Excellent Article on Mathematical Modeling of Athletic Training

I came across this wonderful article of David C. Clarke and Philip F. Skiba on mathematical modeling and want to make sure the readers of the blog get access to it.

Clarke and Skiba have reviewed all the current knowledge on mathematical modeling to predict adaptations to training and to predict performance and have provided all the details about the different methods as well as the summary of all calculations with a spreadsheet.

The article is available here and below you can read the abstract:

A number of professions rely on exercise prescription to improve health or athletic performance, including coaching, fitness/personal training, rehabilitation, and exercise physiology. It is therefore advisable that the professionals involved learn the various tools available for designing effective training programs. Mathematical modeling of athletic training and performance, which we henceforth call “performance modeling,” is one such tool. Two models, the critical power (CP) model and the Banister impulse-response (IR) model, offer complementary information. The CP model describes the relationship between work rates and the durations for which an individual can sustain them during constant-work-rate or intermittent exercise. The IR model describes the dynamics by which an individual's performance capacity changes over time as a function of training. Both models elegantly abstract the underlying physiology, and both can accurately fit performance data, such that educating exercise practitioners in the science of performance modeling offers both pedagogical and practical benefits. In addition, performance modeling offers an avenue for introducing mathematical modeling skills to exercise physiology researchers. A principal limitation to the adoption of performance modeling is a lack of education. The goal of this report is therefore to encourage educators of exercise physiology practitioners and researchers to incorporate the science of performance modeling in their curricula and to serve as a resource to support this effort. The resources include a comprehensive review of the concepts associated with the development and use of the models, software to enable hands-on computer exercises, and strategies for teaching the models to different audiences.

This paper was published on Advances in Physiology Education which is a relatively new journal of the American Physiological Society.

Here is the full reference: 

Clarke DC, Skiba PF. Rationale and resources for teaching the mathematical modeling of athletic training and performance. Adv Physiol Educ. 37(2):134-52. June 2013.

If you want to read more about Dr. Skiba's work you can go here.

Great paper and most of all great supplementary material, excellent job @DrPhilipSkiba!

Aspetar Journal Special Issue on Handball

This is great news I hope for all the handball readers of my blog. Aspetar Sports Medicine Journal, which you can receive for free in print and access online if you subscribe has just published a special issue on Handball. 

This issue was developed by the editor in chief Dr. Nebojsa Popovic, an excellent Sports Medicine specialist with a glorious past as a handball player (Olympic Champion with ex-Yugoslavia in 1972) and contains an excellent series of articles on various aspects of handball.

I wrote something about strength training available here.

So if you are working with handball players or you are a coach, make sure you don't miss this special issue of Aspetar Sports Medicine Journal. 

New Article Published

This work was a collaboration with colleagues at Center of Excellence for Sport Science and Coach Education, in East Tennessee State University.

J Sports Med Phys Fitness. 2014 Apr 9. [Epub ahead of print]

Repeated change-of-direction test for collegiate male soccer players.

Mizuguchi S1, Gray HS, Calabrese LS, Haff GG, Sands WA, Ramsey MW, Cardinale M, Stone MH.

Author information

• 1Center of Excellence for Sport Science and Coach Education, Department of Kinesiology, Leisure, and Sport Science, East Tennessee State University, Johnson City, TN, USA - harahara10@hotmail.com.

Abstract

AIM:

The aim of the study was to investigate the applicability of a repeated change-of-direction (RCoD) test for NCAA Division-I male soccer players.

METHODS:

The RCoD test consisted of 5 diagonal direction changes per repetition with a soccer ball to be struck at the end. Each player performed 15 repetitions with approximately 10 seconds to jog back between repetitions. Data were collected in two sessions. In the first session, 13 players were examined for heart rate responses and blood lactate concentrations. In the second session, 22 players were examined for the test's ability to discriminate the primary from secondary players (78.0 ± 16.1 and 10.4 ± 13.3 minutes per match, respectively).

RESULTS:

Heart rate data were available only from 9 players due to artifacts. The peak heart rate (200.2 ± 6.6 beats∙min1: 99.9 ± 3.0% maximum) and blood lactate concentration (14.8 ± 2.4 mmol∙L1 immediately after) resulted in approximately 3.5 and 6.4fold increases from the resting values, respectively. These values appear comparable to those during intense periods of soccer matches. In addition, the average repetition time of the test was found to discriminate the primary (4.85 ± 0.23 s) from the secondary players (5.10 ± 0.24 s) (p = 0.02).

CONCLUSION:

The RCoD test appears to induce physiological responses similar to intense periods of soccer matches with respect to heart rate and blood lactate concentration. Players with better average repetition times tend to be those who play major minutes.

I have been away form the blog for few months now. The move to Qatar has meant adjusting to life in the desert and learning a lot new relevant aspects of my new job. There are so many things to learn and too many things to do. Sadly the time to update the blog has been less than expected. Abandoning Windos for Mac has also not helped, as I am still trying to find a good software solution to be able to blog more often (if you have suggestions, feel free to email them!). 

Anyway, I want to share the news that finally this paper has been published. This was the result of a lot of hard work from Dr. Andy Galbraith and a collaboration with Professor Louis Passfield's group at University of Kent to make sure we made the most out of the data gathered in the study. Hopefully more data of this study will be published in the future.

Here is the abstract:

A One-Year Study of Endurance Runners: Training, Laboratory and Field Tests

Section: Original Investigation Authors: Andy Galbraith1, James Hopker1, Marco Cardinale2,3,4, Brian Cunniffe3 and Louis Passfield1 Affiliations: 1Endurance Research Group, School of Sport and Exercise Sciences, University of Kent, Chatham Maritime, United Kingdom. 2Aspire Academy, Doha, Qatar. 3 Department of Computer Science, University College London, London, United Kingdom. 4 School of Medical Sciences, University of Aberdeen, Aberdeen, Scotland. Acceptance Date: March 18, 2014 DOI: http://dx.doi.org/10.1123/ijspp.2013-0508 Abstract: Purpose: This longitudinal study examined the training and concomitant changes in laboratory and field-test performance of highly trained endurance runners. Methods: Fourteen highly trained male endurance runners (mean ± SD: VO2max 69.8 ± 6.3mL·kg-1·min-1) completed this 1-year training study commencing in April. During the study the runners undertook 5 laboratory tests of VO2max, lactate threshold (LT) and running economy, and 9 field tests to determine critical speed (CS) and the modelled maximum distance performed above CS (D’). The data for different periods of the year were compared using repeated measures ANOVA. The influence of training on laboratory and field test changes was analysed by multiple regression.Results: Total training distance varied during the year, and was lower in May-July (333km [SD: ± 206km], P=0.01) and July-August (339km [SD: ± 206km], P=0.02) than in the subsequent January-February period (474km [SD: ± 188km]). VO2max increased from the April baseline (4.7L·min-1 [SD: ± 0.4L·min-1]) in October and January periods (5.0L·min-1 [SD: ± 0.4L·min-1], P<0.01). Other laboratory measures did not change. Runners’ CS was lowest in August (4.90m·s-1 [SD: ± 0.32m·s-1]) and highest in February (4.99m·s-1 [SD: ± 0.30m·s-1], P=0.02). Total training distance and the percentage of training time spent above LT velocity explained 33% of the variation in CS. Conclusion: Highly trained endurance runners achieve small but significant changes in VO2max and CS in a year. Increases in training distance and time above LT velocity were related to increases in CS. Keywords: VO2max, critical speed, distance running, endurance, performance changes

Change of scenery, move, new job and new opportunities

Apologies for the silence, but the last month has been quite eventful. I left the UK and moved to Qatar to start my new job at Aspire Academy heading physiology and biochemistry. So far I have been a month in Qatar and I can tell you that this is an exciting project with huge potential.
This is the location of the Academy.

An incredible facility with some great colleagues and great coaches, so looking forward to get back into working with young athletes. Reading a lot at the moment and trying to write up few things while developing the structure of the physiology and biochemistry activities in Aspire. 

I plan to write more and have few ideas for new articles on this blog, so stay tuned and hopefully you will like the new content.