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Fastest marathon times achievable based on extreme value statistics

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  • Kebe, Malick
  • Nadarajah, Saralees

Abstract

Marathons are one of the ultimate challenges of human endeavor. In this paper, we apply extreme value statistics to predict fastest marathon times achievable for ten marathons around the world and for both men and women. We concentrate on the theoretical minimum time for each gender at each venue, irrespective of who runs there. Thus, we measure the potential of each marathon, not the actual performance of the runners.

Suggested Citation

  • Kebe, Malick & Nadarajah, Saralees, 2024. "Fastest marathon times achievable based on extreme value statistics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 652(C).
  • Handle: RePEc:eee:phsmap:v:652:y:2024:i:c:s0378437124005788
    DOI: 10.1016/j.physa.2024.130069
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    References listed on IDEAS

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    1. John H. J. Einmahl & Sander G. W. R. Smeets, 2011. "Ultimate 100‐m world records through extreme‐value theory," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 65(1), pages 32-42, February.
    2. Jean-Renaud Pycke & Véronique Billat, 2022. "Marathon Performance Depends on Pacing Oscillations between Non Symmetric Extreme Values," IJERPH, MDPI, vol. 19(4), pages 1-19, February.
    3. Billat, Véronique & Carbillet, Thomas & Correa, Matthieu & Pycke, Jean-Renaud, 2019. "Detecting the marathon asymmetry with a statistical signature," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 240-247.
    4. Lin, Zhenquan & Meng, Fan, 2018. "Empirical analysis on the runners’ velocity distribution in city marathons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 533-541.
    5. Wang, Shi-dong & Wang, Xin-chuang & Zhang, He-bing, 2015. "Simulation on optimized allocation of land resource based on DE-CA model," Ecological Modelling, Elsevier, vol. 314(C), pages 135-144.
    6. Richard L. Smith & Mark Corbett, 1987. "Measuring Marathon Courses: An Application of Statistical Calibration Theory," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 36(3), pages 283-295, November.
    7. Einmahl, John H. J. & Magnus, Jan R., 2008. "Records in Athletics Through Extreme-Value Theory," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1382-1391.
    8. Beat Knechtle & Stefania Di Gangi & Christoph Alexander Rüst & Elias Villiger & Thomas Rosemann & Pantelis Theo Nikolaidis, 2019. "The role of weather conditions on running performance in the Boston Marathon from 1972 to 2018," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-16, March.
    9. Guo, Junke & Mohebbi, Amin & Zhang, Tian C., 2022. "Application of general unit hydrograph model for marathon finish time distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    10. Kwong, Hok Shing & Nadarajah, Saralees, 2019. "Modelling dynamics of marathons – A mixture model approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
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