The new ELO-based ranking system

@MrRoboto I’m not worried that it will fail to capture the exceptional case. Its just that I’d like the system to ensure that players (new or otherwise) make the playoffs in a given year based on their performance in that year with little influence from games played in prior years. Another example would be if players starting a year with a 1500 ELO, a 1800 ELO and a 2100 ELO all have the same record in that year, I expect we are often going to still see a difference in their ELO at the end even though the lower ranked players have closed some of the gap. With enough games, that difference should more or less disappear but I’m worried that it will be more than the 6 games needed for entry into the playoffs.

But again, happy to give it a try and see how it works. And I do really like this ELO for a bunch of other reasons that your work has illustrated.

@gamerman01 @MrRoboto

I don’t know the term in English but you can include “Zahlenformat (?) in die bedingte Formatierung” so that in cells (of the column with players’ names) that are colored white they also display something like “less than three games so far” behind the name

I still can’t access the spreadsheet directly and use things like the search and filter function, or put new data in directly. I can just see it as another page in chrome (so no google sheets interface either) and nothing tells me that I don’t have permission or that it is read only. I’ve tried going into google sheets and then loading the page but can’t find it.

Two questions. If others are able to access it, how? If others aren’t, is there something that @MrRoboto needs to do to open up access.

I usually use office, not google for documents and spreadsheets, so might just not be familiar enough.

@MrRoboto that does work! Thanks!

@MrRoboto said in Proposal for a new, ELO-based, ranking system:

How do you like it this way?

That way everyone can see the lifetime-ranking and also the playoff-spot

Yes, perfect, tier colors across and also formulaed rankings for 6+ games. I said ready, set, go because I had confidence you would make the solution quickly! 💯

@MrRoboto
Why are the ELO ranking levels different for the different versions? Is that intentional based on some mathematical spread?

@MrRoboto Mr. Roboto, this is excellent work! It’s actually quite perfect timing, I created my own spreadsheet a few days ago for Revised players on TripleA. The one thing I can’t seem to wrap my head around is setting an ELO and then updating it without creating a circular reference. If you could help this I would be eternally grateful! My spreadsheet is here: https://bit.ly/revisedstats

Thanks!

The dwarves are digging deep, all the way to 9/30/17 so far…

Watch as the life-time ELO rankings take shape…
Or wait until all is entered and edit checks done

@airwalker

I just saw that your post was queued for approval, and approved it

@gamerman01 Thank you

From the first page:

“A win by the current #1 against the current last place will award only meager 4 points for the winner and -2 for the loser.
However, the last player would receive a whopping 136 for a win and #1 would suffer -87 for that loss!”

Maybe this has been adressed before and. I am just curious why this is fair.

In chess, the winner and the loser gain/lose the same number of points whereas here the winner always gain more than the loser lose. Why is it this way? This means that everyones rating will increase over time given the number of players are constant? How is this fair to new players?

I am sure I am missing something!

I say everyones rating will increase. I mean “everyone” or most player.

The loser’s ELO drops more than the winner’s gains if the winner’s ELO is higher than the loser’s

I think you can access the “results” tab
Type in a player’s name in the yellow box and I think you’ll be able to see

It’ll be more efficient if @MrRoboto answers the rest

Something is wrong if the average player is worse than the new player since this has been incorrect from personal experience.

I looked through the data to see the apparent ELO of new players and they have been averaging around 1360 meaning they beat people ranked above this number the same frequency as they lost to people ranked below this number in their first game. I excluded the first few years of data as everyone was fresh in the League. Not the most rigorous mathematical calculation and I am sure you could be more accurate in the numbers.

Unfortunately this is a bit of a recursive calculation if you wanted to do this properly; adding in new people at ELO=1360 will lower the ELO of the entire community meaning you have to again adjust the ELO of newbies. In the end you probably will get around 1330 as the best estimate of a fresh person joining the League, but I would be interested if you could do a more thorough evaluation.