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'Watt' it Takes to win Vineman 50-54
August '08
Larry Davidson of Dana Point CA won Vineman 50-54, a first-ever win at the 70.3 distance.
Larry has trained with M2 for 4 years since beginning his triathlon participation.
A summary and detailed outline of Larry’s training and race performance can be viewed below:
Vineman 2008 Training Race Summary |
|
SWIM : |
33 min 39 sec |
BIKE : |
2 h 37 min 11 sec |
RUN : |
1 h 37 min 02 |
TOTAL : |
4 h 53 min 06 sec |
Reasonable Training Hours:
A typical week of training sees 3 focused workouts in each discipline – option to add easy sessions as body/motivation invite.
Measured Training using Relevant Metrics
All of Larry’s bike training is wattage-based – two sessions on the computrainer similar to what we practice at M2 with duration 50-70min, and a weekend road-ride using a Powertap. Run is a mix of treadmill, track, and roads where pace is the metric.
No Silly "Taper Formula"
Where Larry is also prepping IM Wisconsin, his training the weekend before Vineman horrified the “periodized taper” crowd (subject of an upcoming article) Saturday saw a 2hr ride with a mix of shorter intervals ranging from 95-105% intensity, followed by a basic 30min get the running legs transition. Sunday was a longer 4hr effort with a range of focused work ranging from 80-92% intensity, with optional 10-15min get the running legs transition.
Certainly a solid weekend of training, but if you can’t recover and be sharp in a week’s time from two hard bike sessions then the adequacy of your preparation has to be called to question. We figured this double-dose would stand him good stead for Vineman and IMW.
No Complex "Nutritional Strategies"
Horrors! There was none of the following:
- Obsessive calorie targets
- Elaborate sequencing of fuel assortments
- Spreadsheet time-table for ingestion of such
- 4:1 Carb / Protein calculations before, during, or after
Per earlier articles, optimal fueling for tri-events does not need to be as complicated as folks seem to want to make it.
For the Data and Performance Inclined Enthusiasts
Vineman Power Data as measured by Larry’s Zipp Powertap
FT – Functional Threshold = 220 watts
AP – Average Power = 184 watts
NP – Normalized Power = 194 watts
TSS – Training Stress Score = 206.7
FT represents a rider’s best 1hr wattage average. For M2 Revolution riders, this would be about 95% of the benchmark we use in class.
Average Power is self-explanatory – average watts for the entire ride duration, but given the often irregular effort in a cycling/tri event, avg/pwr often does not truly reflect how hard the ride was in terms of its physiological cost.
More interesting can be what is referred to as Normalized power (NP), a feature of a highly functional power analysis software program where an algorithm takes into account the variability of a rider’s efforts, and calculates a Power number that more accurately reflects the physical effort of a particular ride.
As an example of how AP and NP relate to each other and work effort, consider the example of a one hour uphill time-trial, and a criterium style race. In the TT, it is clear to see that the ride effort would be uninterrupted and largely even. In this example, you would get a clear idea of your best one hour watts - FT. Such an even effort would see NP and AP as identical or very similar.
However, ride an intense one hour criterium and you will see that despite a maximum effort and feeling of such, your average power will be lower than your best 1hr watts (FT). This will be due to coasting through turns, dropping into the draft zone, etc. Thus, in this example, average power will not be as accurate a reflection of your work effort.
However, enter normalized power and its algorithm, and you see a wattage number very similar to your sense of effort – best 1hr watts – FT.
With the inherent variability of outdoor riding (downhills, turns, stop-signs, draft zones, etc.) Normalized Power and its relation to Functional Threshold (your best 1hr watts) becomes a very useful analysis tool because it gives you a better sense of the physical cost of the ride.
IF – Intensity Factor =.881
Intensity Factor is derived by dividing Normalized Power by Functional Threshold; NP/FT.
Larry biked at a relatively high intensity (88% of his FT), beyond what the early stage mainstream is eager to postulate as optimal. He followed up a hard bike effort with a very strong run, indicating that his bike effort was not excessive.
To the extent that measured results matter, it is clear that TSS and IF ranges need to be evaluated also as a function also of training efficacy.
TSS – Training Stress Score =206.7
For those fluent in CyclingPeaks/TrainingPeaks power analysis, you will note that TSS is notably higher than what general training quarters want to think is feasible where a strong run can follow. Note that Larry went on to have the 2nd fastest run split and was likewise strong by his standards.
For those unfamiliar with CP/TP, TSS is an interesting data point which scores your “training stress” by factoring both the duration of your ride with the overall intensity as it relates to the rider’s FT.
AHR – Average HR = 157 (LTHR 166)
Although HR is a less reliable metric for longer events, Larry average HR indicates an aggressive ride.
Larry’s LTHR is based on 2 x 15min all-out time-trials with a brief 2min easy spin between efforts, where we look at the average for the 2nd effort and typically add a few beats.
Bay Area folks who determine LTHR and training zones by performing a 10 mile TT with effort such that one feels they could go another 10 miles at the same pace should take special note of Larry’s sustainable HR, where for 2+ hours he averaged a higher HR than what the 10+10 TT would have indicated as a “LTHR”.
Training and racing at such a low HR would not have produced either the fitness or this race result.
VI – Variability Index = 1.05
VI gives the rider a perspective on the overall consistency of effort, and is derived by dviding Norm-Pwr by Avg-Pwr.
VI can be a useful data point because for time-trial efforts, a consistent and even effort will generally be the best approach for optimal performance. Uneven pacing such as going out too hard, jamming on hills, dramatic accelerations, etc. would see a higher VI and suggest that ride strategy was less than optimal.
Cadence AVG = 89
Larry’s fitness and measured intensity allowed him to maintain a lively and engaged cadence throughout the 56m rolling ride.