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FRC Elo 2008-2016 by: Caleb Sykes

This workbook describes the Elo ratings of every team in FRC since 2002.

This workbook describes the Elo ratings of every team in FRC since 2002. Every match since 2002 is used, and the model predictions and results can be found in the year sheets. Team Elo ratings at the end of each season can be found in the “End of Season Elos” sheet. Average team Elo ratings for each season can be found in the “Average Elos” sheet. Detailed information about each team can be found in the “Team Lookup” sheet. To use the “team lookup” sheet, simply enter a team number into cell B1, and optionally a second team into cell B2, and press the “Import Teams” button. The second team will then show up on the same graph as the first team, but with “+” markers. If you only want to view a single team, leave cell B2 blank. Optionally, after importing teams, enter your desired year range into cells B3 and B4 and press the “Update Range” button.

This workbook describes the Elo ratings of every team in FRC since 2008. Every match since 2008 is used, and the model predictions and results can be found in the year sheets. Team Elo ratings at the end of each season can be found in the “End of Season Elos” sheet. Average team Elo ratings for each season can be found in the “Average Elos” sheet. Detailed information about each team can be found in the “Team Lookup” sheet. To use the “team lookup” sheet, simply enter a team number into cell B2 and press the “Update” button.

My biggest takeaway from this whole endeavor was how incredibly dominant 1114 was during the period 2008-2011. After their first event in 2008, this model predicts them to win every single remaining match in 2008, every match in 2009, every match in 2010, and every match at Pittsburgh in 2011. Their end of season Elo in 2008 was 200 points higher than the next highest rated team.

I will be following up soon with a comparison of predictive models.

Very nice tool you have here. 1114 is a fun team to watch the ELO for, which got quite high in 2010 until they threw the match.

Is it possible to adjust some of the parameters? Because the end of season reversion to the mean seams to small. 538’s models for basketball and football have at least a 25% reversion to mean. 25% seems like a lower bound since each team loses a class of seniors and build a new robot each season, and the latter should really drives this model.

As an example of this, the highest ELO from 2016 was a 254 qual match at their first event, which is really a carryover from their 2015 season. But this might be inevitable in some cases, like 538 notes in their NBA model that teams with superstars like Bulls and Cavs maintained high ELOs for a while after Jordan and LeBron left.

I chose the parameters I did based on what was the most predictive. I would have expected the mean reversion to be stronger, but 20% seemed to work the best. Here are the Brier scores for 2012-2014 for various mean reversion parameters.

What about the Brier score for longer windows? Between 2012 and 2014, the mean only reverts twice, and the relative error (|a-b|/|b|) between the Brier scores for different parameters is less than .1 in even the most extreme cases. With more reversions, that parameter should effect the accuracy more extremely, giving a better parameter estimate.

Interestingly, these results imply that 10% mean reversion would have been ever so slightly better than 20% for the 2015-2016 offseason. I don’t want to draw any larger conclusins though since 2015 was a weird year.

This is honestly one of the coolest documents to look at, especially to look at teams elo when they have either gained or lost key mentors and seeing how it had a short or long term impact in comparison to the field.

Hey, I appreciate you spending the time to put this together.

Question: Is there any way to use the team lookup, without having to purchase Excel? Google Docs obviously won’t run the program. Neither will LibreOffice. The free Windows Modern (nee’ Metro) app won’t run the function, and I don’t have access to Dreamspark any more.

Obviously, Excel is a powerful tool which is standard in many environments. But you’re really limiting who can actually use your work if we need to pay MS a $150 entry fee to do so.

Okay, I spent a bunch of time looking at the mean-reversion parameter and the results are extremely interesting. First, I tried running every 2-year period individually and found the best mean reversion just for that period. Here were the results:

The mean reversion was pretty high and relatively constant for all years.

Next, I found the best mean reversion for 2009 given 2008. Then I found the best mean reversion for 2010 given 2008 and 2009, and so on. In this way, each year would have a distinct mean reversion that builds off of the previous mean reversions. Here were the results:

These values start high, as in the previous case, but they seem to drop after a while as the model learns more about the teams.

Finally, I compared how predictive the previous model was in comparison to my original 20% for all years, the results are attached.

Interestingly, adjusting the mean reversion every year actually fares worse overall than just using 20% every year, even if you throw out 2015 and 2016 because 2015 was an outlier year in many respects. I think the reason for this is because team performance 2 years in the future can still be reasonably well predicted by a current season’s performance. The constantly updating model seems to put the mean reversion parameter too high to fully account for this 2 year explanatory effect.

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.

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 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.

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.

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.