Biomechanical Hacking in Pitchers

The Early Days

In 2010, Motus was founded with the mission of bringing biomechanics to the masses. Where did it all start? In a mobile motion capture biomechanics lab. Tracing back to its very first MLB motion capture shoot with the Baltimore Orioles in 2011, Motus has always been on the leading edge of extracting high-quality, high-speed performance and injury data on athletes. Its first efforts were heavily focused on analyzing baseball pitchers.

Motus’ first mobile biomechanics data capture session with the Baltimore Orioles in 2011 at Ed Smith Stadium in Sarasota, FL.

A biomechanics lab can extract hundreds of measurements during a pitcher’s delivery. There are some pretty straightforward measurements like “stride length” and “arm slot”, but there are also some very ambiguous and complex measurements like “elbow Valgus Torque”—which can be equated to the external load on the elbow and Ulnar Collateral Ligament (UCL).

For decades, teams have been searching for the “holy grail” of predicting and preventing injuries in their treasured pitching staffs. As such, teams go to great lengths to capture data that shows potential to provide a link to injury prediction. Pre-wearable tech days, they would have biomechanics labs like Motus stop out in the spring, have their pitchers strip down to their compression shorts, get “dotted up” with 50 reflective markers, and throw to a catcher during a simulated bullpen. It’s a real-life scene from “Bull Durham”.

Breaking Down the Walls of the Lab

In an effort to bring biomechanics to the masses, Motus felt a need to bring less obtrusive technology to sports. In the Fall Instructional League of 2014, Motus launched its first piece of wearable technology, the mTHROW, and piloted it with 9 MLB Organizations. The technology consisted of a 3D sensor embedded in a compression throwing sleeve. Inside, were a high-end tri-axial accelerometer and tri-axial gyroscope. The smart sleeve recorded 3D data with every throw a pitcher made. From the 3D data, Motus applied their biomechanical algorithms to compute “Elbow Valgus Torque”—the external load on the UCL. Today, Motus has next generation versions of the initial wearable technology, motusTHROW, motusBASEBALL and motusPRO, and works with 28 MLB organizations.

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Advanced Workload Monitoring: Acute:Chronic Valgus Workload

The beauty of the biomechanical sleeve is that it allows users to monitor stresses from every throw made. The first step is to monitor daily workload on the elbow. Based on NASA’s “Daily Load Stimulus” (which monitors workload on bones), Motus adapted a ligament-based model that is a measure of total Valgus Torque on the elbow in one day.

Motus then computes a weekly workload, and a monthly workload. These two workloads help gauge the acute (weekly) and chronic (monthly) status of how much load a pitcher’s elbow has sustained. A growing industry of research has shown that large increases in acute workloads can place an athlete at a risk of becoming injured.

To take this a step further, the research shows that a high Acute:Chronic Ratio (A:C Ratio), Acute workload divided by Chronic workload, is a strong indicator of injury risk. An analogy of running a marathon is a great example. If you decided to pick up the sport of running your first marathon tomorrow, more likely than not you would get hurt. However, if you decided to train for a few months and build up a high chronic workload of miles ran per day, your chances at getting through 26 miles unscathed is much higher. In this scenario, your A:C Ratio would be under 1.5 (miles per day this week/miles per day this month).

A similar mechanism is at play when training pitchers with workload data. During the pre-season, all pitchers work on progressing their workload in terms of pitch counts or long toss distance (albeit the same progression for all pitchers on a team). Monitoring the A:C Ratio during the pre-season is crucial to on-boarding a pitcher for the regular season. When using the sleeve analytics, a pitcher can individualize their progression to ensure their ratio stays below normal ranges established by Motus’ research.

Valgus Loading Pattern of a MLB pitcher that lead to a torn UCL on day 83. The A:C Valgus Ratio peaked at 2.1 (Acute workload was 210% of Chronic workload).

During the regular season, a moderately high chronic workload on the elbow can be protective of injuries. In the example above, a MLB pitcher encountered a season ending injury. In the first half of the season, he built up a normal chronic/monthly workload, allowing him to sustain acute workload spikes. This led to peak A:C Ratio’s of 1.2. However, mid-season, the pitcher’s chronic workload dropped, and the same acute workloads he could tolerate early in the season produced A:C Ratio’s over 2.1. In this scenario, the forearm muscles became fatigued easier and more force was imparted to the UCL. Ultimately the pitcher sustained a torn UCL on day 83.

Machine Learning to Avoid Dangerous Workloads

With millions of throws captured on the elbows of pitchers, and a physiological-based injury model, Motus has learned how to guide a pitcher’s throwing regimen. Combining a pitcher’s throwing schedule, designated game-day, current A:C Ratio, and current Chronic (monthly) workload, Motus can program optimal training volume up to 30 days in the future.

Ultimately, teams and individuals can subscribe to motusDASH to receive these advanced workloads and projections powered by a machine-learning cloud server similar to the machine learning cloud computer- IBM Watson. The tool empowers coaches and trainers with powerful data-driven prescriptions that coaches can tweak given real-world practice and game schedules. The dashboard (seen below), gives teams alerts when pitchers get into dangerous training zones, and ultimately provides them with a throwing plan to get back into normal workload ranges. For more information on how to use and purchase this technology, please visit www.motusglobal.com.