There was some back and forth on social media last fall regarding the efficacy of using new technologies like wattage meters or other stride measuring metrics in training. Some respondents suggested that such technology was either unnecessary or just plain gimmicky as a training aid. The counter-argument didn’t focus so much on efficacy from the athlete’s training standpoint (though there can surely be a benefit). Instead, proponents underscored how utilizing new technology in an action-challenged sport like running could assist in opening a new window into the inner workings of the sport to better educate the audience as to WHY the race was shaping up as it was.
Often, when commentating, we announcers make subjective assessments as to which athlete “looks better”. Splits, of course, tell their own story, but much of our assessment comes from years of watching scores of runners and races. But if athletes were fitted with non-intrusive stride metrics and internal systems measuring devices, like how a car’s dashboard shows RPMs, engine temperature, oil pressure, and the like, we could more precisely illustrate which athlete was working harder to produce this pace based objective data rather than a subjective eye.
There are other factors involved, of course, but the more information we can get to the audience, the better chance we have to engage their interest, especially in a sport where the action is repetitive, hard to differentiate, and moments of truth are generally relegated to a single move late in the race.
While watching 2020’s Elite-only London Marathon, I recall thinking that women’s marathon world-record holder Brigid Kosgei was carrying her left arm cocked up more than I recall seeing it in her other marathon races. She always carries her arms up high, yes, but not as rigidly held on the left side as I perceived her to be doing in London 2020.
At both her Honolulu Marathons (2016 – 2017) and at London 2019, I thought she was more fluid in her arm swing, as both hands swung easily across the body to the sternum midpoint, though, again, they were carried high.
First, was that merely my personal assessment, or was there really a measurable difference between Kosgei in London 2019 and in 2020?
If there was a difference, of what magnitude was it? Then, if discovered, was it due to some minor stride imbalance or a small niggle she was unconsciously compensating for? If we had stride and arm carriage readouts, we might be able to answer that question more definitively and in doing so, illuminate the subtle differences that can significantly impact a race.
In 2012, we recorded a 25-kilometer fartlek session along the Masai Land Road in Ngong, Kenya with the then world record holder in the marathon Patrick Makau. We attached tiny accelerometers to his shoes that measured stride length, foot roll, ground contact time, and distal leg (heel) lift.
Through the readouts, we discovered that Patrick did have an imbalance from one leg to the next. The minor compensation he made unwittingly to offset that imbalance eventually led to a chronic lateral knee issue.
Well, with the data gathered on that run, he might have been able to understand specifically why his knee hurt, and what he might do in terms of exercises or drills to help offset that imbalance. And if he did the same workout again over the same terrain, he could compare the data and see if his mitigations were working. That is how the athlete might benefit from technology.
Another year at the Los Angeles Marathon, we put similar accelerometers on the shoes of several top runners, and on-air in real-time we were able to monitor the same stride metrics that we had measured on Makau in Kenya.
After halfway, the readouts indicated that the ground contact time and distal heel lift of the defending champion had changed, suggesting he was pushing harder off the ground with each stride to maintain the current pace. I couldn’t see a difference with my eye alone, but the data indicated he was working harder than he had been earlier. When he fell off the pace one kilometer later, one could better understand why, because the metrics were predictive of outcome. That’s how a broadcaster might utilize such data.
Every sport digs into data collection to enhance performance and viewer appreciation. Running should, too.