Lol, it made sense to me! Guess you had to be there. Basically, he was getting across to me that the reason most people do not learn is because they let their previous “knowledge” filter out what they are being taught.
If you really wish to learn anything, you have to trust the teacher and you have to forget what you already know WHILE you are being taught. Don’t let your past teachings affect your willingness to learn things today…
I guess the treadmill theorists at your conference must have either had quite a bit of stock in high speed treadmills or overflowing cups:)
Sometime ago i went for a position as a fitness trainer at a sports club. As a part of the interview process they wanted me to give a demonstration of speed and agility training for tennis players. They had those little hurdles, cones, ladders, wobble boards, core stability balls ready for usage.
I grabbed the olympic lifting bar and demonstrated to the tennis player OL. And explained to the athlete the benefits of the lifts. The interview panel were a bit shocked.
Did i get the position?
Sport specific rules! Ladders, cones, reactive balls oh yeah.
Or cups filled with garbage. It has always seemed to me that facts/elements of the facts seem to fill the cup the least (as in they leave room for more). So if one’s cup is full, it is probably full of garbage. “The more one knows, the more that they know they don’t know…” I forgot who said it (Socrates?), but it is very true.
I believe the longer version of this last statement goes something like this: When you start something new you don’t know anything so you “don’t know what you don’t know”. When you study for awhile you know a thing or two so now you may “know what you don’t know”. And when one becomes a so-called master they “know what they know”. I like Bruce Lee’s version: “When I began martial arts a kick was just a kick. After I studied martial arts a kick was no longer just a kick. When I mastered martial arts a kick was just a kick.”
I was browsing through training for speed and last night I read some of the comments about what you said regarding training with Percy. This was prior to your post.
No matter how much I think I know about speed training or training for sports, I keep having to refer back to my base texts to REABSORB the truth. It’s kind of like a physician peeking into the desk reference before the big surgery. Even like the preacher going through the Bible before his sermon.
Even when you are well skilled at certain things, the brain needs to be constantly reminded of what the truth is. This will be the fourth time reading TFS, and I guarantee I will find the need to highlight things I didn’t highlight the previous 3 times.
Things I did not understand I overlooked, things I did not believe (because of previous teachings clouding my view) I overlooked. It is my desire that I can read the whole book tommorrow without one time letting the brainwashing of others determine what I truly LEARN from the book.
Thanks, Bear!
Yes, that’s the one; I was just a bit surprised, because of what you said before: “Regardless, I don’t own the algorithm so I cannot reveal how it works yet. Hopefully, that will change in the near future.”, that’s all…
Again some people might have some arguments about the overall methodology used and/or the analysis for the agreement between the methods. Not to be pain in the ass, what’s published is published, of course!
“All” that’s left is to see the thing in practice!
Thanks again for bringing this to our attention!
High-speed running performance: a new approach to assessment and prediction
Matthew W. Bundle,1 Reed W. Hoyt,2 and Peter G. Weyand2,3,4
1Flight Laboratory, Division of Biological Sciences, University of Montana, Missoula, Montana 59812; 2United States Army Research Institute for Environmental Medicine, Biophysics, and Biomedical Modeling Division, Natick, 01760; 3Concord Field Station, Harvard University, Museum of Comparative Zoology, Bedford, Massachussetts 01730; and 4Department of Kinesiology, Locomotion Laboratory, Rice University, Houston, Texas 77005
Submitted 7 October 2002 ; accepted in final form 21 July 2003
We hypothesized that allout running speeds for efforts lasting from a few seconds to several minutes could be accurately predicted from two measurements: the maximum respective speeds supported by the anaerobic and aerobic powers of the runner. To evaluate our hypothesis, we recruited seven competitive runners of different event specialties and tested them during treadmill and overground running on level surfaces. The maximum speed supported by anaerobic power was determined from the fastest speed that subjects could attain for a burst of eight steps (~3 s or less). The maximum speed supported by aerobic power, or the velocity at maximal oxygen uptake, was determined from a progressive, discontinuous treadmill test to failure. All-out running speeds for trials of 3-240 s were measured during 10-13 constant-speed treadmill runs to failure and 4 track runs at specified distances. Measured values of the maximum speeds supported by anaerobic and aerobic power, in conjunction with an exponential constant, allowed us to predict the speeds of all-out treadmill trials to within an average of 2.5% (R2 = 0.94; n = 84) and track trials to within 3.4% (R2 = 0.86; n = 28). An algorithm using this exponent and only two of the all-out treadmill runs to predict the remaining treadmill trials was nearly as accurate (average = 3.7%; R2 = 0.93; n = 77). We conclude that our technique 1) provides accurate predictions of high-speed running performance in trained runners and 2) offers a performance assessment alternative to existing tests of anaerobic power and capacity.
Testing our first hypothesis required 1) obtaining measurements of the maximum speeds supported by the anaerobic and aerobic power of individual runners, 2) establishing individual speed-duration curves for each athlete, and 3) evaluating the agreement between the measured and predicted speeds for the all-out running trials completed. The quantitative expression of our hypothesis that the speed-duration curves of different runners would conform to a general relationship took the following form:
Spd(t) = SpdAER + (SpdAN-SpdAER)e^(-kt)
where t is the duration of the all-out run, Spd(t) is that speed maintained for a run of duration t, Spdan is the maximum speed supported by anaerobic power, Spdaer is the maximum speed supported by aerobic power, e is the base of the natural logarithm, and k is the exponent that describes the decrements in speed that occur with increments in run duration. We called the term Spdan - Spdaer the runner’s anaerobic speed reserve. The exponent k used for predictive purposes was 0.013. This was the average value of the individual best fits on data previously acquired from 17 subjects. None of these 17 subjects participated in the present study.
Testing our second hypothesis required 1) assessing whether high-speed running performances could be predicted from as few as two performance trials and 2) obtaining running performance data in the field to supplement that obtained in the laboratory. The speeds and durations of any two all-out trials, Eq. 1, and algebra could be used to create a system of equations, which, when solved, would predict the speed-duration curve from 3 to 240 s for individual runners.
In regards to the algorithm, the fit numbers look good. The experimental design looks pretty solid too.
Bear, as you use this model, i assume that it has generalized to your athletes well (otherwise, you wouldn’t be using it). Have you noticed any confounding factors that effect this algorithm’s efficiency? (Namely athletes with qualifications at the extreme ends of those tested in the paper)
So far I haven’t found any, but I haven’t worked with it long enough or with enough subjects to give a legitimate opinion regarding your question. Ken Jakalski, a coach in the Chicago area as used it much longer than I. He has not reported anything unusual to me.
For training purposes, it is very dynamic in nature because of its adaptation to changes in ability of each athlete.
I don’t understand the second graph (or the first one really…). You input the Distance1, Time1, Velocity, Distance2, Time2, Velocity2, and the rest is pumped out onto the worksheet?
The 800m time is quite a bit off, though. most 60 second runners Guys or girls I know hit about 2:20-25 in the 800. I haven’t seen any algorith/program that can accurately predict times when switching energy systems. 100->800->10k. Regardless, it looks fairly accurate, and like one heckuva tool.
Daniels Running formula has a chart similar to this -and it helps oodles for doing trainig runs and intervals, but again it’s off depending up on the different event emphasis of the athletes.
Ladders, cones, reactive balls oh yeah.