Closest I can think of is when Coggan posted a graph to the wattage list showing a correlation between TSS and glycogen use measured via biopsy.
Oh wait - Skiba once did a study of NP. I’ll see if I can find it.
ETA.
Skiba PF. Evaluation of a Novel Training Metric in Trained Cyclists. Med Sci Sports Exerc 2007; 39: S448.
" Numerous systems have been developed to quantify athlete training, many based upon subjective criteria. Recently, a novel system based upon lactate-normalized power output has been popularized for cycling (Coggan 2003, 2006), which has not been evaluated in the literature. This system should be superior to existing methodology because it relates a purely objective parameter (power output) to resultant metabolic stress by weighting cyclist power output with a 4th power function that closely tracks serum lactate response to a standard ramp exercise protocol. This value is then compared to the average power an athlete is capable of maintaining for one hour (previously shown by Coyle et al (1988) to be highly correlated to power output at LT) to generate a training stress score.PURPOSE: This investigation examines the validity of this algorithm in a group of trained cyclists (n=5). This work also evaluates the utility of the related training stress scoring system in the quantification of training load and performance modeling using convolution integrals.METHODS: Power meter files for one-hour (range 51�62 minutes) individual time trial races (ITT) and one-hour (range 51�60 minutes) criterium races (CRIT) were obtained from 5 trained cyclists. Average power (AP) values were compared between ITT and CRIT. CRIT power data were then subjected to a 4th power-weighted 30-second moving average to generate a normalized power (NP) value. ITT AP and CRIT NP were then compared. Training stress scores were generated and used as the input function for systems-based performance modeling for a national-level track cyclist per the method of Morton et al (1991).RESULTS: CRIT AP was highly correlated with ITTAP (p<0.04, r2=0.791), however, CRIT NP was more highly correlated to ITT AP (p<0.001, r2=.978). Using the examined training stress score, it was also possible to accurately model performance (p<0.0001, r2=0.9189). CONCLUSIONS: Though additional work with a larger sample size is required, these data indicate that NP may be superior to AP in describing how strainful a variable-power work task is. These data also demonstrate the utility of the associated training stress quantification system in performance modeling for trained cyclists.
It’s also important to be aware of how much hard sprints can throw NP into wildly irrelevant values thanks more to the non-linear math than physiological relevance.
For example, I did Bays +1 yesterday using the screwed up outside workout version. Mostly high Z2 endurance but with 6 20-sec sprints instead of the targeted 4. Did the sprints at ~3.1 X FTP instead of target ~1.8 X.
Two extra sprints and going harder on them skews the TSS from a target of 84 to an actual of 167 in 95 minutes. Was also the highest NP I’ve ever seen for 95 mins. But there’s no way I could actually do those watts for 95 mins steady - doubtful I could even do it for 60 mins.
At the same time, I’m also not nearly as fatigued as I might have been with a 95 min all out TT or other more steady efforts to try to achieve that same NP / TSS.
Point being, be careful on NP conclusions if you have a few big sprint efforts on a group ride or workout - the math goes pretty crazy when you start taking things to the 4th power
(ps - for those that use Rouvy and chase the career seasonal TSS metric - this is a very useful hack to rack some extra TSS up quickly )
In addition to the study that @old_but_not_dead_yet shared, here is an excerpt from Coggan’s March 25, 2003 early manuscript for Training and Racing with a Power Meter (before the book was published):
Thanks to both for digging this up. If I am reading it right, what we have is:
A study finding a good fit for a fourth-order equation of power to blood lactate (n=76); and
A study of 5 (!) cyclists showing that (1) the correlation between a cyclist’s NP in a crit and their AP in a time trial is stronger than (2) the correlation between a cyclist’s AP in a crit and their AP in a time trial.
This second one seems a bit odd to me. Why would we expect any particular relationship between a crit effort and a TT effort? I’m specifically thinking of @Pete’s comment that in a crit you want to do as little work as possible for as much of the race as possible.
)
