IWCABTAMD

Dr. Steven Platek and co. offer up data analysis showing increased performance in Fran, Angie, Cindy and the CrossFit Total.

Constantly varied functional movements executed at high intensity—this is CrossFit.

To create functionally fit individuals is a primary goal of CrossFit, and an efficacious way of measuring or operationally defining fitness is in an athlete’s ability to do more work faster and across variable domains over time—increased work capacity across broad time and modal domains, or “IWCABTAMD.”

For those of us who are embedded in the culture and the workouts, there is little skepticism about this method because we have loads of anecdotal evidence to draw on.
Anecdotal evidence, however, is just that: anecdotal. In order to show the efficacy of any treatment program, one must devise an experiment where progress is tracked over time. Individuals outside the CrossFit community often question the metric for measuring the efficacy of CrossFit. For instance, they’ll ask, “Where’s the data?”

In an effort to demonstrate evidence-based increases in performance, we conducted two small-scale post-hoc studies. In Experiment 1, we analyzed main-site posts for a benchmark CrossFit workout: Fran. These initial data, even in light of the myriad scientific and methodological limitations associated with our approach, still revealed statistically significant increases in performance (decreased Fran times) over time.

In Experiment 2, we contacted Bill Patton, the owner of LogsItAll, an online repository for CrossFitters to log their times, loads and performance and keep track of their progress over time. Bill was kind enough to provide us with a nameless version of his database, from which we extracted data for four benchmark workouts: Fran, Angie, Cindy and the CrossFit Total.

These data confirm the preliminary data from Experiment 1 with a larger sample size. In other words, people get quicker Fran and Angie times, complete more rounds of Cindy and lift heavier loads from doing CrossFit.

Radha Mitchell Melissa Rycroft Chloë Sevigny Janet Jackson Georgianna Robertson