Tuesday, 30 April 2019

Can marathon performance be predicted? - Tanda and beyond

I, and others, have made great play of Giovanni Tanda's marathon prediction equation. We have promoted it's use, both as a predictive tool and as a way of shaping training. Yet, it continues to fail for many people - they head-off at what seems an appropriate pace and fail. Whilst some claim it is the execution of the marathon plan that is at fault, and others simply junk the Tanda equation, I think the problem may lie elsewhere. First, I think that the Tanda equation is one of the best equations to predict marathon performance. It is simple to calculate and of all of the equations that I have come across seems to get closest to predicting performance, especially once it is customised to the individual. But, it still fails and can fail spectacularly. Some of those failures are easy to predict because they involve obvious changes in physiology that the equation cannot know about. Colds and infections a few days before a race can wreck the possibility of a decent performance. But, even in the absence of these obvious problems the equation can still fail. And, we should expect it to do so. The statistics tell us it will. The equation was derived from optimal performances - from a dataset of races where a near flat pace was maintained. The Tanda equation (with some individualization) represents the best that can be hoped for. For the best to happen many things need to align - not just the weather, course, pacing, grouping of runners but also a myriad of internal physiological and psychological parameters need to be in the right place. Executing a plan based on 'the best' happening is risky. And, given the cliff edge drop in performance that occurs with even a modestly over-enthusiastic pace, the most likely outcome will be failure. Before Tanda constructed his dataset, a number of performances would have been filtered out. These were performances where the training went well but one of a number of problems occurred to result in a non-flat pace. The result being that the equation is not a fit of what is 'most likely' to be achieved, but what happens when things go well. What many runners want to know is the probability that the prediction will work - and how to finesse that function so that there is a high probability of getting something positive out of the event. Many runners adopt an all-in or should it be an all-out approach. They have a primary goal and adopt an uncompromising strategy to reach it. Modelling this on a pay-out basis would be $1,000,000 for achieving the A goal and $0 for missing it. It is a binary approach which will occasionally work. This is often seen as an heroic approach with the massive detonation or collapse as a sign of willingness to push for the highest level of achievement. I do not doubt this is the case - and respect those capable of committing to this - but, don't blame the science when it goes wrong. You could, however, blame the lack of science. Risk distribution within a race is something we all instinctively engage with. Several times now I have listened to runners justify the collection of gels on their belts at the start of a marathon. Many believe them necessary, but the interesting ones are those people who suspect that the gels probably aren't - but, why take the risk of not having them? When running drafting is common - the closer the better. Now, there is a risk-based decision. How close do you get? When do you over-take? How close to the course edge can you run? The risk profile is important in knowing if the decision being taken is sensible. Your stomach rumbles and the sensations are present - but, do you stop at the portaloo or press on? At the London Marathon the risk is very different to that at a rural event - our nervous systems convolve probability and risk to arrive at an optimal strategy with no graph-plotting involved. Many risks we take, or should they be 'cautions' are instinctive with almost no proper conscious analysis. The problem here arises when the risk is non-linear, highly non-linear. The analogous game that comes to mind is what I think was known as 'Shoffe-Groat'. It can easily be played with a few coins and a table. The idea is to launch your coin towards the other end of the table, getting as close to the edge as possible. The winner is the person who gets closest to the edge without falling off. He or she takes all of the money either on the floor or on the table. Now, in the case of marathon running few people are playing against other players - people are competing with their PBs. By definition those PBs were the best performances - the ones where most things went right. Of course, if you don't have many performances, you may not be close to the limit. But, for anyone who has given the event a good few tests they are going to be close to the table-edge. Of course additional training can make the 'distance' between a previous PB and the failure that is represented by dropping-off the table a bit bigger. But, the space that you are trying to nestle into is tight. The odds are stacked against you. Now, the Tanda prediction - which worked for you before - is getting ever more difficult to achieve. The probability of success is dropping the more you train and the faster you go even though the prediction of what might be possible is correct - it is now simply that the number of times that the equation will 'work' is much smaller. Here is lies an interesting observation. The Tanda equation does not tell us the probability of success. It tells us that people who trained in a certain way have achieved certain times. But, we don't know how many times they have trained that way and failed. It is almost certain that the Tanda equation has a much higher 'success' rate at lower performance times than faster ones. And, this is what is misleading about it. Just because the equation worked before, don't rely on being able to use it to extrapolate your new training space to a faster PB. To be safe you will need to push your training further - that is your PB race pace needs to be executed at a level of fitness which is greater than what you are trying to do. Of course, you may get lucky and get the performance predicted by training. But, a more likely scenario is that you will get your PB and an underperformance relative to the equation - at least until you repeat it a few times. There is an in-race way of doing exactly this. It is the planned negative-split. Start the race somewhat slower than your fitness might warrant. At the appropriate time - and this needs discussion as to when this is - you ramp-up the pace carefully. If this is 'your day' you will sustain the ramp and get a very mildly disappointing time - not the best you could have done, but if you have put in the 'over-training' it will be the PB you wanted. If this isn't your day the ramp won't happen the best you will get is a flattish pace - it is the finishing time you deserved from your fitness and your 'luckiness'. As Alberto Salazar is claimed to have said; “If anyone goes out at a suicidal pace, I’ll probably sit back”.

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