Hearing the experiences and opinions of the team are what make the podcast entertaining and informative, and I love it when the pod is full of easy banter and interesting anecdote.
Reviews of the literature should be done critically, and with an understanding of science and research which, understandably, the team doesn’t have. There is a huge amount of poor-quality sports & exercise research out there. I was relieved when Chad went, as listening to him stumbling through countless poorly designed studies with inadequate sample sizes and inappropriate statistical claims made me cringe. Now it looks as though Jonathan may be attempting to do the same - please don’t!
If you are going to present research, please look at the credentials of the originating institution/authors, at the design of the study and its aims, and really decide whether the results are credible enough to contribute to the podcast. By all means mention the rest, but be clear that these are no more than unsubstantiated theories. And finally, please don’t say “x was higher/lower in one group, but it wasn’t significant” - that’s the point of statistics! If it’s not significant, it means the study hasn’t demonstrated a difference.
Sorry to criticise - I love the essence of the podcast.
My preference would be for the podcast to steer away from the “deep dive” approach, but I appreciate many/most may not share this view.
damn, I agree. I tuned out long ago. Making a podcast interesting and engaging talking about the same topics, answering the same questions over and over must be a hell of a task. I don’t envy them…
I agree, also referencing papers for the sake of it doesn’t capture my interest.
I much prefer to listen to actual coaches sharing their field knowledge and direct experience with the right amount of detail.
This is why my favourite podcasts are the likes of Evoq, Empirical cycling (weekend Q&A is super cool kudos to them) and CTS time-crunched.
Fascat has somewhat lost its allure becoming a marketing tool and most episodes of Fast talk are too vague for my own taste.
Finally, TR’s sits on a par with the latest I have mentioned I believe.
I can’t remember when, but at some point before COVID, the podcast started to switch from an hour of the guys talking about their training and racing, whatever topic they were diving into at the moment (Dexa scans, aero testing, etc.), team trips, etc., to much longer podcasts with much deeper dives into research. I personally preferred the old format because it felt more personal.
There was a lot of debate about this on the forum, but, to my surprise, the vast majority of respondents said “I love the deep dives and I wish the podcasts were all 3 hours long”.
I think Jonathan has a very tight rope to walk in trying to make everyone happy with content, length, guests, etc. It’s not easy and I respect how hard he tries. They even tried breaking things into multiple pods to give everyone what they want. As the company has grown and evolved, that has gotten even more complex. I don’t always like the direction the podcast goes, and as a result, I’ll stop listening for periods or just pick and choose, skim, etc., but I recognize I’m in the minority and I respect that. I miss the days of the team all getting their body fat measured together, sitting in one room talking trash, eating as many carbs as possible during a 24 hour mtb race…but I also recognize that the company, their individual lives, and the podcasting landscape, have moved on.
The podcast definitely was at it’s best when the hosts were all training for events and would share their experiences/banter. That was way more entertaining than any deep dive. I just want to be entertained while maybe learning a bit.
Value is often (always?) subjective. I personally don’t feel the need to have every aspect of TR or related training be “science backed”. There are plenty of examples of coaches & athletes implementing training that is not directly founded in or justified by “hard science”, but it works to get the goals they set.
I know some TR AACC listeners are much more into the science of things and would prefer than TR or any other system justify their approach with science data backing. We’ve seen this range and some between shown in the various discussions related to the Deep Dive sections of the cast in the past. Some love them while others hate them.
I don’t think there is a clear, singular answer here.