“In God we trust, all others must bring data.” - W. Edwards Deming
Today every major decision is made by the insights provided by numbers dancing on our excel sheet. World of sports is no different. My Garmin provides so much data for each stride - cadence, left-right balance, stride length, vertical oscillation; the insights are mind boggling and offer quite useful feedback to tune my training. Now imagine 5000+ runners running a race like SPBM for hours, this worked as a fodder for a geek like me. Just a heads up, I have worked on the aggregated data published by race organizers for SPBM 2019. I have tried to come up with some interesting insights and would like to share.
Given the general assumption that running in India is gaining momentum in the last few years, I assumed the participation must be an upward trajectory but my assumption proved me wrong, the growth trend is flat.
Half marathon participation numbers have marginally increased from last year, marathon participation numbers took a slight dip.
Due to lack of data, I couldn’t compare it with other major marathons in India, but it will be an interesting comparison to understand if this trend is specific to SPBM or it is true with other races in India as well.
There has been a 64% rise from the inaugural year 2014, the ratio of men to women participation is dipping over the years. However, if you take marathon category separately, the numbers however remained flat. I only hope this trend is SPBM specific.
Runpeat’s excellent state of running 2019 report has put Women to Men running numbers across distances in India at 19:81.
For SPBM this ratio is bleak:
What can be done to improve this skewed ratio? (please share your views in the comments section)
Average finish timing related to India were not available, however global average for men marathon is around 4h:10m and for women is around 4h:39m per marastats.com. SPBM results show a lot of scope to improve. Here are the category wise average finish times for marathon distance.
Half marathon averages are not very different either. Global average finish times are 1h:53m and 2h:09m respectively for men and women.
These numbers probably also reflect on how we can structure our training throughout the year. It can also to do with how we take running - recreational, just to remain fit or take training seriously more on the sporting front. Do share your views in comments.
Interesting take away from the above numbers is the age category finish times. 45-55 years runners seem to be the best among the age categories for both men and women. 35-45 is the next best. Apart from average finish times, these categories also are the most popular in terms of participation. Interestingly these trends are inline with global trends reported by marastats.com.
Half marathon participation numbers also show similar age category distribution, [which are also inline with global trends] (https://marastats.com/halfmarathon/).
Another interesting insight comes from marathon finish times where runners are distributed in various time intervals, some of these are surprising and counter intuitive. I expected that runners would finish in time ranges according to pacing buses. For example, I was expecting more people would finish at 4h:00 than 3h:55m and 5h:00m than 4h:55m. However, to my surprise, more participants completed at 3h:55m than 4h:00m and 4h:55m than 5h:00m. I wonder why?
Similar observations could be made for half marathon’s finish time distributions.
Negative splits (finishing second-half of the race faster than the first-half) is a popular race strategy of elites. The most popular running strategy at SPBM is positive splits. Negative splits among the marathoners is almost non-existent. Just about 2.5% runners ran negative splits. Did weather on race day play a spoil sport?
I also wanted to understand if the negative splits are more popular with faster runners. I was hoping that runners who finish under 3 would have more negative splits. However, none of the participants are with negative splits in this time range. Most negative splits were finished between 4 and 5 hours. Probably that has to do with more runners finished in this time range than to do with any specific strategy. Clear trend however is that the positive splits are getting bigger with slower runners, while faster runners have smaller positive splits.
For Half marathon distance, the share of negative splits is not very different either, but is slightly better at 4.3%.
Finishers between 2 and 3 hours had the maximum negative splits compared to other finish time bins. As with marathoners, positive splits are getting bigger with slower runners.
As you can see in the scatter graphs, a few runners had negative splits by more than 15 minutes in the half marathon distance. Also few runners with 5 minute negative split in marathon distance. Wonder how one could achieve such a strong negative split?
Numbers can tell stories, but it is up to us to interpret the numbers and form hypothesis. Would really like to hear from you, your views and how you see these numbers. Please share your views in the comments section below.
I am also sharing the complete timing data which you can use for your own analysis.
[Marathon timing data] (https://docs.google.com/spreadsheets/d/e/2PACX-1vR7H-UyDMy-wDojhWxRuVQDBjdDe3MBjgscBKRfDxX88Nm-0xxGWzqc-BMmzravwTuKyQCAj8iTXu6k/pubhtml?gid=474776733&single=true)
[Half-marathon timing data] (https://docs.google.com/spreadsheets/d/e/2PACX-1vR7H-UyDMy-wDojhWxRuVQDBjdDe3MBjgscBKRfDxX88Nm-0xxGWzqc-BMmzravwTuKyQCAj8iTXu6k/pubhtml?gid=1537362082&single=true)
Aravind is a running geek, marathoner, and CrossFitter. He loves all things technology and technology in running, with special interest in running form analysis.
Edited by Aditi Pandya. Aditi is an avid runner, a writer and a fitness enthusiast. She is second runners up at Airtel Hyderabad Marathon 2019 in Women open half-marathon category.