| Title |
Sprint Running Performance Monitoring: Methodological and Practical Considerations
|
|---|---|
| Published in |
Sports Medicine, December 2015
|
| DOI | 10.1007/s40279-015-0446-0 |
| Pubmed ID | |
| Authors |
Thomas Haugen, Martin Buchheit |
| Abstract |
The aim of this review is to investigate methodological concerns associated with sprint performance monitoring, more specifically the influence and magnitude of varying external conditions, technology and monitoring methodologies not directly related to human physiology. The combination of different starting procedures and triggering devices can cause up to very large time differences, which may be many times greater than performance changes caused by years of conditioning. Wind, altitude, temperature, barometric pressure and humidity can all combine to yield moderate time differences over short sprints. Sprint performance can also be affected by the athlete's clothing, principally by its weight rather than its aerodynamic properties. On level surfaces, the track compliance must change dramatically before performance changes larger than typical variation can be detected. An optimal shoe bending stiffness can enhance performance by a small margin. Fully automatic timing systems, dual-beamed photocells, laser guns and high-speed video are the most accurate tools for sprint performance monitoring. Manual timing and single-beamed photocells should be avoided over short sprint distances (10-20 m) because of large absolute errors. The validity of today's global positioning systems (GPS) technology is satisfactory for long distances (>30 m) and maximal velocity in team sports, but multiple observations are still needed as reliability is questionable. Based on different approaches used to estimate the smallest worthwhile performance change and the typical error of sprint measures, we have provided an assessment of the usefulness of speed evaluation from 5 to 40 m. Finally, we provide statistical guidelines to accurately assess changes in individual performance; i.e. considering both the smallest worthwhile change in performance and the typical error of measurement, which can be reduced while repeating the number of trials. |
X Demographics
The data shown below were collected from the profiles of 55 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 11 | 20% |
| United States | 6 | 11% |
| Spain | 4 | 7% |
| Australia | 4 | 7% |
| New Zealand | 3 | 5% |
| France | 2 | 4% |
| Netherlands | 1 | 2% |
| Canada | 1 | 2% |
| Norway | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 20 | 36% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 39 | 71% |
| Scientists | 14 | 25% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
| Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 569 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | <1% |
| Spain | 1 | <1% |
| Turkey | 1 | <1% |
| Unknown | 566 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 88 | 15% |
| Student > Bachelor | 80 | 14% |
| Student > Ph. D. Student | 76 | 13% |
| Researcher | 32 | 6% |
| Student > Postgraduate | 26 | 5% |
| Other | 111 | 20% |
| Unknown | 156 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Sports and Recreations | 291 | 51% |
| Medicine and Dentistry | 24 | 4% |
| Engineering | 12 | 2% |
| Social Sciences | 11 | 2% |
| Agricultural and Biological Sciences | 9 | 2% |
| Other | 44 | 8% |
| Unknown | 178 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 30. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 June 2021.
All research outputs
#1,180,622
of 23,613,071 outputs
Outputs from Sports Medicine
#992
of 2,749 outputs
Outputs of similar age
#21,255
of 392,808 outputs
Outputs of similar age from Sports Medicine
#29
of 64 outputs
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