Work Smarter, Not Harder.
As with most industries, technological advancement and the use of data is becoming a necessity in order to keep up with the ever-changing world. However, in the athletic performance realm, we are just now beginning to see the application of data becoming more apparent. There is no question that data and the use of statistics has already infiltrated its way into athletics. When listening to any sports reporting or broadcast, you hear and see examples on the screen all the time. What we typically see and are used to seeing in an athletic sense regarding data are examples like:
- The Capital’s Alex Ovechkin trailing Wayne Gretzky’s chart-topping career goals by 164 goals before the start of the 2021-22 season but having a higher goal per game average (0.6 vs. 0.61).
- While at Clemson the prolific Travis Etienne having rushed 686 times for 4,952 years with 70 rushing touchdowns and caught of 102 passes for 1,155 and eight receiving touchdowns in 1,852 career snaps over 55 games.
- Zack Greinke, who in 2015 posted a 1.66 ETA over 222.2 innings (6.94 IP/G) and kept batters at a .185 AVG, easily giving him one of the best pitching seasons.
With the advancement of technology and data analytics, we can collect, gather, and analyze so much data in game like pitching speed, angle of a golf ball, where in the goal a keeper is least likely to block, percentage of 3-pointers likely to be made given certain circumstances. The list goes on and on…
However, why don’t we see huge advancements of using data to influence the actual performance of the athletes? With the stronghold that athletics has on so many people’s lives, why hasn’t the “science” followed suit with the great stride seen in technology, medicine/health, and the comfort of making objective decisions through data analysis. That’s where the new and growing field of “Sports Science” comes into play.
Let’s start by answering the question—what is Sports Science? Sport Science is the application of scientific theory to sport, or the study of sport using scientific methods of inquiry in the fields of human performance, athletic endeavors, and sporting competition. To rephrase— it’s changing data from just random numbers to valuable information to support decision making and influence outcomes of human performance capacity for the specific purpose of maximizing performance. Maximizing performance could mean less injuries, more wins, being bigger, faster, stronger, smarter. I refer to the application of Sports Science data usage as working smarter, not harder to WIN.
Lots of teams have a plethora of data, but are unsure of what to do with it, the questions to ask, or the problems to solve.
Some cool questions I have been able to answer using data:
- Which Functional Movement Screen pattern is leading to the most injuries? Where are these injuries occurring?
Example: A Football program I worked with I noticed that a high percentage of our hamstring tears had the same Functional Movement Screen scores/patterns—mostly having failed in ankle mobility. Sharing this objective data with strength and conditioning staff, a quick ankle mobility and stability exercise was added a few days a week in the warmup. At the end of the spring ball season, hamstring injuries were significantly reduced.
- How do we know how “ready” an athlete is before a heavy squat day? If they are fatigued, should they be lifting the same amount of weight? How do we quantify this?