Flying 10 Benchmarks by Gender and Level

Flying 10 Benchmarks by Gender and Level

The flying ten removes the start entirely, which few field tests do. That makes it the cleanest maximum velocity number a coach can get without a radar gun. This post covers flying ten benchmarks for males and females at four competition levels, from middle school through professional. All times assume a 30-yard build-up into a 10-yard timed zone recorded with laser timing gates.

A note on these numbers: The benchmarks in this post are drawn from peer-reviewed literature, published performance data, and established normative datasets. Where direct data exists for a level, we used it. Where data is limited, figures are extrapolated. That applies mainly at the middle school level and for female athletes outside track and field. The extrapolations draw on youth percentile data, age-adjusted development curves, sprint testing in female team sport athletes, and documented sex differences in maximum velocity. All numbers should be treated as reference ranges, not absolute targets, and interpreted alongside the athlete's sport, position, training age, and testing protocol.

What the Flying Ten Actually Measures

A 10-yard dash is almost all acceleration. A 40 is a mix of phases, and NFL Combine analysis shows maximum velocity drives most of the 40 result. Both tests also carry the athlete's ability to get out of a stance. That is a separate skill from covering ground at speed, and the flying ten leaves only the second one. The athlete is already near full speed when the first beam breaks, so the number describes how fast they run once acceleration is finished. That is why acceleration and top speed are tested as separate qualities.

The 30-yard build exists for a reason. Field sport athletes need roughly 27 meters from a standing start to reach 97.5% of their top speed. Entering the zone already striding cuts that to about 16 meters. Thirty yards is 27.4 meters, which puts most athletes inside their top-speed window by the time the clock starts. Trained sprinters take longer and tend to peak closer to 50 meters. For them a 30-yard build reads slightly below true maximum, and for a team sport athlete it reads very close to it.

Where the Average Athlete Actually Stands

The bands describe trained athletes. They are built from maximum velocity research rather than percentiles drawn from a measured population of flying ten times. An untrained athlete of the same age usually falls below the average band.

Males

Stage Average Good Advanced Elite
Middle School (12–14) 1.42–1.65 s 1.25–1.41 s 1.12–1.24 s Sub-1.12 s
High School (14–18) 1.20–1.42 s 1.08–1.19 s 0.94–1.07 s Sub-0.94 s
College (18–22) 1.05–1.22 s 0.95–1.04 s 0.88–0.94 s Sub-0.88 s
Professional (22–32) 0.95–1.10 s 0.88–0.94 s 0.82–0.87 s Sub-0.82 s

Females

Stage Average Good Advanced Elite
Middle School (12–14) 1.65–1.90 s 1.45–1.64 s 1.28–1.44 s Sub-1.28 s
High School (14–18) 1.42–1.65 s 1.25–1.41 s 1.12–1.24 s Sub-1.12 s
College (18–22) 1.22–1.45 s 1.10–1.21 s 1.00–1.09 s Sub-1.00 s
Professional (22–32) 1.10–1.32 s 1.00–1.09 s 0.92–0.99 s Sub-0.92 s

An athlete with a year of dedicated top-speed work should typically sit at good or above for their age group. The bands are wide on purpose, because the sport an athlete plays shifts the distribution inside a level considerably.

Two reference points help place the professional rows. The fastest ball carrier of the 2024 NFL regular season, on a 64-yard touchdown in Week 11, hit 0.91 over a flying ten. That was measured in a game, in pads, carrying a ball, and it sits in the good band rather than the elite band. The men's 100 meter world record run peaked at roughly 0.74.

Because the flying ten skips the phase that the 10-yard dash is built to measure, the same athlete can land in different tiers on the two tests. That split is information, not a contradiction.

Why There Are No Sport-by-Sport Tables Here

Our other benchmark posts, including vertical jump, break their numbers down sport by sport. This one stops at gender and level. Maximum velocity has no combine behind it. Sport-level data comes from three sources that do not compare to each other: match tracking peaks, controlled radar or laser testing, and top speeds modelled from timing-gate splits.

Match data is the most common of the three and the least useful as a benchmark. A peak speed recorded in a game measures how fast an athlete had a reason to run, not how fast they can run. Across three NFL seasons, cornerbacks averaged a game peak of 1.05 over a flying ten and offensive linemen 1.61. The lineman is not slow. He plays a position where nothing asks him to reach top speed. Devices disagree too, so a pooled table would rank equipment as much as athletes.

Understanding Your Numbers

Protocol matters more than most coaches expect. Change the equipment or the starting procedure and the time can move more than years of training would move it. Fly-in distance is the most common culprit.

Four things need to stay constant between tests: build-up distance, gate height, surface, and footwear. Set gates just above hip height so an arm swing does not break the beam early. Mark the build-up on the ground rather than judging it by eye. Changing the start and gate setup between sessions makes a season of results impossible to compare.

Maturity matters too. Peak velocity changes sharply through the growth spurt, so where an athlete sits in that window shapes how they compare against any group. For a middle school or high school athlete, their own previous tests carry more information than a band that pools different maturity stages.

What to Do With a Benchmark

The table tells you where an athlete sits. It does not tell you what to do next. That answer depends on how the flying ten compares against the athlete's other numbers rather than against the population. An athlete in the advanced band on a 10-yard dash and the average band on a flying ten is an accelerator who has never trained top speed. The reverse profile appears regularly in taller athletes who cover ground well once they are moving. Sprint mechanical profiles tend to vary more between individuals than between sports, which is the argument for testing both ends of the sprint. Reading jump, sprint, and strength data together is what turns a single result into a training decision.

There is a second reason to run this test often. Regular exposure to near-maximal sprinting is now treated as part of hamstring injury management rather than a risk to minimize. Flying sprints in the 90 to 95% range are also a documented way to improve sprint performance directly. A flying ten is one of the few tests that requires the athlete to actually reach top speed, so it doubles as the exposure.

Test it every four to six weeks, hold the protocol constant, and read the trend rather than the single result. The table matters most the first time an athlete is measured. After that the useful comparison is against their own previous number.


References

  1. Ruf, L., Altmann, S., Kloss, C., & Härtel, S. (2024). Normative reference centiles for sprint performance in high-level youth soccer players: The need to consider biological maturity. Pediatric Exercise Science, 36(4), 192–200. https://doi.org/10.1123/pes.2023-0186
  2. Tønnessen, E., Svendsen, I. S., Olsen, I. C., Guttormsen, A., & Haugen, T. (2015). Performance development in adolescent track and field athletes according to age, sex and sport discipline. PLOS ONE, 10(6), e0129014. https://doi.org/10.1371/journal.pone.0129014
  3. Vescovi, J. D., Rupf, R., Brown, T. D., & Marques, M. C. (2011). Physical performance characteristics of high-level female soccer players 12–21 years of age. Scandinavian Journal of Medicine & Science in Sports, 21(5), 670–678. https://doi.org/10.1111/j.1600-0838.2009.01081.x
  4. Haugen, T. A., Tønnessen, E., & Seiler, S. (2012). Speed and countermovement-jump characteristics of elite female soccer players, 1995–2010. International Journal of Sports Physiology and Performance, 7(4), 340–349. https://doi.org/10.1123/ijspp.7.4.340
  5. McClelland, E. L., & Weyand, P. G. (2022). Sex differences in human running performance: Smaller gaps at shorter distances? Journal of Applied Physiology, 133(4), 876–885. https://doi.org/10.1152/japplphysiol.00359.2022
  6. Clark, K. P., Rieger, R. H., Bruno, R. F., & Stearne, D. J. (2019). The National Football League Combine 40-yd dash: How important is maximum velocity? Journal of Strength and Conditioning Research, 33(6), 1542–1550. https://doi.org/10.1519/JSC.0000000000002081
  7. Young, W. B., Duthie, G. M., James, L. P., Talpey, S. W., Benton, D. T., & Kilfoyle, A. (2018). Gradual vs. maximal acceleration: Their influence on the prescription of maximal speed sprinting in team sport athletes. Sports, 6(3), 66. https://doi.org/10.3390/sports6030066 (distance-to-maximum-speed values reported in this paper, originating from Benton, 2000, unpublished thesis, University of Ballarat)
  8. Healy, R., Kenny, I. C., & Harrison, A. J. (2022). Profiling elite male 100-m sprint performance: The role of maximum velocity and relative acceleration. Journal of Sport and Health Science, 11(1), 75–84. https://doi.org/10.1016/j.jshs.2019.10.002
  9. Haugen, T., Seiler, S., Sandbakk, Ø., & Tønnessen, E. (2019). The training and development of elite sprint performance: An integration of scientific and best practice literature. Sports Medicine Open, 5(1), 44. https://doi.org/10.1186/s40798-019-0221-0
  10. Buchheit, M., Simpson, B. M., Peltola, E., & Mendez-Villanueva, A. (2012). Assessing maximal sprinting speed in highly trained young soccer players. International Journal of Sports Physiology and Performance, 7(1), 76–78. https://doi.org/10.1123/ijspp.7.1.76
  11. Vescovi, J. D. (2012). Sprint speed characteristics of high-level American female soccer players: Female Athletes in Motion (FAiM) Study. Journal of Science and Medicine in Sport, 15(5), 474–478. https://doi.org/10.1016/j.jsams.2012.03.006
  12. NFL Next Gen Stats. (2024). Fastest ball carriers, 2024 regular season. https://nextgenstats.nfl.com/stats/top-plays/fastest-ball-carriers
  13. Štuhec, S., Planjšek, P., Čoh, M., & Mackala, K. (2023). Multicomponent velocity measurement for linear sprinting: Usain Bolt's 100 m world-record analysis. Bioengineering, 10(11), 1254. https://doi.org/10.3390/bioengineering10111254
  14. Sanchez, E., Weiss, L., Williams, T., Ward, P., Peterson, B., Wellman, A., & Crandall, J. (2023). Positional movement demands during NFL football games: A 3-year review. Applied Sciences, 13(16), 9278. https://doi.org/10.3390/app13169278
  15. Altmann, S., Ruf, L., Backfisch, M., Thron, M., Woll, A., Walter, L., Kaul, D., Bergdolt, L., & Härtel, S. (2026). Assessing maximal sprinting speed in soccer: Criterion validity of commonly used devices. Science and Medicine in Football, 10(1), 126–131. https://doi.org/10.1080/24733938.2024.2441321
  16. Haugen, T., & Buchheit, M. (2016). Sprint running performance monitoring: Methodological and practical considerations. Sports Medicine, 46(5), 641–656. https://doi.org/10.1007/s40279-015-0446-0
  17. Haugen, T., Tønnessen, E., & Seiler, S. (2012). The difference is in the start: Impact of timing and start procedure on sprint running performance. Journal of Strength and Conditioning Research, 26(2), 473–479. https://doi.org/10.1519/JSC.0b013e318226030b
  18. Jovanović, M., Cabarkapa, D., Andersson, H., Nagy, D., Trunic, N., Bankovic, V., Zivkovic, A., Repasi, R., Safar, S., & Ratgeber, L. (2024). Effects of the flying start on estimated short sprint profiles using timing gates. Sensors, 24(9), 2894. https://doi.org/10.3390/s24092894
  19. Runacres, A., Mackintosh, K. A., & McNarry, M. A. (2024). The effect of sex, maturity, and training status on maximal sprint performance kinetics. Pediatric Exercise Science, 36(2), 98–105. https://doi.org/10.1123/pes.2023-0009
  20. Haugen, T. A., Breitschädel, F., & Seiler, S. (2019). Sprint mechanical variables in elite athletes: Are force-velocity profiles sport specific or individual? PLOS ONE, 14(7), e0215551. https://doi.org/10.1371/journal.pone.0215551
  21. Sandford, G. N., Laursen, P. B., & Buchheit, M. (2021). Anaerobic speed/power reserve and sport performance: Scientific basis, current applications and future directions. Sports Medicine, 51(10), 2017–2028. https://doi.org/10.1007/s40279-021-01523-9
  22. Shah, S., Collins, K., & Macgregor, L. J. (2022). The influence of weekly sprint volume and maximal velocity exposures on eccentric hamstring strength in professional football players. Sports, 10(8), 125. https://doi.org/10.3390/sports10080125
  23. Edouard, P., Mendiguchia, J., Guex, K., Lahti, J., Prince, C., Samozino, P., & Morin, J. B. (2023). Sprinting: A key piece of the hamstring injury risk management puzzle. British Journal of Sports Medicine, 57(1), 4–6. https://doi.org/10.1136/bjsports-2022-105532
  24. Skoglund, A., Strand, M. F., & Haugen, T. A. (2023). The effect of flying sprints at 90% to 95% of maximal velocity on sprint performance. International Journal of Sports Physiology and Performance, 18(3), 248–254. https://doi.org/10.1123/ijspp.2022-0244

Reading next

Average vs Peak Bar Speed: What Each Number Measures and When to Use It
Why Your Laser 40 Is Slower Than the Stopwatch Time

Leave a comment

This site is protected by hCaptcha and the hCaptcha Privacy Policy and Terms of Service apply.