats the worse players. For those score will be only going down.
- I'm also not sure about noob dilution, you can play basically a duel with a pro and having 6 other noobs present may be inconsequential to the outcome but it will change the score dramatically.
- good players leaving before the end may affect the score greatly.
- quitting might be a way of cheating the system, people tend to do this anyway, maybe they just had enough
- elo does not even tell you how much is somebody good (jumping from 200 to 100 without one match?)
- why are score differences in matches no longer displayed?

also there may be a bug in your article:
we’ll each have a K value of 20. ----- but over the course of 32 games that factor decreases linearly down to 40.

In the week since I wrote that article I've made a lot of tweaks to the algorithm, especially for team games and DM (duel is largely unchanged). divVerent had many good suggestions that counteract some of your negative points and we came to a good compromise. I'll be writing a followup blog post to inform everyone of the changes.

Let me address a couple of your points anyway:

- I'm sorry you don't feel like you aren't playing for fun anymore. You can turn off your tracking and be excluded from any Elo calculations if you'd like, or you can just ignore the ranks because they aren't important to you.
- There is a reason the variance is high in the early stages - it's because we aren't yet confident that we've arrived at something close to your true score. That's the reason why you don't get ranked until >32 games.
- Quitting is a way to game the system at the moment. div and I are discussing ways to counteract that. Even without that in place, quitting is something everyone else playing the game can see. It doesn't take long for people to recognize the quitters and adjust accordingly for them. Additionally if people want to have a single minded focus on Elo, fine. IMO they are ignoring many other aspects of stats that would be beneficial to them if they were to stay in the game.
- The ending K value is indeed 40. In my haste I wrote down the kfactor (percentage reduction to K) instead. Fortunately this does not materially impact what I'm trying to show with the example since it each player had the same ending K value.

I don't take statistics all that seriously, I have just checked them a dozen times and realized with the help of your explanation that its sometimes not fair. They record the state of the game at the end which is something that may be the opposite of how the game started out.

I just wanted to point out potential problems, I know that I can ignore my stats and that nobody gives a frag about my score anyway. Statistics are quite cool but not when people can cheat them.

Quitting is not only stats-braking but also game-breaking but that is probably for some other thread...

- low variance: stats say I have played 391 CTF matches :-), my elo is better than rocknroll's (98) and he's a better player than I am

Here's a funny thing I've coded lately ... thought I just share that with you: http://pastebin.com/BydSaRp5

It shows the elo change which results from a duel match for the two possible outcomes (A wins vs. B wins), according to Antibody's post above. The K-factor can be given too (default 40, for new players you have to calculate it from the number of games N (N < 32): K = 200 - 5 x N).

Example output:

Code:

$ python elo.py 100 1000
A has elo  100.000 at K =  40
B has elo 1000.000 at K =  40

Outcome 1: A wins
    A gains  39.776 points
    B loses  39.776 points

Outcome 2: B wins
    A gains   0.224 points
    B loses   0.224 points

Note that in duel matches, the final score doesn't affect the elo change, only the rank does. (However in dm/ctf, score is also important!)