Thursday, January 20, 2022

10.0 Scores at Home and Away Meets 2022



A thoughtful question came up on Twitter yesterday:

 

 




I have the RTN data scraped for all scores reported from 1998 to 2022 so far (through January 17), so I checked. According to that data, there have been 718 10s scored and 434 have them have been by a gymnast competing at home. That means 60% of 10s are scored at home, which is more than half, but it doesn’t seem too out of the ordinary at first glance.



One thing I hadn’t considered until seeing this question is how many meets are home vs. how many are away. Since meets can (and do) often have more than one away team, in the entire dataset, there are more away scores than home scores.

In fact, of the scores on RTN from 1998-2022, just 37% are home scores.

 

Counts of home and away scores 1998-2022


(blue line is average percentage)





37% of all scores are scored at home, yet 60% of 10s are scored at home. This plot shows the percentage of each score from 9.0 to 10.0 scored at home (scores from judging panels > 2 are excluded so that only scores ending in .x0, .x25, .x5, and .x75 are included)









When we take this into account, we see that .21% of home scores are 10s, but just .082% of away scores are 10s.

Proportion of home scores that are 10s: 434/205014 = .002117

Proportion of away scores that are 10s: 284/344638 = .0008241



We often set this sort of data up in a 2x2 table like this:





10

not 10

Home

434

204580

Away

284

344354






Similarly, the odds of a 10 at home (total 10s at home divided by total non-10s at home) is .0021 and the odds of a 10 away (total 10s away divided by total non-10s away) is .00082.

Odds of 10 at home: 434/204580 = .002121

Odds of 10 away: 284/344354 = .0008247



These numbers are very similar to the proportion of home scores that are 10s and proportion of away scores that are 10s because 10s are relatively rare.



This means the odds ratio for scoring at 10 at home is 2.57. Odds ratio = odds of 10 at home/odds of 10 away.

Odds ratio: .002121/.0008247 = 2.57

(some rounding has occurred throughout when reporting the numbers)

This means the odds of scoring a 10 at home is about 2.57 times the odds of scoring a 10 away.



If we were to do the same calculation using 9.8s (just 9.8s exactly, not 9.8 and greater) scored home and away, we’d get this:

Home 9.8s = 13974

Home not 9.8s = 191040

Away 9.8s = 21524

Away not 9.8s = 323114



So, our 2x2 table looks like this:



9.8

not 9.8

Home

13974

191040

Away

21524

323114




Odds of 9.8 at home = 13974/191040 = .07315

Odds of 9.8 away = 21524/323114 = .06661



Odds ratio = .07315/.06661 = 1.10

The odds of scoring a 9.8 at home is only 1.1 times the odds of scoring a 9.8 away.





Some things to keep in mind here:

This doesn’t account for anything other than being home or away. It’s not a rigorous/thorough analysis so we have to be careful what kind of conclusions (if any) we draw from it.

One big weakness here is that it’s very likely that schools who are more likely to score 10s are also more likely to host home meets. That means that while there may be a real “home teams score more 10s” type of effect, we can’t completely separate it from “10s teams host more meets.”  Likewise, there might be other factors at play here in similar ways.

From the table and plot, it looks like there has been some variation in the percentage of home meets over time. There are probably multiple things factoring into these trends, none of which are really being accounted for here. Also, some of the earlier data on RTN tends to be less complete.



2 comments:

  1. Very interesting. I love data. I think it would be interesting to look at scores of non-top ten teams when they take on top-ten teams.

    I feel like generally in the past, scores are more generous for both teams against schools like UCLA, Utah, Oklahoma, Florida, and LSU. While this year, UCLA is struggling, I feel like there's been a lot of inflated judging at Michigan meets. I'm not saying the Michigan gymnasts don't deserve it, but in the past, Big Ten meets have had stricter judging than the SEC. While I think the goal should always been to have the same judging across all conferences and teams regardless, I draft my fantasy teams looking across the conferences and who has the potential to score a possible "inflated" score.

    ReplyDelete
    Replies
    1. I definitely think you’re onto something with the teams competing against traditionally high-scoring teams. I scratched the surface on this a few years ago, but I think it could stand some further review and updated data.

      In the meantime, this is from 2019:

      https://ncaagymstats.blogspot.com/2019/02/scores-for-teams-competing-against.html

      I also think it could be interesting to consider D2/D3 teams competing against D1 teams, as I suspect there may be a similar effect (sometimes).

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