2022 Games Rankings: Less Prediction, More Spreadsheet Fun
Let's get a few things out of the way.
- Trained statisticians & analysts take years to develop their processes & algorithms to predict their sport. I am not trained nor have I spent years developing the following.
- Predicting any sport has a measure of error. Predicting a sport where the competition changes year after year compounds that measure of error.
- The following rankings are less my predictions & more an nerdy way to pass the time while my family is out of town.
When I set out to develop a ranking system, I knew that there would be others whose predictions would take many, many variables into consideration, trying to address the huuuuuge complexity that is the sport of CrossFit.
I knew I didn't want to spend the time creating a redundant system.
I knew that I wanted to find a system that piqued my curiosity—if I wasn't interested in the question, I wouldn't be interested in finding the answer.
So, here we are. I have a system that is pretty simplistic, isn't redundant, & was exciting to develop.
I've written before about my disillusion with taking the Open & Quarterfinals at face value for ranking Games contenders. The tests aren't Games-level, aren't on-site, & aren't on a very specific schedule.
The one saving grace of the Open & Quarterfinals is their universality—every Games contender competed in the Open & Quarterfinals.
On the flip side, the Semifinal competitions are more similar in nature to the Games—e.g., harder tests, in-person competing, external schedule. However, aside from the two HQ workouts, Semifinals were not universal, with some Semifinals testing swimming, others testing handstand walking or Husafell bag carries.
The question I found forming in my mind as I considered the pros & cons of scores from all three events was this: how did athlete performance differ from Open/Quarterfinals versus Semifinals?
& what would happen if that change in performance was reapplied to Open/Quarterfinal scores?
To demonstrate what I'm getting at, here's a not-so-hypothetical hypothetical:
Let's say an athlete's Open + Quarterfinal rankings (oqscore) when ranked in his Semifinal suggested he would take 8th, & instead he took 1st. His oqscore was 2070 while the athlete projected for first was 630. Going from a 2070-caliber performance to a 630-caliber performance is an improvement of 69.57%.
In my world of big assumptions & simple statistics, I take that to mean this athlete does well competing in a crowd.
Methods
Though I began to cover them above, here are my exact methods.
- Find all Semifinals athletes' oqscores (worldwide open event rankings + worldwide quarterfinal event rankings).
- Fina all Semifinals athletes' predicted placement based on oqscore.
- Find all Games athletes Semifinal placement, oqscores, & predicted Semifinal placement.
- Calculate the change from an athlete's oqscore to the corresponding oqscore of the place that athlete took in Semifinal competition (e.g., athlete A has an oqscore of 450 & took 2 which was predicted to need an oqscore of 300 or less).
- Apply the percentage change to the athlete's Open & Quarterfinal rankings & sum them, resulting in an adjusted oqscore.
- Add to the adjusted oqscore the worldwide rank for the Semifinal clean complex & legless rope climb events.
- Rank athletes.
Results
MEN
- Justin Medeiros
- Jeffrey Adler
- Saxon Panchik
- Brent Fikowski
- Jay Crouch
- Willy Georges
- Ricky Garard
- Dallin Pepper
- Jayson Hopper
- Lazar Dukic
- Travis Mayer
- Patrick Vellner
- Henrik Haapalainen
- Cole Sager
- Guilherme Malheiros
- Tudor Magda
- Noah Ohlsen
- Spencer Panchik
- Alexandre Caron
- Cole Greashaber
- Andre Houdet
- Alex Vigneault
- Roman Khrennikov
- Samuel Kwant
- Giorgos Karavis
- Bayden Brown
- Guillaume Briant
- Bjorgvin Gudmundsson
- Will Moorad
- Austin Spencer
- Jonne Koski
- Moritz Fiebig
- Uldis Upenieks
- Kealan Henry
- Nick Mathew
- Enrico Zenoni
- Colten Mertens
- Agustin Richelme
- Timothy Paulson
- Arthur Semenov
Notes:
Looking at the men's field, right off the bat I think BKG, Noah Olsen, Roman Khrennikov, & Colten Mertens are ranked too low. In BKG's case, his oqscore was so far ahead that the adjustment down for his 2nd place crushed his total score. Though Khrennikov was predicted to take first & took first, I suspect his rank is low because he hasn't needed to push himself in his region.
WOMEN
- Tia-Clair Toomey
- Mallory O'Brien
- Laura Horvath
- Haley Adams
- Jacqueline Dahlstrom
- Alexis Raptis
- Danielle Brandon
- Kara Saunders
- Amanda Barnhart
- Paige Semenza
- Kristi Eramo O'Connell
- Sydney Michalyshen
- Ellie Turner
- Karin Freyova
- Matilde Garnes
- Gabriela Migala
- Baylee Rayl
- Christine Kolenbrander
- Emma McQuaid
- Emma Lawson
- Dani Speegle
- Lucy Campbell
- Alex Gazan
- Thuri Helgadottir
- Victoria Campos
- Paige Powers
- Emily Rolfe
- Caroline Spencer
- Arielle Loewen
- Solveig Sigurdardottir
- Elisa Fuliano
- Julia Kato
- Freya Moosbrugger
- Elena Carratala Sanahuja
- Brooke Wells
- Rebecca Fuselier
- Seungyeon Choi
- Seher Kaya
- Carolyne Prevost
- Michelle Merand
Notes: Like the men there are some notable names that are ranked lower than I'd expect. Gabby Migala, Brooke Wells, & Emma Lawson are all athletes I'd predict to place higher. Migala's ranking suffered similar to BKG's: oqscore ranked predicted higher & the adjustment was likely too aggresive.
Conclusion
Though I like the general direction of this system for Games rankings, there are some definite bugs. First, an athlete that underperforms in Semifinals relative to their oqscore is at the mercy of the performance of other athletes. I don't like that. Second, there is still too much weight given to Open & Quarterfinal performance. Introducing a system to weight the Semifinal events heavier than the adjusted oqscore might balance that out.
Regardless, this year's Games is gonnsta be a treat. I can't wait to see how fitness is tested this year & which athletes rise to the top.
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