Category Archives: ADHM

Race Start Logistics – Chaos, Flow and Entropy

Should you really be up front in the crowd at the start line?

Have you ever run one of the big races in India like the Standard Chartered Mumbai Marathon (SCMM) or the Airtel Delhi Half Marathon (ADHM) and had varying experiences about the ‘flow of crowd of runners’? As the number of racers has grown and the increased focus on logistics for handling them has tried to avoid making a mess and avoid a human catastrophe, I have been curious about the flow of runners at the start and its subsequent impact along the route. Today’s conversation, with some interesting pictures, is about that. Takeaway lessons for you, racer, pacer or race organizer, will come soon.


I will first talk about the distribution of runners and how it transitions from start line to finish line. I then introduce you to my idea of ‘disorder’ in a race, with a measure that I call the Race Entropy, and show how that beautifully captures the flavour of the ease of flow within a race. I use the case of the Mumbai races (SCMM) to show how start-enclosures have helped with achieving less disorder (but significant room for improvement exists). I also show what impact the extreme pollution scares in New Delhi last winter had on the race that was held at that time (ADHM2016).

Gross Time, Net Time, Mat Crossing Time

I have shown you numerous graphs in the past of race finish times. These are typically histograms of ‘net finish times’ that show how many runners cross the finish line within each time bucket, where each bucket might be just a few seconds wide. What you will have probably never seen until today is a similar picture of what happens at the starting line.

How do we spread ourselves out over time?

Because not everyone crosses the starting line at the same time, there is a ‘spreading out’ or ‘distribution’ over time of runners crossing the starting line. This distribution is what leads to the need for recording gross finish time and net finish time.
The gross time is based on the natural clock time – the same clock for all the runners.
The net time is the specific time taken for each individual runner measured as, starting at their specific start line crossing (time = 0) and ending at their crossing the finish line.
Many races have RFID timing sensors placed under mats over which runners pass at the start/finish line, and so we often use the terms ‘starting line’ and ‘starting mat’ interchangeably.

Easing Flow

If your race’s logistics are handled smoothly, the fastest runners would be placed right up front at the start line and the slowest runners placed towards the back of the crowd. In the extreme scenario of the runners being released in descending order of their speed, in the hypothetical situation of constant speed for each runner, the number of ‘overtakings’ would be 0. No one would overtake anyone despite everyone running at their race pace. This would ensure a smooth flow of humans across the starting line and thereafter.

Smooth flow of runners ranked in order of speed

In practice, although it ‘feels good’ to overtake other runners, the truth is that it always involves some risk. Besides the physical risk (of impact) if the runner being overtaken sends you negative thoughts as you try to glide past him, that cannot be good for your soul.

Consider now, the worst situation for race start ordering, the slowest runner being placed right up front and the fastest runner at the back of the pack. In the extreme situation of N runners placed in such a reverse order of their speed, the fastest runner would have to overtake N-1 other runners to finish 1st. The runner who comes in second would have to overtake N-2 runners to come in 2nd. And so on for all the other runners… And, therefore, {ignoring the school maths proof}, the total number of ‘overtakings’ for all N runners would be ½*N*(N-1). Let us call that measure MaxPossibleOvertakings – e.g. for 10,000 participants placed in this reverse order MaxPossibleOvertakings will be 49,995,000.

Flow disrupted when runners not ranked in order of speed

For any given race with an actual ordering at the start line, we can also easily add up the minimum number of ‘overtakings’ that would have led to the actual finish ranking observed. Let us call this MinPossibleOvertakings.

Having defined a measure for the actual starting/finishing rankings of runners and the theoretical measure with maximum disorder, let me now tell you about what I call the ‘Race Entropy’ of an event. If numbers or equations faze you, hang in there, there’s nothing particularly complicated in what follows.


Borrowing from Thermodynamics, I define the measure of disorder in a race as being the ratio

Entropy – a measure of disorder in your race

If the runners are released in the perfect ranking of their eventual times, so that there will be no overtaking, the Race Entropy will be 0.
If the runners are released in the perfectly reverse order, the Race Entropy will be 1.
If the ordering is purely random chance, the Race Entropy will be approximately ½.
We hope that the Race Entropy for any race will be less than ½ and closer to 0.

Start-End Ranking Plot

We can also visualize this order and disorder with what I call a Start-End Ranking Plot – a rank for crossing the finish line plotted against the rank for crossing the start line. This example plot shows the two ends of [1] perfect order and [2] perfect disorder as well as [3] the case of purely random start ordering.

Start-End Ranking Plot: Avoiding disorder or wrong order is a worthy effort

Start-End Ranking Plot: Avoiding disorder or wrong order is a worthy effort

With this distilled single measure of disorder, Race Entropy, and the Start-End Ranking Plot, let us now examine a couple of interesting stories from the Indian recreational marathon scene.

Case 1 – Chaos to Order: Introduction of Enclosures for SCMM

The first year that I happened to run a distance race, quite by chance, was the flagship Mumbai Marathon in 2010 (SCMM2010). I remember being at the start line and witnessing the undignified pushing and jostling. It was pretty much ‘law of the jungle’ up there akin to the local trains I took to work daily. It was a free-for-all, first-come-first-serve type start, so everyone pushed up ahead, with no real attention to ordering themselves naturally by expected finish time.

Race Start Enclosures

Race start enclosures or ‘holding areas’ were first introduced to the Indian running scene in January 2012, at the Standard Chartered Mumbai Marathon. These enclosures, now common in the races with large numbers of participants, are set up with the philosophy that the fastest runners are kept together and typically go past the start line first, the slowest ones last, and the ones in-between following the same principle. In order to decide which start-enclosure you wait in before you start the race, race organizers request a recent race timing certificate from you at the time of registration. Based on this ‘previous timing certificate’ you, the customer, are allocated a start enclosure, specified visibly on your racing bib.

Pre/Post Enclosures

Start Enclosures help ensure reduced Race Entropy (disorder) despite an increase in competitors

If we examine the difference between 2010 & 2011 compared with 2016 & 2017 there is a noticeable reduction in Race Entropy despite the number of participants rising. Having seen the Race Entropy drop between 2010 to 2017 despite the massive increase in participation, we can see the Start-End Ranking Plot which corresponds to those numbers and the picture tells us the same story.

Comparing the Start-End Ranking Plot for 2010 with that from 2017 indicates a clear move away from high disorder towards greater order.

Population increase need not be a problem if mismanagement is replaced by better management!

Case 2 – Pollution Reduces Race Participation: Massive Reduction in Delhi Disorder

The flagship race of New Delhi, soon after the worldwide scares in the media about the city’s air pollution levels at the end of 2016, saw a massive reduction in actual participation on race day (ADHM2016). My simple but sensible estimation method tells me that 40% of those who had paid and were registered to race did not show up on race day. This is almost always fortunate for the race organizers and those who do show up to run. The race experience is always better for such large races when the turnout is lower {fewer people chasing the same resources including, quite literally, air, water and land}.

What did the fearless who turned up experience?

What is interesting is that the Race Entropy was so much lower (20.3%) than in 2012 (32.0%) when the ADHM first introduced start enclosures. It was also considerably lower than the previous year where in ADHM2015 the Race Entropy was 26.8%. Perhaps, the general time trend in Race Entropy shows that the running population itself is becoming slightly mature and sensible as a group about the race start. For ADHM2016, it is possible that a predominance of experienced runners showed up and many of the newer runners stayed away. Or, perhaps, managing fewer runners with arrangements for many more (who did not show up) induces lower Race Entropy (lower disorder). All my friends who ran ADHM2016 had a fantastic experience. As luck would have it the weather was (described by a mentee who ran) ‘absolutely perfect’ and my guess is that the reduced disorder added to a better overall experience.

Pollution Scares: Did the drop in crowding make humans more relaxed and reduce irrational crowding?

Once again, comparing the Start-End Ranking Plot for 2017 with that from 2012 when the number of participants was similar and start-enclosures had just been introduced indicates a clear move away from high disorder towards greater order.

Did the reduced crowd density encourage more orderly behaviour?

Summary and Way Forward

I introduced the concept of ‘disorder’ or Race Entropy to characterize the (lack of) ease of flow within a race. I showed how the introduction of start-enclosures based on ‘expected finish time’ helps reduce this Race Entropy (disorder). So, besides features such as aid stations, route marshaling, medal quality, pricing of race entry tickets, and post-race refreshments Race Entropy serves as a superb single measure to capture the overall race experience for those who turned up.

I will write again soon and provide guidance to you the racer, race pacer or race organizer based on this dimension of analysis.

Until then, try to not bump into anyone 🙂


Dr Purnendu Nath spends his waking hours focusing on helping individuals and organizations reach their goals, to make the world a better place. He speaks, writes and advises on topics such as finance, investment management, discipline, education, self-improvement, exercise, nutrition, health and fitness, leadership and parenting.

Are Recreational Marathoners in India getting Faster?

Is that random runner getting faster?

A Fundamental Question

The same person running the same race, a year apart, what percentage of runners would have improved their timings?

Before I begin to answer that question, and suggest ways to incorporate my findings into your life, I’d like you to close your eyes for 10 seconds and make a guess yourself. I asked this question a few days ago in my quick update on quality and quantity performance numbers of the Standard Chartered Mumbai Marathon.

The Opinion of Casual Experts

I’ve already talked to you about why you need not run. I’ve also explained why I don’t really care about your podium finish (or mine). But now, pick someone, let’s call him/her “R”, who ran a race two years in a row. What’s the likelihood that R improved between one year and the next?

When I asked a bunch of experienced marathoners in Mumbai what they thought was “the proportion of runners who ran the same race in successive years and improved their race timing”, the overwhelming response was along the lines of “the majority would have improved their timings over the previous year”. Within this ‘expert sample’, their gut response for what percentage improved varied significantly (already a warning sign if you are trying to fish out facts from noise). And the vast majority of those who responded had significantly high percentage estimates. Now, let’s not forget that if x% improve, then 100-x% must get worse. So if 80% improve then only 20% got worse in consecutive years. Likewise, if 20% improved, then as many as 80% got worse in consecutive years.

Cognitive Biases and Why we need to Dig Deeper

Every year most of my friends who run seem to get faster. Hang on, wait… do they really? One of the primal traits of humans that has allowed our species to evolve wonderfully is our ability to put together sketchy information to reach conclusions that help us both survive and thrive. Our ancestors avoided predators or extreme weather by observing sketchy evidence and reaching (usually correct) conclusions to escape or seek shelter. They also thrived by figuring out weather patterns for growing crops or navigating their way home from a hunt. Seeking out patterns to reach conclusions works well in some domains, not in others. The human cognitive bias “confirmation bias” makes us seek out and pay extra attention to evidence that “confirms” our beliefs. Some of us would like to believe that we get better over time if we just keep training for longer. The human cognitive bias “representation bias” nudges us to reach population wide conclusions based on small bits of evidence. For instance, if we had a bad year of racing, we might be more likely to think that others too would have had a bad year. But anecdotal evidence does not work well in the court of science. Let’s look at some hard facts.

What do YOU actually think?

Public Perception of Improvement is Diverse

Public Perception of Improvement is Diverse

When I posed this question a few weeks ago, hundreds of you responded as shown above. As you can see, there’s a lot of variation in the public’s perception of how a runner will perform from one year to the next. Now, remember, I did not specify any more background. That means we do not know for any specific runner how well the person trained through the year. The question I posed was to gather a sense of what we think about running improvements over time, keeping other real-life variables relatively constant. Given the wide range of responses, suggesting a diverse range of perceptions, it will be useful to look at what actually happens in India when it comes to improvements in recreational distance running. Let me now show you what has actually been happening.

What is “Improvement” anyway?

Throughout this discourse I refer to “improvement”, “faster”, “race times” etc. all being loosely synonymous with “improvement”. As a recreational distance race is ultimately a race, and predominantly against oneself, it is not unfair that I use these terms interchangeably. This does not take away the valour required to simply attempt to match the same race time one achieved in the previous year, let alone the effort it takes to beat it. Having said that, all things being equal, one usually expects that even semi-serious recreational runners will better their times in successive years as the training effect of a year on our exercise physiology is typically stronger than the deterioration arising from ageing by a year. [This may not be the case with someone who has been running seriously as a recreational marathoner for 30 years (like my regular Sunday long run buddy with a half marathon PB of 1:12) but is definitely expected to be the case for someone who is far down the road in their adult life and has taken up distance running in the last few years (like I have!). The vast majority of the recreational distance running population in India is more like I am – we expect to see improvements, year-on-year. Sounds all good in theory!]

Controlling Factors and Benchmarking

CPRP - a near-perfect benchmark measurement unit

CPRP – a near-perfect benchmark measurement unit

If we want to know how people improve over time, probably the most valuable metric we can look at is the same person running the same race in successive periods. There will be variation because of weather conditions on different days, and because of the idiosyncratic time-variation in training/lifestyle of each and every individual runner. But looking at thousands of such runners, across such consecutive period race pairs (CPRP), should give us a pretty good idea of how things are trending. I examine such consecutive-years runner-specific changes in net-finish-times to help us understand where we are going with our training as recreational distance runners in India.

Focusing on the largest race in India

I focus my attention on the Standard Chartered Mumbai Marathon which is the largest distance race in India as measured by the number of participants in the half and full marathons. In the 7 years between 2010-2016, even as the total number of finishers increased, the mean (average) and median times of those who completed the event varied as shown in my previous article. Now let’s look at the case of individually identified runners from all these editions of this race.


I identify each and every runner who ran across the start line of the Standard Chartered Mumbai Marathon in the last 7 editions (2010-2016) for either the half or the full marathon. For each runner in a given year, I match his/her time in the following year’s race. I then identify those runners who ran the half in successive years, or the full in successive years. Each of these runners is a CPRP. The change in their net finish time provides a nicely controlled measure of improvement, or lack thereof, in athletic performance. I condition for gender, and I condition for age bands – “open” and “veteran” {women > 40 years and men > 45 years}. I ignore the small number of DNF (Did Not Finish) without affecting the results as, even for the full marathon, they are a tiny percentage.

High Failure Rate in Improvement

Improvement is far from being a sure shot!

Improvement is far from being a sure shot!

There were 50,719 consecutive-period race pairs (CPRP) for the period from 2010-2016 across all age groups, both genders and both the half and the full marathons. For all of these observations that represent a significant proportion (37%) of racers, a whopping 44% had worse race times in the subsequent year than in the benchmark year. The remaining 56% did better. It is worth your while to pause here and think about what this means. For the population at large, it translates into “even as you train, as the years go by, if you continue to train without significant thought, your chances of apparent improvement aren’t really much more than 50-50!

Breaking it Down Further

The headline grabbing stats above hide a lot of the story of course. There is the trend over time (runners improve with training, but runners also peak and then often stay in “comfortable, recreational, maintenance mode” for years thereafter). Women often show greater determination for endurance activities (documented in non-Indian populations, but I’m sure all my running sisters in India won’t disagree that it’s universal). Older runners often show greater maturity towards the process of self-improvement (somewhat of a selection bias) and might show better relative progress than the much younger, enthusiastic but less-dedicated, runner. Improving one’s full marathon time might prove to be much more difficult, or at least, more uncertain (given the scaling up of distance and the associated risks) than improving one’s half marathon time. Anyway, rather than provide explanation and story about all these factors, what I would like to show you are the numbers broken down by group.

You can find the tables and graphs on this page.

Hey Guys! Where are we going with all this running around?

So, we’re all running around a lot, but where is it taking us? If you step back, the broad results we see begin to make sense. If you replace the running population with a single representative runner, you expect to see the following. Initially, a lot of improvement year-on-year. The rate of improvement will slow down at some point. There will come a point when, in a steady state, the experienced fit runner in trained state will have to work hard to maintain the same peak performance. That will mean beating his previous year’s performance half the time, and being unable to beat it the other half of the time. Note that once you are operating at the limit, the ability to beat a well-constructed benchmark is typically 50-50. If you found it almost impossible to beat the benchmark, or beat it almost all the time, then that is the sign of a poorly defined benchmark. Also, if your benchmark is last year’s performance (as is the case with CPRP) and you don’t make any real progress over the period to the next race, then there will be a natural mean-reversion (tendency to return towards the average after moving away from it) where, if you were lucky enough to have a good benchmark year by chance, it is highly likely that you will have a bad subsequent year, and vice versa. That effect is quite clear if you examine the coloured columns in the table below. We have the green runners who improved from NetTime1 to NetTime2. We have yellow runners who worsened from NetTime1 to NetTime2. What is relevant to note is that when NetTime2 was an improvement for the green runners, it was because last year’s NetTime1 was poor compared with the yellow runners. When NetTime2 was a worsening for the yellow runners, it was because last year’s NetTime1 was better than for the green runners. With improvement rates of near-50% perhaps there’s no real improvement in either set of runners – each set just happened to fairly randomly underperform last year and randomly outperform this year or vice versa.

The ones who did better this year were just awful last year and vice versa

What does that mean for you?

Whether there is real improvement or not, half the runners in the population appear to improve in successive years. Whether real or not, half the time a given experienced runner is appearing to improve between one race and its subsequent edition. The true rate of improvement slows down and pretty much stays steady, followed by age decline (a slow effect). And then there are some runners who continue to make progress year-after-year, and then manage to maintain high performance for many seasons. They then decline very gradually over time, as they age. It is the behaviour of this (small) group of runners that interest me. For you, the question that will be worthwhile thinking about is “what is it that these more successful runners do to improve over time and then maintain their level of performance?” Please, please, please note, I am not referring to fast runners. I am suggesting you emulate the behaviour of those runners, slow or fast, whose progression over time is admirable. Emulating that behaviour, be it training methods, nutrition, rest, psychological training (motivation and stress control) or race strategy, will lead to continual improvement (or reduce the probability of worsening rapidly) for you too.

And, so, no matter what your runner friend is doing this year or next year, it makes sense for you to pay heed to my favourite quote from my favourite movie star role model, Bruce Lee.

If you always put limits on everything you do, physical or anything else. It will spread into your work and into your life. There are no limits. There are only plateaus, and you must not stay there, you must go beyond them.”


Dr Purnendu Nath spends his waking hours focusing on helping individuals and organizations reach their goals, to make the world a better place. He speaks, writes and advises on topics such as finance, investment management, discipline, education, self-improvement, exercise, nutrition, health and fitness, leadership and parenting.

Why you need not run

There is no need to run

Three wins in a month, but I believe there is no need to run

About a year ago, I told you why I don’t care much about your podium finish, or mine! Yesterday I won my third distance running race for this month of October. But today I am going to chat with you about why you need not run.

Running could be part of your life – but it need not be

Perhaps you have been running for years.  Or perhaps you are new to recreational running.  Or it might be that you have been thinking of taking up running for some reason – a sudden health shock, or perhaps you noticed your clothes don’t fit like they used to because you’ve piled on the pounds. Running could be part of your life – but it need not be.

I do not encourage others to run

The global growth in recreational distance running has definitely reached many shores and is growing strong. Those who have seen me run, think that I am a huge proponent of it.  In fact, quite the contrary is true. I believe I am an excellent coach when it comes to guiding anyone to better running performance. But whenever I am approached by someone who wants to avail of my mentoring for living a better life, but does not currently run, the first thing I do is dissuade them from running. Or whenever someone asks me for my opinion on running longer races, I try to turn them off the idea. Here is why…

Back to basics

If you remember, I spoke with you earlier about What is Fitness Anyway? and then later about Skills Based Measures of Fitness being BS CRAP. Well, nowhere in those chats did I specify that one needed to run to be fit. Yes, one can try to get fitter through running and running does have numerous benefits to our overall health, including mental health, that have been well-documented. But, running is nowhere close to being essential for excellent health or quality of life or even improved life expectancy.

Risk and Reward

As a quantitative trader, I appreciate that just about every human activity (usually pursued for some upside or benefit) has with it a downside or potential cost. We need to think about the details. What are the risk adjusted benefits of running that next mile and what might be an alternative optimal path you could follow?

If we approach this problem from the perspective of the health based measures of fitness, then for:

Cardiorespiratory Fitness – any activity that gets your heart rate sufficiently high with physical movement could suffice. To the list of possibilities, you could include swimming, brisk walking uphill, cycling, dancing, stair climbing, the cross-trainer, the list is literally endless. You do not need to run to improve cardiorespiratory fitness.

Muscular Endurance – the same list of activities that help improve your cardiorespiratory fitness could be used for muscular endurance. In fact, you could possibly target a wider range of muscles with some of these activities than you could with running, and perhaps with better balance between your upper and lower body.  In addition, many of them (think “dance”!) will focus on one or more skills based measures of fitness too.

6 packs despite running, not because of running

6 pack despite running, not because of running

Body Composition – that running for hours every couple of days will make you look toned is a terrible myth that seems to lose no dominance in urban minds. Running longer will make your legs stronger for running longer (endurance), but being a catabolic activity, there is no guarantee that you will lose your love handles. Don’t believe me? Well, let us flip this around and you can prove it to yourself. Go stand at the finish line of a full marathon or a recreational urban ultra-running event – do all the runners who finish look ripped? I know they don’t!

Flexibility and Muscular Strength – running itself does not target flexibility and although it improves muscular strength in some areas, the improvement is marginal.

Let us now look at some of the other benefits of running:

Runner’s High – this invariably arises from the release of a combination of Endorphin, Serotonin, Dopamine, Adrenalin.  Well, you could get this from any of the other activities too. In fact, besides sports, Endorphin, the “happy hormone” is released during sex or even when you eat spicy food but most typically when you are in sudden pain or injured!

Although it sounds like I am trashing running, I am not.  I love running but I do not ever let it take up centre stage in my life for more than a few minutes a week. Going by my blog’s tag line, I think about how much I ought to run in a systematic manner that is best described by this graphic.  I believe that it applies to you too, elite athlete or couch potato:

Think about where on this scale is best for you

You could first use this graphic to think about your various measures of fitness (see above) and running’s relevance to them. You could ask yourself to what extent running is the only option (hint: almost never ;-)) to achieve a specific goal or benefit. Do you realize that going from couch potato to running with inappropriate progression is riskier than not running at all? You could ask yourself “To what extent does being at a specific point on this scale affect my physical, mental or emotional state negatively?”  Are you increasing the production of the stress hormone Cortisol by running too much and too often when, in fact, you took up running to reduce the impact of stress from urban living in the first place? Is the social benefit of running (having better friendships) being compromised because you are running too much? In fact, are you running just to keep up with the recent fad in recreational running without thinking about the alternatives for good health? Did you consider that, all else being equal, how much you ought to run for a specific goal is a function of both your age and gender? Given that an extra hour of sleep is significantly more important than an extra hour of running, are you getting enough sleep? Since you need fuel for your existence and activities, is what you are eating correct for the running you are doing or are you expecting your running to take care of bad eating habits?

Bikini Body Wanted, No Running Required

Recently I mentored a middle-aged client who had little success with “celebrity trainers” at achieving a bikini body. With me she achieved this with no running! Did we do things to improve her cardiorespiratory fitness? Of course we did. The point is, running was not essential to achieving her goals. Like activities such as yoga, pilates or weight training, running too is just a method. A method to better health. Don’t have madness in your method!

Hey! There’s a simple question for you at the end of this, don’t forget to scroll down and click to let your voice be heard!

And now, I’d like your (anonymous) opinion please?


Dr Purnendu Nath spends his waking hours focusing on helping individuals and organizations reach their goals, to make the world a better place. He speaks, writes and advises on topics such as finance, investment management, discipline, education, self-improvement, exercise, nutrition, health and fitness, leadership and parenting.

2-hour Pacing Strategy for the Airtel Hyderabad (Half) Marathon 2015

Your 2-hour pacer for AHM 2015

Your 2-hour pacer for AHM 2015

Earlier this year I presented to you my 2-hour pacing strategy for the Standard Chartered Mumbai (Half) Marathon 2015. Now I’m happy to present to you the strategy that my star mentee, Shailja Singh Sridhar, will follow as an official 2-hour pacer for the Airtel Hyderabad (Half) Marathon on 30 August 2015. I wrote about her in a previous article and since that time she has only grown from strength to strength.

The terrain and weather conditions form the primary factors driving the difference between the race in Mumbai (January) and Hyderabad (August). In fact, both the median and mean times for the Hyderabad (half marathon) are about 10 minutes slower than the equivalent in Mumbai. This overall population difference statistic is for a variety of reasons, but the key point to note is that Hyderabad is generally a slower race.

Hyderabad Half Elevation Map - Click to Enlarge

Hyderabad Half Elevation Map – Click to Enlarge

Hyderabad Half Route Map - Click to Enlarge

Hyderabad Half Route Map – Click to Enlarge

The usual word on the street is “Hyderabad is tough, too many flyovers” and so the pacing plan I present here is based on the changing terrain – elevation up/flat/down segments. Running based on “effort” rather than “pace”, you will naturally slow down during the up slopes and have a faster pace during the down slopes. And, in the final few hundred metres, most 2-hour runners push their pace to the finish. I also present the desired splits for two types of runners (a) the “Average” runner with slightly positive splits (slightly faster first half) and (b) a “Strong” runner with slightly negative splits (slightly faster second half). You can decide how you want to run between these two types of runners. Even if you meander between them during the race, just make sure you start with, and finish with or before, both of them.

Use me! (click to enlarge and PRINT)

Use me! (click to enlarge and PRINT)

You can print out the graphic, cut it out, and make a wristband out of it.  Or you could write some of the key numbers onto your forearm with waterproof ink.

I advise you, whether pacer, race organizer, wannabe pacer or race runner to also read my article on the matter of pacing to better understand how to make the most of this useful facility that is now a part of most public distance-running races.

I wish you well for your days of tapering to race day. Have a safe and fun run in Hyderabad!


Dr Purnendu Nath spends his waking hours focusing on helping individuals and organizations reach their goals, to make the world a better place. He speaks, writes and advises on topics such as finance, investment management, discipline, education, self-improvement, exercise, nutrition, health and fitness, leadership and parenting.

Mumbai vs Delhi – A Race Time Model

Hey! There’s a simple question for you at the end of this, don’t forget to scroll down and click to let your voice be heard!

Mumbai vs Delhi – A Race Time Model

Indians who have lived in either or both of Delhi and Mumbai will at some point make a comparison between the two cities and you’ll know why they have a strong preference for one over the other. Even expats in India who have lived in one and visited the other will express fairly strong opinions about one or both cities.

As a recreational distance runner, I am well aware of the claims that are made about the Airtel Delhi Half Marathon being a “faster race” than the Standard Chartered Mumbai Marathon. Both are held in the winter, with Mumbai scheduled for the third Sunday of January, and Delhi some weeks before that. In my life as a hedge fund manager, what mattered was not just how well you performed but also why your performance was the way it was – how much was from your effort or skill, and how much was just luck! Your time in a race will be a function of many things on race day, some that are to do with you, others that are to do with various features of the race itself.

The Question
The question I set about to answer was “how much faster is Delhi than Mumbai?”. Internationally, there are rating factors, a single number between 0-100 (or between 0-1) that rate races based on a given set of factors. However, I preferred to dig for a deeper understanding of Delhi vs Mumbai, the two most popular races in India. Would you like to know how much slower (or, perhaps, faster!) you will be in Mumbai than in Delhi? And how does that vary based on whether you are a 1:30 half marathoner as opposed to a 2:30 half marathoner?

Data & Methodology
Ideally, to make a comparison, you would like the weather and the course for both races to be the same every year – they are not. You would also like the same runners to participate in both races with the same level of fitness and race motivation. Often your motivation for one race is to “push hard” for the other it is to “do an easy pace”.

So, practically, I identify runners who ran both races a few weeks apart and thus am able to work with differences in race time for the same runner in both races. By using multiple race years and thousands of runners I hope to iron out any statistical variations and glean some useful information from the data.

Looking at the 6 races in Delhi from 2009 to 2014 I could identify 5,525 individual runners (by name, gender and age category) who ran both Delhi and Mumbai in any given season. From these records, obvious outliers were removed, many of them because it was clear that they ran the half marathon in Delhi but the full marathon in Mumbai a few weeks later.

Race Specific Backgrounds to Bear in Mind
There are features of the races that are specific to the comparison.
Time of Year
The Delhi race is earlier in the primary racing season, which for the main and older races in India happen between the end of the Monsoons and culminate with the race in Mumbai. Of course, fortunately, there are races in India all through the year now but the premium races are bunched in the period between October and January.
Delhi is colder in Nov-Jan than Mumbai by a noticeable margin. (The “historical average low” in Delhi in November is about 8 degrees Celsius lower than that of Mumbai in January). It is also less humid in Delhi than in Mumbai for the most part. One notable exception is the year 2012 when the Delhi race date was, annoyingly for most runners, brought forward to September! I will tell you how this too impacts the answer.
The race route for Delhi is ‘pretty much flat’ whereas Mumbai has 2 noticeable inclines (the Bandra-Worli Sea Link and Peddar Road). In both cities, the races are held on motorable roads.

Because Delhi is reputed to be faster, what interests me is “what is the time difference (in seconds) between Delhi and Mumbai run a few weeks later?”. So, I define
TimeDiff = Delhi – Mumbai
using the race records of “net time”.

Thus, a negative value indicates that Delhi is faster than Mumbai.  A positive value tells us that Mumbai was actually run faster than Delhi.

Racing ahead
I shall tell you the details of what I did over many tens of hours (of programming, number crunching and analysis) when I present this research in a live presentation one day.  For now, what might interest you more are the primary findings. And, pictorially, this is what they look like.

Race Times in Delhi not always faster than Mumbai

Race Times in Delhi not always faster than Mumbai

There’s no single number
There is no single “Delhi is faster than Mumbai by X minutes” that paints a decent representation. In fact the slower runners in Delhi get faster by the time they race in Mumbai.

The relationship is far from linear
One might expect that, as we examine slower runners, the difference grows such that Mumbai (hotter, more humid and with inclines) becomes increasingly slower.  Not only do we find the converse to be true, but also that it is not linear. This general relationship is seen when bucketing the time differences by race time buckets. The effect can be easily explained by the fact that often (not always, but, in general) the slower runners are also newer runners or are the type that train to race only in the primary racing season. Thus, even as they peak towards the end of the racing season (ending with the race in Mumbai) their fitness levels improve and they actually run Mumbai faster than Delhi.

2012 – The dreaded Delhi Year
In case you had not noticed, I excluded the data for Delhi from 2012 because that is the year the race was held in September, in weather that was considerably hotter (by about 5 degrees Celsius) than Mumbai in January. The impact of that is evident in the race timings. Once you adjust for the difference in weather, Delhi looks less attractive than Mumbai to obtain a better race time. Also, for the typical runner there was even more time to improve between Sep-12 (Delhi) and Jan-13 (Mumbai). I suspect that the additional training time had a greater impact than the weather difference.

Adjusting for heat makes Delhi less special

Adjusting for heat makes Delhi less special

Racing to the finish – what might you conclude?
So, what might you conclude from this? Well, if you are an experienced runner, run Delhi to get your fastest time in India. If you are new to running, and train to race mainly in the Sep-Jan season, then Mumbai will not be particularly slower than Delhi. In fact, you might even race faster in Mumbai than in Delhi. In that case, unless you are a Delhi lover or live close to it, reduce your carbon footprint and race only in Mumbai.

So far, so good…so what?
All that I presented is what the data tells us.  But you are not a number! You can pay attention to detail and focus on your goals without labels, avoiding bottlenecks and working with discipline to get to that higher level you have never been at before. Never mind the debate between Delhi and Mumbai lovers!

And now, I’d like your (anonymous) opinion please?


Dr Purnendu Nath spends his waking hours focusing on helping individuals and organizations reach their goals, to make the world a better place. He speaks, writes and advises on topics such as finance, investment management, discipline, education, self-improvement, exercise, nutrition, health and fitness, leadership and parenting.