Making Sense of Wearables with Sian Allen PhD | Koopcast Episode 139
Episode overview:
Sian spent over 10 years providing sport science support to athletes and coaches in Olympic, Paralympic and professional sports across high performance environments in Great Britain and New Zealand. She began her career working as a Physiologist with British Swimming in the lead up to the London 2012 Olympics, before obtaining an applied PhD in statistical modelling of sport performance from AUT University while working with Swimming New Zealand.
Sian then took up a strategic role as Performance Intelligence Manager with Paralympics New Zealand into the Rio 2016 Games, managing innovation projects and data analysis systems across all Paralympic sports in New Zealand. She now combines her data analytics and exercise physiology backgrounds with the latest in technology and scientific research, working as a Research Manager in the Product Innovation team at lululemon athletica on the West Coast of Canada.
Episode highlights:
(23:42) Three ways to inform training: training architecture, using past athlete data, physiology
(32:53) Raw data: how to make use of data for training
(43:55) data as confidence: you are more than your watch score, performing well with low wearable scores, getting psyched out before your race
Our conversation:
(0:00) Introduction: bringing method to the madness of wearables
(2:19) The power and limitations of technology: CTS’s involvement in designing wearables, how to interpret the data at our fingertips
(4:41) Finding the signal in the noise: bridging elite and amateur athletes, the limitation of wearable utility is often user knowledge
(6:03) Sian’s background: sports and sports science, working with olympic swimmers, applying elite athlete data to amateur athletes
(8:34) Introducing the evolution of wearables: capturing data, transmitting data from athletes to coaches
(11:12) Using wearables to better know yourself as an athlete: elite athletes, knowing when to push and when to avoid injury, getting familiar with your body during training
(14:05) Recap: wearables add objective value to an athlete’s subjective feelings
(14:46) Discrepancies amongst wearables: the importance of knowing how to interpret data, comparable wearables to each other and personal analysis
(16:53) The pitfalls of wearables: how you wear devices, sampling rates, different companies use different algorithms which compound error
(19:54) Megawave: stoplight systems, combining useful physiological data into an ambiguous score, can you train by scores
(23:42) Three ways to inform training: training architecture, using past athlete data, physiology
(26:30) Training load: external versus internal, training versus life stress, the iterative learning process
(29:31) Using wearables properly: tracking body temperature, HRV, resting heart rate, sleep
(32:53) Raw data: how to make use of data for training
(36:14) Training currencies: chasing variables, time, energy
(38:13) Contextualizing data: the four-pronged approach, the cost-benefit of micromanaging data, training traps
(40:50) friction versus reward: wearables as a learning tool, pricing, data traps
(43:55) data as confidence: you are more than your watch score, performing well with low wearable scores, getting psyched out before your race
(46:38) Hiding data from athletes: anecdote from the Olympics, avoiding second guessing your fitness
(47:33) Novelties in wearables: rationalizing price with quantity of data and training scores
(48:53) The future of wearables: personalization, isolating relevant variables
(50:38) sport groups: personalizing wearable data by athlete goals
(53:50) Specific to nobody: looking at raw data, putting data in context
(55:21) Wrap-up: the future of wearables, staying skeptical, where to find Sian
(57:10) Outro: giving thanks, alchemizing data into training scores, the future of recovery data
Additional resources:
Buy Koop’s new book on Amazon or Audible
Information on coaching-
Koop’s Social Media
Twitter/Instagram- @jasonkoop