Use of Data Analytics in Running

It is rare when people get to combine their passions and I am super excited to share that I have partnered with?Tata Consultancy Services - North America?for the 2021 TCS NYC Marathon. This partnership allows me to professionally bring together my two great passions of data and running!

The race is coming up on November 7th, so I’m in full-blown training mode. I’m leaning heavily on the data collected while training to help measure my progress towards my goals and to predict my marathon completion time.

When I leave my house to run, I typically only take my phone and headphones. I step outside, turn on my music or audiobook, open the run tracking app, hit record and I’m on my way. I recently switched over from Runkeeper to Strava, as it provides me with more insights about my runs and includes some fun challenges in which runners can participate. Just a few days ago I took part in the Tata Consultancy Services We Believe We Can challenge on Strava. For every mile run, TCS donates $1 to Rising New York Road Runners.

My goal for the TCS NYC Marathon this year is to beat my personal record for time. My current record stands at 5:07:15, which occurred at the Marine Corps Marathon in DC on October 27, 2019. My average mile pace for that race was 11:44. I still remember that marathon really well – it started early morning – we couldn’t find breakfast around the hotel where we stayed. Oh, yea, it also poured like crazy about 80% of the time. Our feet were soaked hours before we actually started running. Not sure if the rain helped me run faster or slowed me down ??.

The mission for November 7 is to complete the marathon in fewer than 5 hours. I’ve gotten plenty of feedback from the community to “not start too fast” and focus on having enough energy to speed up in the later miles. This is much easier said than done because once you start the race with hundreds of other runners, the excitement alone gets you running extremely fast.

So, how do I use data in my training and preparation? Well, I track every single training run so I can gather data on number of miles completed, how fast was I running, and did I slow down significantly when I faced elevation? There are several other questions we can ask from the data to gather input into our training plan. I personally love setting a goal for total number of miles completed in a period of time, and then tracking it to see how close I am to that goal. I then break up the remainder into smaller targets to hit over the next few days or weeks. For example, in 2019, I decided to run 1,000 miles in a year and designed data visualizations that clearly showed how near or far I was from the goal. It works as a great motivator for getting you moving. I still remember that I got to December 2019 and decided to make it more difficult by adding a 12-pound weighted vest to the challenge. I had 100 miles left, and December in NYC can get a bit cold. Here’s a visual that I designed to report on the progress for the month.

As another example, on September 1, 2021, I set out to run 5 miles per day – EVERY DAY for the month of September. Some days I ran more than 5 miles - because it felt great, and I had the time. Other days - I stopped as soon as the 5 miles was complete. The total ended up being 175 miles for the month, which is more than I've ever run in a month.

For the next few weeks leading up to the marathon, my main focus is keeping track of my running pace, speeding up, and also avoiding injury. I plan to incorporate plenty of rest in between training runs to make sure I’m fully ready for the marathon.

I’d love to hear from others.

How do you leverage data when it comes to tracking your fitness goals?