How to Establish Intensity Ranges with Adam Pulford, CTS Pro Coach | KoopCast Episode 162
Episode overview:
Adam Pulford is a Pro Level Coach at CTS and is one of the most sought after mountain bike coaches in the world. He also has served ass the team director for TeamShoAir UCI Professional Factory MTB Team the Twenty16/Twenty20 UCI Professional Women’s Race Team and the Orange Seal Off-Road Team
Episode highlights:
(23:45) Zones are descriptive not prescriptive: avoiding overeager zone prescriptions, instantaneous tests, athlete adaptability
(36:19) Is physiological testing worth it: marginal gains, correlating time to exhaustion between the field and lab tests, physiological testing is best for gauging improvement
(1:07:39) Durability at intensity: making sure zone paces are sustainable to increase volume at intensity, the importance of durability and sustainability in training
Our conversation:
(0:00) Introduction: the challenges of quantifying intensity, introducing Adam, relevance to individual training
(3:08) Sport crossover: Ultrarunning is about a decade behind cycling science-wise, cycling and ultra-trail can learn from one another
(4:50) Athlete context: runners are setting up their season and need to understand training intensity, traditional methods of measuring intensity are obscured in trail running
(6:38) Adam on setting intensity ranges for new athletes: using data as a starting point, what information you can glean from athlete data
(9:40) Using athlete data: learning from when athletes performed their best and their worst, using the past 30-90 days of training as a benchmark, testing when data is absent
(13:23) Intensity anchors: power-duration, determining maximum power over 5s, 20s, 1min, 5min, 20min, and 60min, these correspond with different energy systems in the body, 20min is the anchor point, anaerobic power is more genetic
(15:26) You need intensity to establish zones: zone 2 training does not provide meaningful information for establishing zones, races, field tests, and workouts
(18:51) Testing for intensity: anaerobic and neuromuscular power tests, 20 minute time trials, pacing for tests, 5 minutes all-out
(21:38) Deriving power from tests: waiting for context to prescribe ranges, examples
(23:45) Zones are descriptive not prescriptive: avoiding overeager zone prescriptions, instantaneous tests, athlete adaptability
(26:15) Heart rate for establishing zones: transitioning using from heart rate to power in cycling, RPE, backcalculating zones from max efforts, caution against relying on technology
(29:42) When to do physiological testing: Renee Eastman, deriving ranges from lab tests, caveats, quality, specificity, cost
(34:09) Utilizing physiological testing: variable testing protocols, using lab tests data
(36:19) Is physiological testing worth it: marginal gains, correlating time to exhaustion between the field and lab tests, physiological testing is best for gauging improvement
(40:07) Percentage of VO2max at lactate threshold: data from training, one of the prime indicators of training architecture, knowing when to train threshold versus VO2
(43:54) Artificial intelligence: benefits and drawbacks of AI as a tool, additional insight on training zones, drawbacks of black box models, bad data yields bad results
(48:08) AI and coaching: AI will make bad “copy-paste” coaches obsolete, it will help good coaches get answers for athletes faster
(49:33) Understanding AI tools: COROS Effort Pace example, you need to know how AI tools work to use them properly
(51:58) Banter: how Koop and AP could compare their running efficiency
(53:29) TrainerRoad: generating training zones from bulk workout data, learning from athlete training, caveats, overreliance on tools causes problems
(55:46) Example of CTL AI: AI tool for increasing chronic training load: defining acute and chronic training load, challenges with individualization
(58:45) Building coaching assists: PKRS AI, maximizing coach leverage via communication, prescribing training, evaluating athlete data, AI is most effective at evaluating data, knowing how to interpret data is a challenge for machines
(1:03:14) Humans are not predictable: there are too many variables for AI to accurately model human emotions and responses
(1:04:41) Modifying zones over time: intentionally uptraining and detraining, investigating durability at zone paces
(1:07:39) Durability at intensity: making sure zone paces are sustainable to increase volume at intensity, the importance of durability and sustainability in training
(1:09:47) Time at intensity > higher intensity: caveats, it is better to undershoot intensity and increase time at intensity than vice versa
(1:11:20) Wrap-up: giving thanks
(1:11:58) Koop’s three takeaways: time-duration is more important than precision of intensity, RPE is a powerful tool for cyclists, you need to validate calculated zone intensities in training regardless of method
(1:15:06) Outro: giving thanks, changes to the KoopCast, positive listener responses
Additional resources:
Buy Training Essentials for Ultrarunning on Amazon or Audible
Information on coaching-
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