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Monday, July 15, 2013

So Who CAN Win the 2013 CrossFit Games - Predictions

Just a few quick notes before getting to the picks:
  • These picks are based almost entirely off the results from this season, and thus the order will be similar (but not identical) to the Cross Regional Comparison found at
  • There are some Games veterans, like Matt Chan for instance, whose odds probably look lower than some would expect. That's because last year's Games played only a very minor role in these projections. Although there are some athletes for whom we could probably make an exception, I think that in general, the results from Regionals this season are the best predictors of what will happen at the Games this season. Regionals are competitive enough now that I doubt many athletes were holding much back.
  • For full methodology, see the previous post. The general idea is to use the results from the events that have occurred this season and simulate Games events that would be similar to them.
  • These are rounded to the nearest 1%, so some athletes listed with a 0% chance actually may have non-zero chance according to the model, but that chance is less than 0.5%. For instance, virtually everyone had a non-zero chance of finishing in the top 10. The list is sorted by chance of winning, prior to rounding, and in case of ties, it is sorted by average finish.
  • This is all in good fun, so don't take it too seriously if your favorite athlete doesn't appear as highly as you'd like. I'm well aware that this model isn't perfect, but my goal is to make the best predictions I can with the data we have available. There's plenty going on behind the scenes for each of these athletes and plenty of other variables that I simply can't capture.
  • I'm curious to hear who you guys are picking this year. I think it should be a blast to see how things play out given the level of competition we've already seen this season. Post to comments or shoot me an email to let me know your take.
OK, without further ado, here are the picks. For each athlete, I have the estimated chance of him/her winning, placing in the top 3 (podium) and placing in the top 10 (money), along with the average ranking he/she attained across all simulations.


  1. How does this compare to last year? Outside of Froning's dominance is parity increasing?

    1. I'd say yes on the women's side, but for the men, it's about the same.

      On the women's side, this year I have 4 women with greater than an 8% chance of winning and 2 more with greater than a 5% chance of winning. Last year (using this system), I would have had just 2 with a greater than an 8% chance and just 2 more (Lentendre and Clever) with greater than a 5% chance of winning.

      For men's side, this year I have 3 men with greater than an 8% chance of winning and 1 more with greater than a 5% chance of winning. That's the same as last year. Last year I had 22 guys with at least a 10% shot at getting in the money, but this year I only have 20.

      If you look at the men, we're starting to see a group of about 5 younger guys that basically contend every year: Froning, Bailey, Khalipa, Graham Holmberg and Ben Smith. Throw in Panchik and Josh Bridges (who have each done extremely well once), and those are basically 7 guys who are very strong (Matt Chan probably fits in there somewhere but it's tough to say this year as he recovers from injury). But notice there are no Games rookies anywhere near the top in my predictions, and remember this is almost entirely based off the results from THIS SEASON.

      For women, without Annie or Julie Foucher this year, the only athletes consistently at the very top have been Rebecca Voigt and Kristan Clever, and Clever is a big question mark this year. But then you have a bunch of others who seem to be on the rise (Camille, Lindsey Valenzuela, Elizabeth Akinwale, Talayna Fortunato, Sam Briggs) plus people like Valerie Voboril who have had some really strong years. Someone like Amanda Goodman or Michelle Letendre could pop up near the top this year, too.

      Sorry, that was a long answer - I guess just the first sentence would have sufficed.

  2. Hey, this is great! I've only skimmed so far but love what you've done here.
    I ran across your blog because I was curious if there is a way to download or gain access to the entire CF Games database; is there? Specifically I want to do some data analysis on all the athletes with a tool like Tableau to look at correlations to things like previous athletic experience and other variables.

    Keep up the good work keeping Crossfit nerdy! ;)


    1. E,

      Thanks for reading, glad you're enjoying my take on the sport. The short answer to your question unfortunately is no, there is no way to access the entire CF Games database. There are ways to pull the data from the outside, often by writing scripts to do it for you. I found .csv's of last year's Open results here:

      This year, I do not believe the person who pulled that data (Jeff King) did the same thing this year. However, I was able to get all of the Open results by copying and pasting the entire leaderboard (I figured out how to expand it beyond 60 rows at a time), but that doesn't include any of the personal info. Someone else helped me get a hold of a more detailed dataset of the Open, but I'd have to check with him before passing that along to you. Send me an email if you are interested in that and I can put you guys in touch.

      As for Regionals and Games results, I just had to copy that stuff straight from the web into Excel. Tedious at times, but it's the only way that I know of. Hopefully HQ will eventually make the data more easily accessible.

  3. Very cool analysis! Try your luck on our 2013 CrossFit games competition where you choose the Top 10 male athletes in order. Free to enter would love to see you or your readers use the mathematical approach to win this thing!

    1. Thanks for reading. Cool competition you've got going on. I'll throw my name in, but just because I went the analytical route doesn't mean I'll come out on top. There's a bit of an NCAA Tourney feel to the Games where things never turn out quite like you expect (except Rich will probably win).

  4. Just curious how you were able to get the data for this? I really wanted to run some analysis on ideas I had.

    1. Well the regional data I pulled from the Cross Regional comparison (can't remember the website offhand, may have been mentioned in my methodology post). Open data I was able to copy from the Games site after messing around with the URL a bit in order to get more lines to display at once. I generally just pasted into Excel and then cleaned it up from there. So nothing I used here wasn't publicly available, but aggregating it can be a pain.