Are Training Plans Dead?
In this latest article, coach Philip explores whether a training plan is now dead. He also looks into the rise of artificial intelligence and its impact on the sports industry.
With the ever-increasing advances of data-capturing devices, it is now possible to do and record so much more through a smartphone or smart device. Only a few years ago this was possible solely in the laboratory. Although there are still improvements in the validity and accuracy of the data set. However, most athletes are unlikely to care whether or not they were a few per cent off the distance for their Sunday morning jog. At the very sharp end, these small inaccuracies can mean a lot. However, these small inaccuracies are meaningless for most of the global population of active individuals.
With the advances in many of the ways of recording and tracking fitness progress, we have seen a growth in the popularity of social apps around fitness: platforms like Zwift, Strava, and a host of other training-related or health applications are commonplace. Within these, there is a clear way of tracking fitness, each usually with its own IP surrounding it: it may be the frequency of sessions, hours, miles or more specific training load measurements.
Training load is at the heart of exercise physiology. Athletes and physiologists are trying to understand how much load training is on the individual and how much load is needed to help them progress towards their goals. The training plan purely manipulates that load to see progressive overload and adaption to optimally load the athlete for improvement, but not too much that they break or cannot recover.
As one of the most basic examples, gym memberships help you with your training load. You purchase a frequency of sessions. For example, you can go to the gym two times a week. If you want to improve, you may increase that membership to 3 times a week. This rudimentary yet effective manner of measuring training is the first step. Advances through the ages have seen estimating training load through complex equations and manipulation of data to estimate how much training dose someone has done, the recovery they need and how much the next one.
Commonly, in the traditional marathon build, we see running distances for the long run increasing from maybe 8 miles to 22 miles over a few months. Given the clear linear relationship between an increase in training load and the progression of a training plan, it is little wonder that coaches used spreadsheets (some still do) in order to create formulae and calculate how much training volume or load the athlete needed to do in order to progress. The more accurate this training load measurement is, the more appropriate the training plan can be.
As we can now clearly see, training plans are purely a manipulation of training load in order to generate a desired output. With the advances in artificial intelligence, the improvements in data capturing, and the number of things athletes can begin to measure, it will be only a matter of time before a training program can be customised and adapted based on what you’re wearing (wearable technology), the measurements that something is taking from inside of your body (“internalable” technology) and how it sees you move (motion capture technology). Furthermore, it will adjust the time it takes to compute and analyse the data, which could be almost instantaneously.
This is a significant progression from the classic training plan ripped out of your endurance sports magazine or followed in a book. Suddenly, a smart or adaptive training plan begins to explore suggestions that your body is giving you around fatigue, training, adaption, and environmental factors, like how the heat or altitude will affect your session. In many ways, this is a coach's current role.
Traditionally, through conversations with the athlete or reactions from training sessions, the coach would adjust a training plan based on the athlete's feedback. At the extreme level, coaches relied on their philosophy or dogma to produce athletic performance. They were as good as their subjective observations. Now, more coaches are becoming data-informed, but many often have biases and can only process so much data simultaneously. Often, this may only be once or twice a week as is convenient to them. It is certainly not instantaneous. As we said, with the increased amount of data available to inform that coach about how to adjust the plan, automating the system is not only a saving for the athlete to get a better training program, more in tune with their own needs, but it also makes best use of the coach.
When you look at sports through the ages, ignoring the competitions which were one or lost by the bounce of the ball (or the controversial decision of a match official), these competitions are often won not in the training that the athlete has done physically, but the psychological aspects of it instead. What is commonly known in sports coaching as the biosocial-psycho-social sphere of an athlete becomes ever more important. Therefore, coaches can spend less time analysing and making sense of the exponentially increasing amount of data and focus on these other angles that create the difference between winners and losers.
Therefore, A coach can begin using and relying on artificial intelligence to create a training program while focusing on the performance differences that a program will have. In this case, the athlete gets a far better-valued training programme than what is currently available, knowing that, assuming the right algorithms are used, will always be more up-to-date and more informed than anything a coach can do. Here are three examples of how this could play out.
Firstly, consider the athlete who gets a little carried away on their weekend ride and joins the fast group, going longer and harder than the programme instructed. A coach-led plan then needs a coach intervention to adapt or change the pan for the tired legs of the athlete. If they don’t, then why didn’t they set a longer, harder plan in the first place, or they are eating into a protective buffer that could impact the athlete later in the plan. Another example could be how a training plan can take the recovery metrics, sleep, HRV, mode scores, etc (learn these for the athlete in the same way a coach does: 7/10 for some athletes could be a cause of concern, but for others could be a fantastic time!) and adjust the day’s training or the weeks training accordingly. Finally, a common example is a change in conditions. Heat can impact athletes' performance when it is more than 15’C. Adapting the training zones for the heat stress the run will cause ensures that the correct training load is applied to the athlete at the right time. (Remember, the aim of all training plans is to ensure the optimum load to create adaption without over-training!).
If I look at the training programmes we set for athletes, they take about 40-60% of a coach's time: setting, adjusting, and revising the plan. Leaving the remaining time to focus on the athlete. Many athletes place a value on that plan, which is far higher than the coach's at a push, I would say it is worth about 10% of the coach's time: there really isn’t any secret sauce, whereas athletes (with the exception of those who have engaged with top-level coaching) probably emphasise the plan is worth close to 90% of the coach’s value!
If you think about it, there are only so many ways you can set 5x1km repeats on the track or 5x400m in the pool. What the athlete does is less important than how or why they do it. Imagine if writing the plan was outsourced to AI, which would only be better at managing the data analytics in real time than a coach can be. Allowing the coach to focus on understanding the patterns that are being shown for the athlete’s bio-socio-psycho development. In other words, the coach could focus on the “how” and the “why” rather than the “what”. As we have seen countless times in great sporting clashes, the “how” and the “why” make the difference in the result rather than the “what” they did.
Philip is the founder of Tri Training Harder LLP. He’s a British Triathlon Level 3 coach, and has been coaching for over a decade and is involved with mentoring and developing other coaches.
Philip has coached athletes to European and World AG wins, elite racing, many Kona qualifications, IRONMAN podiums and AG wins.
Alongside the conventional development through many CPD courses, he has also been fortunate enough to work alongside experts in the fields of Physiotherapy, Strength and Conditioning, Nutrition, Psychology, Biomechanics, Sports Medicine. Putting this knowledge into practice he has worked with thousands of athletes to various degrees, from training camps in Portugal and around Europe, clinics in the UK and online coaching.
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