paper: FRC Elo 2008-2016

[Caleb Sykes]

Originally Posted by SoftwareBug2.0

I don't know if this will make you feel any better, but I opened it with Excel and it didn't work and brought up a VB debugging window.

Have you downloaded it recently? My very original upload had a bug which I have since corrected, you might have been one of the 6 people who downloaded it before I deleted it.

[Caleb Sykes]

Originally Posted by EricH

Put 'em in the whitepaper's slot--you can attach multiple documents to one whitepaper. The Extra Discussion forum doesn't allow attachments (or deletions, generally speaking) due to some logic that I don't remember but makes sense from when I was informed about it.

I have put them with the whitepaper. I really don't like doing that though since I prefer my whitepapers to be fully self-explanatory, and for this I really just wanted to post some data which had context provided by my post.

I would love to hear the reasoning for this restriction sometime if anyone knows it.

[Joe Ross]

Originally Posted by Mark McLeod

OpenOffice works with it.

The team lookup tab didn't work for me in OpenOffice 4.1.3, or Excel 2007. It did work in Excel 2013. it looks like some of the features it uses were added in Excel 2013.

[SoftwareBug2.0]

Originally Posted by Caleb Sykes

Have you downloaded it recently? My very original upload had a bug which I have since corrected, you might have been one of the 6 people who downloaded it before I deleted it.

I was one of the six, but then it didn't seem to get fixed when I re-downloaded it. I'm also having no luck with LibreOffice.

The other parts of the spreadsheet are interesting to look at though. It's fun to get some numbers to see both how horrible my team was in 2008 and how good we were in 2013.

[Mark McLeod]

Originally Posted by Joe Ross

The team lookup tab didn't work for me in OpenOffice 4.1.3, or Excel 2007. It did work in Excel 2013. it looks like some of the features it uses were added in Excel 2013.

My mistake, I mixed my machines and which one had OpenOffice and which had Excel.

[Anteprefix]

Originally Posted by Joe Ross

The team lookup tab didn't work for me in OpenOffice 4.1.3, or Excel 2007. It did work in Excel 2013. it looks like some of the features it uses were added in Excel 2013.

It seems to work fine if you replace all instances of FullSeriesCollection with SeriesCollection and saving the changes in the debugger.

[Cothron Theiss]

Originally Posted by EricH

The Extra Discussion forum doesn't allow attachments (or deletions, generally speaking) due to some logic that I don't remember but makes sense from when I was informed about it.

Was it because of all the spam going on in the Rumor Mill, Chit-Chat, and Extra Discussion?

[EricH]

Originally Posted by Cothron Theiss

Was it because of all the spam going on in the Rumor Mill, Chit-Chat, and Extra Discussion?

No, it was something to do with the risk of stuff happening with the original paper/picture. This was before the spam influx.

[Michael Hill]

A couple things, it appears you are just using the raw elo differences in calculating red win likelihood. that is (red1+red2+red3) - (blue1 + blue2 + blue3).

I'm thinking if you're going to calculate win chance, you want to average out the elo on each side. However, it seems FRC Elo win percentages don't quite follow chess win percentages based on Elo. I went ahead and generated a cumulative distribution plot based on 2016 match data (and given elo ratings from the spreadsheet). I got what is shown in the plot below. The blue line is the "standard" chess Elo win probability CDF (a logistic distribution CDF), while the orange is from match data. I fit both a logistic CDF (gray) and Gaussian CDF (yellow).
The modded Logistic Dist had a mean of 0 and st. dev of 55 while the Gaussian dist had a mean of 0 and st. dev of 93.



What does this mean? Well, potentially, difference in Elo rating could potentially be a better predictor of winning FRC matches than chess matches. That is, a small difference in average alliance Elo rating has a larger effect on Win % in FRC (2016) than chess.

[Michael Hill]

Another thing to consider, however, is the distribution of Elo differences. So it's potentially a bit less useful than I made it out to be in the previous post because a huge amount of matches have a fairly small Elo difference.

http://i.imgur.com/bJRlgqu.png

[Caleb Sykes]

Originally Posted by Michael Hill

A couple things, it appears you are just using the raw elo differences in calculating red win likelihood. that is (red1+red2+red3) - (blue1 + blue2 + blue3).

I'm thinking if you're going to calculate win chance, you want to average out the elo on each side. However, it seems FRC Elo win percentages don't quite follow chess win percentages based on Elo. I went ahead and generated a cumulative distribution plot based on 2016 match data (and given elo ratings from the spreadsheet). I got what is shown in the plot below. The blue line is the "standard" chess Elo win probability CDF (a logistic distribution CDF), while the orange is from match data. I fit both a logistic CDF (gray) and Gaussian CDF (yellow).
The modded Logistic Dist had a mean of 0 and st. dev of 55 while the Gaussian dist had a mean of 0 and st. dev of 93.



What does this mean? Well, potentially, difference in Elo rating could potentially be a better predictor of winning FRC matches than chess matches. That is, a small difference in average alliance Elo rating has a larger effect on Win % in FRC (2016) than chess.

Looking at Elo averages instead of sums should be equivalent to changing the x-scale on the cdf by a factor of 3, and that looks like what you have posted. It doesn't really change anything, because all you are doing is changing the scale. I used the sums in my calculations, which should provide a cdf similar to those found in things like chess.

[Caleb Sykes]

Originally Posted by Caleb Sykes

Looking at Elo averages instead of sums should be equivalent to changing the x-scale on the cdf by a factor of 3, and that looks like what you have posted. It doesn't really change anything, because all you are doing is changing the scale. I used the sums in my calculations, which should provide a cdf similar to those found in things like chess.

Other methods of combining alliance Elos, such as taking each alliance's max Elo or doing some kind of weighted average would make a difference. I just haven't investigated these alternatives.

[jrw]

We played around with TrueSkill last year...

https://github.com/thedropbears/TrueSkill

TrueSkill is the natural successor to Elo. It was created at Microsoft for online matchmaking, and as such is able to deal with alliances of players.

A good explanation of the algorithm is here:
http://www.moserware.com/2010/03/com...our-skill.html