In 2008, I saved the little bit of energy I had left in my tank to unleash a huge smile as I crossed the finish line of Ironman Lake Placid. I was overjoyed to have completed racing 140.6 miles, which included my first marathon. For six months, I followed a classic endurance training approach: base, build, peak.
Five years and three Ironman races later, I discovered the difference of power. Threshold tests, max aerobic tests and sprint tests became a regular part of my Tuesday and Thursday mornings at M2 Revolution Cycling in San Francisco. I knew my average watts. I relished if I could break 330 watts in the sprint test. I talked watts with my friends. And this attention to data paid off. Back on the same cycling course for Ironman Lake Placid in 2013, I finished the bike portion 23 minutes faster. The following year on a flat course at Ironman Maryland, I cut 29 minutes off my cycling time across 112 miles.
I was finally learning to embrace data to drive my performance.
Optimal performance driven by data
IBM recently began a project with US Cycling Women’s Team Pursuit to use real-time data collection and wearable devices to feed live performance. While many cyclists (like me) focus on speed, cadence, and power, new data-capture mechanisms such as BSXinsight enable the team coaches to collect muscle oxygen information and soon, psychology. They are feeding information back to the cyclists immediately after a workout and in real time during a race through smart glasses.
As USA cyclist Sarah Hammer put it, “They put in what kind of power do we need to produce… it is very simple color coded on whether you are in the red or you are in the green. Did you go too hard? Did you go too easy?“
This data-driven training and real-time feedback improve the cyclists’ efficiency, guide them on when to push more, and help them avoid the dreaded “bonk” when their tanks just run out of fuel. The results are impressive so far for Team USA: They took home the gold at the World Championships and are on their way to Rio 2016.
Applying data-driven training to weekend warriors
USA Cycling Coach Neal Henderson believes that most athletes train in the middle range of their actual intensity capacity. With all the data we have now from Garmin watches, fitness apps, wearable devices, and power meters, how could we athletes break out of our rut? How can we focus on the right data and break out of the middle rut to see real impacts on our performance?
Whether you’re a weekend warrior, a 10k enthusiast, an aspiring Ironman, or a regular podium finisher, there are a few essential tips we can all put into practice for data-driven training thanks to the work of USA Cycling and IBM.
- Focus on what is critical: “Sport always evolves, sport always changes,” Hammer said. “That is why records are always being broken. It is not necessarily that you have better athletes. It is that people are learning different methods. And if you are not up on that technology, then you know you are going to fall behind.”
- Inspect at your individual response: While you can compare your results across communities such as Strava, Runkeeper, and Fitbit, you’ll gain the most improvement by focusing on your own response and output. Imagine if we could all have dashboards like the one used by USA Cycling or feedback from our treadmill at the gym to help us meet our targets. Runkeeper is using IBM Cloud to layer in insights from Watson to its running training and routing.
- Be willing to abandon old models, use data to drive results: According to Team USA’s Hammer, “When you feel like you have the tools that you need it just makes you that much sharper.” I gave up on the traditional “base, build, peak” Ironman training model to focus on improving my cycling watts.
- Look for tools that improve your training and racing psychology: Coach Henderson believes that psychology can be trained. Can you become more motivated or more competitive? How can we infuse that mental training into our apps and get actionable insights from data-driven training? What will a cognitive fitness app look like in 2017?
I’m more excited than ever to map out my training plan for Ironman Lake Placid 2018. I can’t wait to see the results 10 years after my first race — once I’ve applied real-time analytics and individual responses to my training program — based on apps built on the IBM Cloud platform.
A version of this article originally appeared on the IBM developerWorks blog.
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