A Simple Model...: 10. Discussion and General Conclusions

A Simple Model for Predicting Sprint Race Times Accounting for Energy Loss on the Curve --- J. R. Mureika

10. Discussion and General Conclusions

This model is not intended to serve as gospel of how sprinters perform; surely, it is crude at best. However, it can be used as a simple tool to gauge what kind of records might be expected, based on present performances. Due to the "loose" statistical fit of the data from lack of points, the WRs of Section 7 may be somewhat overestimated. DB's predicted performances of Section 9.1 are probably more representative of the possible range of

² values that one might realistically expect, if such a model holds. That is, if he is capable of running the 200 m in the range of 20.15 to 20.40 s, then if

² is the same for all runners, possible values lie between

² = 0.40 and 0.60. A value of

² =1.00, while closely reproducing the current 200 m WR, is definitely wrong from this observational point of view: it would greatly underestimate Bailey's potential (t > 20.60 s would hardly be expected by a WR holding sprinter, regardless of specialization).

The following points should be considered, though:

² is not the same for indoor and outdoor races; indoor tracks would favor lower , so long as they are banked
² may not be the same for all athletes; 200 m specialists handle turns with greater ease than 100 m specialists. It may be an individual parameter, like (f,,c).
due to physiological considerations (different posture assumed or muscles/joints used, etc...), it seems more likely that the values of and/or c may change around the curve
if the effect is purely physical, then the individual lane records should be strictly decreasing from lane 1 to lane 8. The recorded records (Table 1a) suggest that a minimal race time is achieved around lane 3 or 4, contributing to the physiological nature of curve running.

The results of this paper are limited by the availability of relevant data, unfortunately. It would perhaps be of future interest to investigate the physical nature of the parameters (f, , c, ) through study of various athletes. By knowing the effects of their variability on predicted times, models such as these could perhaps be used as a new training tool to gauge and direct the training of World Class athletes.

Section index

9. A Practical Example: Donovan Bailey

Appendix: The 150m Showdown at Skydome

Curve Model

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Section index	9. A Practical Example: Donovan Bailey	Appendix: The 150m Showdown at Skydome
Curve Model	Main home page