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The fastest nonprofessional age group IRONMAN triathletes in the world originate from Europe

Abstract Bale, J. Kenyan running before the 1968 Mexico Olympics. In East African Running (ed. Francis, T.) (Routledge, 2007). Introduction Institute of Primary Care, University of Zurich, Zurich, Switzerland Google Scholar González-Ravé, J. M., Hermosilla, F., González-Mohíno, F., Casado, A. & Pyne, D. B. Training intensity distribution, training volume, and periodization models in elite swimmers: […]

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January 6, 2025

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The fastest nonprofessional age group IRONMAN triathletes in the world originate from Europe

Abstract

Bale, J. Kenyan running before the 1968 Mexico Olympics. In East African Running (ed. Francis, T.) (Routledge, 2007).

Introduction

Institute of Primary Care, University of Zurich, Zurich, Switzerland
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González-Ravé, J. M., Hermosilla, F., González-Mohíno, F., Casado, A. & Pyne, D. B. Training intensity distribution, training volume, and periodization models in elite swimmers: A systematic review. Int. J. Sports Physiol. Perform. 16(7), 913–926. https://doi.org/10.1123/ijspp.2020-0906 (2021).Article
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Differences between women and men considering race course characteristics.An important finding was that optimal air temperature ranged between 19 °C and 21 °C or at 25–28 °C and optimal water temperature was at 23–25 °C. To date, we have no specific knowledge for the ‘best’ temperatures to compete in an IRONMAN triathlon. It is, however, well known that environmental conditions have a considerable influence on endurance performance in running³⁹ and triathlon⁴⁰ where especially high temperatures impair endurance performance⁴¹. Regarding IRONMAN Hawaii, it has been reported that body core temperature increased during the marathon where an increase in body core temperature appeared to make triathletes run more slowly⁴². The present study shows the optimum race temperatures for both cycling and running where athletes can now select the most appropriate race course for a fast IRONMAN race time.

Methods

Ethical approval

Mantzios, K. et al. Effects of weather parameters on endurance running performance: discipline-specific analysis of 1258 races. Med. Sci. Sports Exerc. 54(1), 153–161. https://doi.org/10.1249/MSS.0000000000002769 (2022).

Data set and data preparation

Conceptualization: Beat Knechtle. Data curation: Beat Knechtle, Elias Villiger. Formal analysis: David Valero. Methodology: Beat Knechtle. Writing – original draft: Beat Knechtle, Mabliny Thuany. Writing – Editing: Katja Weiss, Thomas Rosemann, Pantelis T. Nikolaidis, Rodrigo Luiz Vancini, Marilia Santos Andrade.

Statistical analysis

PDP charts for water temperature in the swim course during race day.

Results

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Distributions of race finish times by sex

DOI: https://doi.org/10.1038/s41598-024-84008-9

Ranking tables of event locations and tri-athletes’ countries of origin

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Table 1 List of origin of the athletes sorted by country with the number of finishers. The race times are color-coded where darker fields represent faster race times.

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Table 2 List of races sorted by the number of finishers. The race times are color-coded where darker fields represent faster race times.

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The PDP chart is another tool we have to look into our model. PDP charts show how the output of the model varies for each numerical predicting variables (features or factors). According to the XG Boost model PDP charts, men are on average ~ 0.8 h faster than women (Fig. 4), and the fastest athletes are aged 25—34 years (Fig. 5). The XGBoost model shows that a representative set of European countries including Germany, Austria, Denmark, Belgium, Switzerland, Norway, Czechia, Estonia, and Slovenia are the fastest. The USA and a group of Asian countries including Philippines, Malaysia, and Thailand appear to be the slowest (Fig. 6). IRONMAN Hawaii is the IRONMAN race location with the fastest race times, but also IRONMAN Vitoria-Gasteiz and IRONMAN Hamburg are singled out by the XG Boost model among the fastest race courses (Fig. 7). Regarding temperatures, optimal air temperature ranged at 19–21 or 25–28°Celsius (Fig. 8), and optimal water temperatures at 23–25°Celsius (Fig. 9).This study aimed to identify the dominant nationalities for nonprofessional IRONMAN triathlon competitions between 2002 and 2020 with the hypothesis that the fastest IRONMAN age group triathletes would originate from the USA. The most important findings were (i) European countries (i.e. Germany, Austria, Denmark, Belgium, Switzerland, Norway, Czechia, Estonia, and Slovenia) have the fastest athletes, (ii) IRONMAN Hawaii, IRONMAN Vitoria-Gasteiz and IRONMAN Hamburg are the fastest races, (iii) optimal air temperature for cycling and running ranged between 19 °C and 21 °C or at 25–28 °C and optimal water temperature for swimming was at 23–25 °C, (iv) the fastest athletes were 25–34 years old, and (v) men were ~ 0.9 h faster than women. The discussion of these findings is challenging, especially due to the lack of evidence in the scientific literature. However, the main finding highlights the importance of adopting similar approaches in order to identify the most successful countries in sports competitions.

Multi linear regression (MLR) ordinary least squares (OLS) regressor

David Valero

Table 3 Results of the OLS linear regressor.

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Decision tree and random forest regressors

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XG boost regressor

Understanding the age demographics of world-class IRONMAN triathletes who emerge victorious and stand out as the fastest is crucial for several reasons¹⁸. First, it provides valuable information on the optimal age range for peak athletic performance in long-distance triathlons, offering guidance to both aspiring and experienced athletes on when their training efforts may yield the best results. Additionally, such knowledge helps sports scientists, coaches, and trainers tailor training regimens that consider age-specific physiological changes, helping athletes maximize their potential while minimizing the risk of injury. Moreover, recognizing the age groups dominating IRONMAN competitions contributes to a deeper understanding of the sport’s evolving dynamics and may influence the development of age-specific talent pipelines or training programs^19,20. In general, investigating the age demographics of top-performing IRONMAN athletes enhances our understanding of the physiological nuances of the sport and has practical implications for optimizing training strategies across different age cohorts.

SHAP values and features importances for the XG boost model

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Partial dependence plots (PDP) of the XG boost model

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Air and water temperature versus race time—3D interaction charts by model

Researching and identifying the countries from which the fastest non-professional IRONMAN triathletes emerge, along with their age groups, is of significant importance for several reasons. Firstly, such information provides valuable insight into the global distribution of talent in the sport, allowing for a more comprehensive understanding of the geographical patterns of high-performance triathletes outside the professional realm²⁶. This knowledge can be instrumental in the formation of training programs, talent identification strategies, and the allocation of resources within different nations. Second, analyzing the age groups of the fastest non-professional IRONMAN triathletes offers critical data on the optimal stages of life for achieving peak performance in this demanding endurance sport. This information can guide coaches, trainers, and athletes in tailoring training regimens that consider age-related physiological changes and potential peak performance windows^27,28. It also helps in the development of age-specific training methodologies to optimize athletic potential at various stages of life. In addition, understanding the demographics of nonprofessional IRONMAN triathletes contributes to a wider promotion of sport and the adoption of a healthy and active lifestyle. Highlighting the diverse age groups and nationalities of successful participants encourages a broader population to participate in triathlons, fostering a sense of inclusivity and inspiration for aspiring athletes.

Discussion

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European athletes were the fastest

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Most of the athletes originated from the USA, followed by United Kingdom, Canada, Australia, Germany, France, Spain, Sweden, Brazil, Austria, and Italy for the 10 first countries.

The fastest race courses

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The aspect of environmental conditions

In summary, researching the countries and age groups of the fastest nonprofessional IRONMAN triathletes is essential for shaping targeted training approaches, fostering global sporting development, and promoting the sport’s inclusivity and accessibility to individuals of all ages and backgrounds^26,29. Despite the importance of professional athletes for the representativeness of the countries at the national level, nonprofessional athletes should be studied to amplify the evidence regarding the fastest countries. Therefore, the purpose of this study was to identify the age group of athletes of the fastest countries competing in IRONMAN events between 2002 and 2020. Based upon existing knowledge we hypothesized that the fastest IRONMAN age group triathletes would also originate from the USA.Poczta, J. & Malchrowicz-Mosko, E. Mass triathlon participation as a human need to set the goals and cross the borders. How to understand the triathlete?. Olimpianos J. Olympi. Stud. 8, 9. https://doi.org/10.30937/2526-6314.v4.id114 (2020).

The influence of race course characteristics

Cote, J., Macdonald, D., Baker, J. & Abernethy, B. When, “where” is more important than “when”: Birthplace and birthdate effects on the achievement of sporting expertise. J. Sports Sci. 24(10), 1065–1073. https://doi.org/10.1080/02640410500432490 (2006).

Limitations

A total of 677,320 IRONMAN finishers´ records (544,632 from men and 132,688 from women) from the top 150 countries by number of records, participating in 443 IRONMAN events over 65 different locations between 2002 and 2022 were analyzed.

Conclusion

Accepted: 19 December 2024

Data availability

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References

Article

Google Scholar
Piacentini, M. F., Vleck, V. & Lepers, R. Effect of age on the sex difference in Ironman triathlon performance. Movement Sport Sci. https://doi.org/10.1051/sm/2019030 (2019).
Marilia Santos AndradeArticle
PubMed

Google Scholar
The XGB model is built with 50 estimators, max depth of 9 and learning rate of 0.3, to obtain a R² score of 0.27 over the 25% held-out test set. Whilst the highest score of the three ML models tested, this is still a low R² score meaning the model can only explain 27% of the variability in the predicted variable, and that more predictors should be considered, if any predictive expectations are to be had. But we can still use the tools in our model interpretability toolset to look for insights into what the model learnt.Knechtle, B., Villiger, E., Weiss, K. et al. The fastest nonprofessional age group IRONMAN triathletes in the world originate from Europe.
Sci Rep 15, 1028 (2025). https://doi.org/10.1038/s41598-024-84008-9
Despite the use of a data set of nearly 700,000 IRONMAN triathletes and the large time frame of 20 years, we are not sure whether all races correctly measured their split distances. Furthermore, since thousands of athletes compete in an IRONMAN race, athletes can cycle in packages during the cycling split⁵⁰, although drafting in cycling in an IRONMAN race is not allowed. Drafting while cycling can considerably improve performance, reduce the cycling split time, and improve the subsequent running split performance⁵¹. The biopsychosocial factors and intrinsic and extrinsic motivation that led to elite performance in professional and nonprofessional athletes are different. It is extremely important to differentiate and highlight this in the research problem and justification. This could even be the objective of future research. In another way, by analyzing and comparing the athletic achievements of different countries in these events, researchers can discern patterns, trends, and potential influencing factors that contribute to superior athletic performance⁵². These findings not only contribute to understanding the competitive dynamics within the IRONMAN community but also have broader implications for sports science, training methodologies, and potentially national-level athletic development strategies²⁷. Further, the study may serve as a foundation for future research, helping athletes, coaches, and sports enthusiasts improve their understanding of the factors that contribute to success in this challenging endurance sport.
Article
PubMed

Google Scholar
Article
PubMed

Google Scholar
Çetin, A. Triathletes’ motivational dimensions for participation in ironman, and comparison of these factors with their life satisfaction and achievement perceptions. Int. J. Hum. Move. Sports Sci. 7(3), 43–50. https://doi.org/10.13189/saj.2019.070301 (2019).Article
CAS
PubMed

Google Scholar
You can also search for this author in
PubMed Google ScholarBritton, E. & Foley, R. Sensing water: Uncovering health and well-being in the sea and surf. J. Sport Social Issues 45(1), 60–87. https://doi.org/10.1177/0193723520928597 (2021).
Jafarnezhadgero, A., Eskandari, S., Sajedi, H. & Dionisio, V. C. Long-term effects of running exercises on natural grass, artificial turf, and synthetic surfaces on ground reaction force components in individuals with overpronated feet: A randomized controlled trial. Gait Posture 109, 28–33. https://doi.org/10.1016/j.gaitpost.2024.01.016 (2024).Article
MATH

Google Scholar
Ultra Sports Science Foundation, Pierre-Benite, FranceWells, M. S. & Marwood, S. Effects of power variation on cycle performance during simulated hilly time-trials. Eur. J. Sport Sci. 16(8), 912–918. https://doi.org/10.1080/17461391.2016.1156162 (2016).
Article
MATH

Google Scholar
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
The first two ML models, attempted over several configurations, obtained best values of MAE of 1.27 and 1.26 h, respectively. They both obtain a best R² score of 0.25. This is an improvement over the linear MLR model, but still a low R² score (weak effect) by any measure.Article
PubMed
PubMed Central

Google Scholar
Carpenter, J., Frank, R. & Huet-Vaughn, E. Gender differences in interpersonal and intrapersonal competitive behavior. J. Behav. Exp. Econ. 77, 170–176. https://doi.org/10.1016/j.socec.2018.10.003 (2018).Article
PubMed

Google Scholar
Article
MATH

Google Scholar
You can also search for this author in
PubMed Google Scholar
Poczta, J. & Malchrowicz-Mośko, E. From half-marathon to triathlon: sports participation as a reflection of post-materialism processes in polish society. Olimpianos J. Olympic Stud. 5, 141–151. https://doi.org/10.30937/2526-6314.v5.id128 (2021).You can also search for this author in
PubMed Google Scholar
Correspondence to
Beat Knechtle.Article

Google Scholar
Puccinelli, P. et al. Origin and age group of the fastest amateur triathletes competing in ‘Ironman Hawaii’ between 2003 and 2019. Sports Med. Health Sci. https://doi.org/10.1016/j.smhs.2023.07.008 (2023).Article

Google Scholar
Race data from all official IRONMAN races was downloaded from the official IRONMAN website (www.ironman.com) using a Python script. The sex, age group, country of origin of the athletes, location and year of the event, and times for swimming, running, cycling, overall race times, and transition were therefore obtained. The data was inspected for consistency, removing duplicate and/or incomplete records. Similarly, the event location variable was harmonized to map generic values to their actual location. Race times were re-calculated to hours and are expressed with two decimal digits. Additional location specific data was added and merged with the race data, including average air and water temperatures in °Celsius (in integer form, that is, without any decimals), and the type of race course in each split discipline as categorical variables, including the values of rolling, hilly, and flat for the bike and run race courses, and lake, ocean, river, bay, reservoir for the different swim courses. The race records were separately aggregated by event location and by country, to produce two large ranking tables sorted by number of race records (i.e. participation). In doing so, we identified up to 228 different countries in the original data sample, many of them with 1, 2 or 3 records and hence with no statistical interest. We then decided to limit the analysis to the top 150 countries by number of records, which account for 99.94% of the full sample and includes countries with at least 13 race records, while eliminating noise, which is in turn good for computing, interpretation, and overall interest. After the pre-processing and merging of the data, the final dataset consisted of a total of 677,320 finishers´ records (i.e. 544,632 from men and 132,688 from women) from the top 150 countries by number of records, participating in 443 events over 65 different locations between 2002 and 2022.Regarding water temperature, it is well known that water temperature has a direct effect on swimming performance⁴³. However, little is described in the scientific literature. A very recent study reported that swimming in a river had in female triathletes a greater effect on overall race time than cycling or running⁴⁰. Whit the present findings, triathletes can also better select an IRONMAN race regarding the swim course temperatures and the influence on overall race time.
Article

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This study was approved by the Institutional Review Board of Kanton St. Gallen, Switzerland, with a waiver of the requirement for informed consent of the participants as the study involved the analysis of publicly available data (EKSG 01/06/2010). The study was conducted in accordance with recognized ethical standards according to the Declaration of Helsinki adopted in 1964 and revised in 2013.
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Beat Knechtle, Elias Villiger, Katja Weiss & Thomas Rosemann
Berri, D. J., Deutscher, C. & Galletti, A. Born in the USA: National origin effects on time allocation in US and Spanish professional basketball. Natl. Inst. Econ. Rev. 232, R41–R50. https://doi.org/10.1177/002795011523200105 (2015).Georgiades, E., Klissouras, V., Baulch, J., Wang, G. & Pitsiladis, Y. Why nature prevails over nurture in the making of the elite athlete. BMC Genom. 18(8), 835. https://doi.org/10.1186/s12864-017-4190-8 (2017).
Article

Google Scholar
Kasović, M., Škrinjarić, B. & Štefan, L. Macro and meso indicators of success pertaining to European countries in elite triathlon. Int. Sci. J. Kinesiol. 13(2), 49–56 (2020).
Usually, these approaches associate the performance of these countries in the most important championships worldwide, to verify those achieving outstanding performance². Even though most of the studies are developed in the context of elite sports, the popularity of sports among countries also presents important indicators regarding the popularity of sports among nonprofessional athletes⁹, and the importance of the sport among residents. For example, for endurance sports, previous literature has shown that running is part of the culture of East African countries, also influencing the practice among nonprofessional athletes^10,11.Thuany, M. et al. A machine learning approach to finding the fastest race course for professional athletes competing in Ironman® 703 races between 2004 and 2020. Int. J. Environ. Res. Public Health 20(4), 3619. https://doi.org/10.3390/ijerph20043619 (2023).
Wattie, N., Schorer, J. & Baker, J. Seeing the forest but not the trees: Heterogeneity in community size effects in Canadian ice hockey players. J. Sports Sci. 36(4), 436–444. https://doi.org/10.1080/02640414.2017.1313444 (2018).Received: 22 February 2024
Jürgens, D. et al. An analysis of participation and performance by nationality at “Ironman Switzerland” from 1995 to 2011. J. Sci. Cycl. 1(2), 10–20 (2012).Article

Google Scholar
Google Scholar
For the top countries by the number of age group records, Germany, Austria, Denmark, Belgium, Switzerland, Norway, Czechia, Estonia, and Slovenia were the fastest. These results are similar to those found by professional IRONMAN 70.3 triathletes²¹. The emergence of Germany, Austria, Denmark, Belgium, Switzerland, Norway, Czechia, Estonia, and Slovenia within the IRONMAN context may be attributed to a combination of unique factors such as geography, climate, and culture^34,35. Many participants are drawn to IRONMAN triathlons as a means to improve their physical capabilities, seeking personal growth and the satisfaction of overcoming a multifaceted challenge³⁶. The competitive aspect also plays a role, with participants aiming to test their limits, set personal records, and, in some cases, compete in organized events. This broader inclusivity, coupled with the diverse motivations behind participation, underscores the evolving and accessible nature of triathlons in contemporary society.
Article
PubMed
MATH

Google Scholar
Asgari, B. & Khorshidi, R. The effect of hosting on performance of host countries in summer and winter Olympic Games. Eur. J. Sports Exercise Sci. 2(2), 1–6 (2013).
Rossing, N. N., Stentoft, D., Flattum, A., Côté, J. & Karbing, D. S. Influence of population size, density, and proximity to talent clubs on the likelihood of becoming elite youth athlete. Scand. J. Med. Sci. Sports 28(3), 1304–1313. https://doi.org/10.1111/sms.13009 (2018).Pryor, J. L. et al. Pacing strategy of a full ironman overall female winner on a course with major elevation changes. J. Strength Cond. Res. 32(11), 3080–3087. https://doi.org/10.1519/JSC.0000000000002807 (2018).
Article

Google Scholar
Knechtle, B., Rosemann, T. & Nikolaidis, P. The role of nationality in ultra-endurance sports: The paradigm of cross-country skiing and long-distance running. Int. J. Environ. Res. Public Health https://doi.org/10.3390/ijerph17072543 (2020).
Medbase St. Gallen Am Vadianplatz, Vadianstrasse 26, 9001, St. Gallen, SwitzerlandMölenberg, F. J. M., de Waart, F., Burdorf, A. & van Lenthe, F. J. Hosting elite sport events to target recreational sport participation: An interrupted time series analysis. Int. J. Sport Policy Polit. 12(4), 531–543. https://doi.org/10.1080/19406940.2020.1839530 (2020).
Article
MATH

Google Scholar
Olcina, G., Crespo, C., Timón, R., Mjaanes, J. M. & Calleja-González, J. Core temperature response during the marathon portion of the ironman world championship (Kona-Hawaii). Front. Physiol. 3(10), 1469. https://doi.org/10.3389/fphys.2019.01469 (2019).
Google Scholar
A last important finding was the IRONMAN race course characteristic had a considerable influence on overall race time where slower race times were achieved with hilly cycling and running courses whilst flat surfaces, rolling cycling and ocean swimming were leading to faster race times. It is well known that the running surface has an influence on running performance especially regarding running-related injuries^44,45. Also in cycling, race course characteristics show an influence on race performance⁴⁶ where especially ascents slow cyclists down⁴⁷. Changes in elevation during an IRONMAN race have also an influence on pacing during the cycling split⁴⁸ where downhill segments show an important influence⁴⁹. The present findings may help IRONMAN triathletes to select an appropriate IRONMAN race for their personal achievements.
Nikolaidis, P. T. et al. Predicting overall performance in Ironman 70.3 age group triathletes through split disciplines. Sci. Rep. 13(1), 11492. https://doi.org/10.1038/s41598-023-38181-y (2023).Article
PubMed

Google Scholar
Nikolaidis, P. T., Kach, I., Rosemann, T. & Knechtle, B. The role of nationality on the pacing of ironman triathletes. Asian J. Sports Med. 8(4), e57130. https://doi.org/10.5812/asjsm.57130 (2017).Article
PubMed
PubMed Central

Google Scholar
Article
PubMed
PubMed Central

Google Scholar
Article
PubMed

Google Scholar
Article
CAS
PubMed

Google Scholar
Sousa, C. V., Nikolaidis, P. T. & Knechtle, B. Ultra-triathlon-Pacing, performance trends, the role of nationality, and sex differences in finishers and non-finishers. Scand. J. Med. Sci. Sports 30(3), 556–563. https://doi.org/10.1111/sms.13598 (2020).
Download referencesBouscaren, N., Millet, G. Y. & Racinais, S. Heat stress challenges in marathon versus ultra-endurance running. Front Sports Act. Living 13(1), 59. https://doi.org/10.3389/fspor.2019.00059 (2019).
Comparative studies have been recurrent in sports science^1,2. Generally, these studies are used to verify the performance of countries in different sports disciplines, including the world championships and Olympic Games². Previous literature has indicated that some countries represent a higher likelihood of being successful in specific sports disciplines, such as basketball in the United States (US)³, Kenya and Ethiopia in long-distance running events⁴, and Canada in hockey events⁵. These higher probabilities are related to several factors, including social, economic, cultural, and environmental characteristics^6,7,8.Mitchell, C., McDonnell, S., Oganezova, K., Mockler, D. & Fleming, N. The effect of surface compliance on overground running biomechanics. A systematic review and meta-analysis. Sports Biomech. https://doi.org/10.1080/14763141.2023.2236058 (2023).
PDP charts for country of origin of the athletes.This study was approved by the Institutional Review Board of Kanton St. Gallen, Switzerland, with a waiver of the requirement for informed consent of the participants as the study involved the analysis of publicly available data (EKSG 01/06/2010). The study was conducted following recognized ethical standards according to the Declaration of Helsinki adopted in 1964 and revised in 2013.
Article
PubMed
PubMed Central

Google Scholar
Phillips, K. E. & Hopkins, W. G. Determinants of cycling performance: A review of the dimensions and features regulating performance in elite cycling competitions. Sports Med. Open 6(1), 23. https://doi.org/10.1186/s40798-020-00252-z (2020).
Article
PubMed
PubMed Central

Google Scholar
The authors declare no competing interests.
Distribution of age groups by sex.World Athletics. What it takes to become a Kenyan distance champion: World Athletics, 2022 [cited 2022 20 August]. Available from: https://worldathletics.org/be-active/performance/kenyan-distance-running-reasons-success
The SHAP aggregated values chart in Fig. 3 shows how each predicting variable influences the model output, with the factors rated as more important at the top. The country of origin is the most important predictor. The variable age group comes up as the second most important feature but the one that best separates data points. Red dots (i.e. high or older age groups) contribute positively to the race time, whilst shades of purples and blues increasingly move to the left, deducting from the race times. Sex and the location of the event are the next most important predictors. Further down but with clear separation of red and blue data points, hilly running and cycling race courses add to race time (i.e. slower race times), whilst flat surfaces, rolling cycling and ocean swimming deduct from it (i.e. faster race times).PDP charts for the location where the race was held.
Knechtle, B. et al. Performance and pacing of professional IRONMAN triathletes: The fastest IRONMAN World Championship ever-IRONMAN Hawaii 2022. Sci. Rep. 13(1), 15708. https://doi.org/10.1038/s41598-023-42800-z (2023).A further important finding was that IRONMAN Hawaii was the fastest race course, followed by European race courses such as IRONMAN Vitoria-Gasteiz and IRONMAN Hamburg. The finding that IRONMAN Hawaii is the fastest race course for age group athletes is explained by the fact that IRONMAN Hawaii is the World Championship for IRONMAN triathletes³⁷ where only the best triathletes can compete after qualification for the IRONMAN World Championship³⁸.
Forrest, D., McHale, I. G., Sanz, I. & Tena, J. D. An analysis of country medal shares in individual sports at the Olympics. Eur. Sport Manag. Quart. 17(2), 117–131. https://doi.org/10.1080/16184742.2016.1248463 (2017).Article

Google Scholar
Collins, M. et al. The ACE gene and endurance performance during the South African Ironman Triathlons. Med. Sci. Sports Exerc. 36(8), 1314–1320. https://doi.org/10.1249/01.mss.0000135779.41475.42 (2004).Allebosch, G., Van den Bossche, S., Veelaert, P. & Philips, W. Camera-based system for drafting detection while cycling. Sensors 20(5), 1241 (2020).
PDP charts for age group.Article
ADS
CAS
PubMed
PubMed Central

Google Scholar
Hancock, D. J., Coutinho, P., Côté, J. & Mesquita, I. Influences of population size and density on birthplace effects. J. Sports Sci. 36(1), 33–38. https://doi.org/10.1080/02640414.2016.1276614 (2018).Haugen, T. A. et al. Peak age and performance progression in world-class track-and-field athletes. Int. J. Sports Physiol. Perform. 13(9), 1122–1129 (2018).
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Normality of the race time distributions by sex was checked by visual inspection of race time histograms and calculation of Gaussian overlapping curves. The statistical values of the overall race times (i.e. mean, std, max, and min) were calculated for each of the 65 locations and 150 countries and are displayed in the large ranking tables. The event location ranking table includes specific race course data, including the average air and water temperatures, and the type of race course. An analysis of the race performance by type of race course was done and the results are shown in the form of boxplot charts and accompanying 2-way ANOVA tests that suggest the statistical significance of the different types of swim, bike, and run race courses. The significance level was set at 0.05 in all cases. Several predictive modelling algorithms were tested, including a Multivariate Linear Regressor (MLR) and three Machine Learning (ML) Regressors, a Decision Tree, a Random Forest and a XG Boost Regressor. The predicted variable (i.e. target) was the overall race time (in hours) whilst a total of 17 predictors (i.e. features or factors) were used, including a number of categorical variables that had to be encoded before they could be used with the models. The variable sex (men/women) is encoded as 0 = women and 1 = men. The age group variable is encoded as an integer, representing 5-year groups, with group 18 representing less than 20 years, group 20 from 20 to 24, group 25 from 25 to 29, etc. until group 75 which includes any triathletes older than 75 years of age. The country and event location variables are encoded based on their position in the ranking lists, sorted by participation, and starting with zero. The event location average air and water temperature variables, of numerical type, are used as they are reported on the website of the organizers. The three categorical variables (i.e. swim, bike and run) are converted into dummy variables (binary flags) indicating the presence with 1 and absence with 0, becoming a set of 11 binary variables. Given the large size of the dataset, a hold-out test strategy was used, with 25% of the dataset reserved for model evaluation: 507,076 race records were used for model training, and 169,026 for model evaluation. For each of these models, the Mean Absolute Error (MAE) and the coefficient of determination (R²) were calculated. After training, evaluating, and comparing the three models, XG Boost emerged as the best performer and we present only the results from XG Boost. Model interpretability tools like SHAP or PDP libraries were used to further understand how, according to the models, each predictor influenced the race finish time. All data processing and analysis were performed using Python (www.python.org/) and a Google Colab notebook (https://colab.research.google.com/).Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
PDP charts for sex.Thuany, M., Viljoen, C., Gomes, T. N., Knechtle, B. & Scheer, V. Mental health in ultra-endurance runners: A systematic review. Sports Med. 53(10), 1891–1904. https://doi.org/10.1007/s40279-023-01890-5 (2023).
Stiefel, M., Rüst, C. A., Rosemann, T. & Knechtle, B. A comparison of participation and performance in age-group finishers competing in and qualifying for Ironman Hawaii. Int. J. Gen. Med. 6, 67–77. https://doi.org/10.2147/IJGM.S40202 (2013).Figure 2 shows the difference between women and men regarding the race course characteristics for swimming with swimming in a bay, in the ocean, a river, a lake or a reservoir where men were always faster than women. Also for cycling and running (i.e. flat, rolling, or hilly), men were always faster than women.

Despite the evidence that indicates higher participation and performance indicators among professional athletes from the USA¹⁶, these results present important limitations. The most important aspect refers to the different methodological approaches used among different studies, which impair the generalization of the findings; also, the time frame should be considered, in association with the greater interest in studying professional athletes^21,22,23. Understanding the nuanced interplay of biopsychosocial factors and the intricate balance between intrinsic and extrinsic motivation is crucial when delving into the realms of elite performance in both professional and nonprofessional athletes²⁴. The assertion that these factors differ significantly between the two categories raises pertinent questions about the dynamics that influence athletic peak achievements in diverse contexts²⁵. In professional athletes, factors such as genetic predispositions, access to high-level coaching, and optimal training environments may take precedence, while nonprofessional athletes may be driven by personal goals, societal expectations, and the pursuit of holistic well-being.

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Johnson, E. C. et al. Bike and run pacing on downhill segments predict Ironman triathlon relative success. J. Sci. Med. Sport 18(1), 82–87. https://doi.org/10.1016/j.jsams.2013.12.001 (2015).Figure 10 is an interesting set of 3D charts comparing how each of the three ML models “has learnt” the partial dependence of the race time (target) with the air and water temperature variables together. The third and best performing XG Boost model shows a more detailed (higher resolution) PDP chart.
Stevenson, J. L., Song, H. & Cooper, J. A. Age and sex differences pertaining to modes of locomotion in triathlon. Med. Sci. Sports Exerc. 45(5), 976–984. https://doi.org/10.1249/MSS.0b013e31827d17eb (2013).SHAP aggregated values for XG Boost Regression model.
Foley, R. Swimming in Ireland: Immersions in therapeutic blue space. Health Place 35, 218–225. https://doi.org/10.1016/j.healthplace.2014.09.015 (2015).Article
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Mabliny ThuanyStiefel, M., Knechtle, B., Rüst, C. A., Rosemann, T. & Lepers, R. The age of peak performance in Ironman triathlon: A cross-sectional and longitudinal data analysis. Extreme Physiol. Med. 2(1), 27. https://doi.org/10.1186/2046-7648-2-27 (2013).
For endurance sports, triathlon events have increased among nonprofessional participants¹², especially influenced by events held in the United States, such as the Ironman Hawaii¹³. The sport became popular among adults of both sexes and different age groups, engaging in this activity with different purposes, including health and well-being benefits, as well as to improve physical capacities and participate in competitions^14,15. Previous literature investigating the most successful countries among elite triathletes showed that athletes from the United States presented the best performance, as well as the highest frequency of competitors, and age of peak performance^16,17.Published: 06 January 2025
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In summary, we found that IRONMAN age group athletes from European countries such as Germany, Austria, Denmark, Belgium, Switzerland, Norway, Czechia, Estonia, and Slovenia have the fastest IRONMAN race times although IRONMAN Hawaii is the fastest race course worldwide, most likely due to the fact that IRONMAN Hawaii is the IRONMAN World Championship. With the presented results for optimal air and water temperatures and the description of the optimal cycling and running course characteristics, IRONMAN age group athletes might be able to select an IRONMAN race with the best conditions in order to achieve a fast IRONMAN race time.

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Beat Knechtle

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Elias Villiger

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Department of Physical Education, States University of Pará, Pará, Brazil
Katja Weiss

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The OLS MLR model (Table 3) obtains a R² score of 0.128 and the analysis indicates all features have a statistically significant effect on the finish time variable (p < 0.05). No differentiation is made between test and train subsets for the MLR, but the full sample is used for training and evaluation (in-sample testing).
David Valero

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Mougios, V. & Deligiannis, A. Effect of water temperature on performance, lactate production and heart rate at swimming of maximal and submaximal intensity. J. Sports Med. Phys. Fitness 33(1), 27–33 (1993).
Thomas Rosemann

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Rodrigo Luiz Vancini

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PDP charts for ambient air temperature during race day.

Marilia Santos Andrade

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Dähler, P., Rüst, C., Rosemann, T., Lepers, R. & Knechtle, B. Nation related participation and performance trends in ‘Ironman Hawaii’ from 1985 to 2012. BMC Sports Sci. Med. Rehabil. 6, 16. https://doi.org/10.1186/2052-1847-6-16 (2014).

Mabliny Thuany

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Choi, Y. H., Wei, Q., Zhang, L. & Choi, S.-J. The impact of cultural distance on performance at the summer olympic games. SAGE Open 12(1), 21582440221085264. https://doi.org/10.1177/21582440221085265 (2022).

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Zhao, J., Wu, Y. & Zhang, J. A study of triathletes’ race strategies in different competition environments. Heliyon 10(8), e29454. https://doi.org/10.1016/j.heliyon.2024.e29454 (2024).

Competing interests

Hausswirth, C. et al. Effect of two drafting modalities in cycling on running performance. Med. Sci. Sports Exerc. 33(3), 485–492. https://doi.org/10.1097/00005768-200103000-00023 (2001).

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For this study, we have included official results and split times from the official IRONMAN® website (www.ironman.com) The data sets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

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The country (Table 1) and the event location (Table 2) ranking tables below show the statistical details of the 150 countries of origin and the 65 race locations considered in this study. The tables are sorted by number of records, so countries (or event locations) with higher participation are at the top. Overall race time statistical values (mean, std, min and max) are displayed in hours, and the mean overall race time column is color coded, with darker cells indicating lower (better) race times. The event location table additionally shows the characteristics of each race course, through the categorical variables swim, bike, run, and the average temperatures for water (°C) and air (°C).
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MoveAgeLab, Physical Education Sport Center of Federal, University of Espirito Santo, Vitoria, ES, Brazil
It is well known that elite athletes of specific ethnicities and/or nationalities dominate certain sports disciplines (e.g., East Africans in marathon running). However, we do not know the nationalities of the fastest non-professional IRONMAN triathletes. Therefore, this study intended to identify the fastest athletes by country of origin competing in IRONMAN triathlon events, focusing on non-professional age group triathletes. Data from all IRONMAN age group athletes competing worldwide between 2002 and 2022 in all official IRONMAN races were collected. Sex, age group, country of origin of the athletes, location and year of the event, split times, overall race times, and transition times were obtained. Additionally, the dataset was augmented with specific data (i.e. event characteristics such as temperatures for water and air and course characteristics for all three split disciplines) related to the different race locations. We limited the analysis to the top 150 countries by participation (i.e. countries with at least 13 successful finishers records in the sample). A total of 677,320 records of IRONMAN age group triathletes originating from 150 different countries and participating in 443 races over 65 different locations were analyzed. European countries such as Germany, Austria, Denmark, Belgium, Switzerland, Norway, Czechia, Estonia, and Slovenia have the fastest IRONMAN age group athletes. IRONMAN Hawaii, IRONMAN Vitoria-Gasteiz and IRONMAN Hamburg are the fastest races. Hilly running and cycling race courses led to slower race times, while flat surfaces, rolling cycling and ocean swimming led to faster race times. Optimal water temperatures were found at 23–25 °C and optimal air temperature ranged between 19–21 and 25–28 °C. The fastest IRONMAN age group triathletes from European countries such as Germany, Austria, Denmark, Belgium, Switzerland, Norway, Czechia, Estonia, and Slovenia. With the presented results for optimal air and water temperatures and description of the optimal cycling and running course characteristics, IRONMAN age group athletes might be able to select an IRONMAN race with the best conditions in order to achieve a fast IRONMAN race time.
Rüst, C. A. et al. Nation related participation and performance trends in ‘Norseman Xtreme Triathlon’ from 2006 to 2014. SpringerPlus 4(1), 469. https://doi.org/10.1186/s40064-015-1255-5 (2015).
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Millikan vs South Torrance, CIF Beach Volleyball – The562.org

VIDEO: Millikan vs. Cabrillo, Boys’ Soccer High School Boys’ Soccer: Millikan vs. Cabrillo Cabrillo hosted rivals Millikan in their Moore League opener for the 2021-22 season. For more coverage of all Long Beach sports, head to www.The562.org. We are a non-profit, community-funded media outlet in the City of Long Beach, covering primarily sports and education. […]

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Beach Volleyball Falls To USC In NCAA Championship First Round

Story Links GULF SHORES, Ala. – No. 12 seed North Florida beach volleyball fell to No. 5 USC in the first round of the 2025 NCAA Championship in Gulf Shores, Ala. on Friday. North Florida concludes its season at 26-11. In addition to a program-record win total, North Florida earned its highest […]

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GULF SHORES, Ala. – No. 12 seed North Florida beach volleyball fell to No. 5 USC in the first round of the 2025 NCAA Championship in Gulf Shores, Ala. on Friday.

North Florida concludes its season at 26-11. In addition to a program-record win total, North Florida earned its highest ranking in program history at No. 14 in the latest 2025 AVCA Collegiate Beach Coaches Top 20 Poll. The Ospreys added its sixth Atlantic Sun Conference title and its second-ever and second-straight berth to the NCAA Championship.

Junior tandem Presley Murray and Mackenzie Murphy collected AVCA Top Flight Pair 1 honors, which recognizes pairs who compete in at least 15 matches together at a specific flight and win at least 75 percent of their matches.

USC claimed the dual with wins at the one, two and four lines. The tandem of senior Mariana Feliciano Sanchez and junior Madison Espy forced a third set at three, 15-21, 21-17, while redshirt sophomore Sophia Notaro and senior Andrea Da Silva were tied 17-17 in the second set at five prior to the moment that the decision was clinched.

No. 5 seed USC 3, No. 12 seed North Florida 0

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Meet the teams for the U17s Female National Age Group Championships

May 2, 2025 The GoCardless Swim England Water Polo National Age Group Championships 2025 (U17/U19) take place at the Alan Higgs Sports Centre in Coventry this weekend. In the build up to the competition, we’re taking a closer look at each of the sides that are looking to become national champions in the Midlands on […]

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May 2, 2025

The GoCardless Swim England Water Polo National Age Group Championships 2025 (U17/U19) take place at the Alan Higgs Sports Centre in Coventry this weekend.

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Here, in the penultimate preview, we take a look at the U17 female teams that have qualified for finals weekend.

Each of the previews for the event will be posted on the Swim England website within the water polo hub, whilst those who haven’t had the chance to get their tickets in advance can purchase them on venue, subject to availability.

Worthing

Worthing’s female teams entered the National Age Group Championships for the first time last year and came away with fourth place in both the U17 and U19 event.

One year on and they’ll be hoping that a medal in on the cards after they were only team with a 100% record in qualification.

They overcame Exeter, City of Manchester and Beckenham at Ponds Forge in March to reach the finals, where they’ll take on Liverpool in the opening match of the weekend.

Led by Great Britain’s U18 stars Amelia Cook and Elsie Graves, the South East club will be looking to make history for the club this weekend and Head Coach Lauren Hand says that the team have been working hard in preparation for the competition.

She said: “We were very pleased to top a competitive group in the U17 qualifying round at Sheffield where the girls put in some strong performances against tough opposition.

“We are excited to compete in the final round in Coventry and have been training hard to prepare for this event.

“Most of the squad have been playing together for a while so we are looking forward to developing further as a team, building on our previous success, as well as giving our newer players some valuable experience.

“They’re all looking forward to the opportunity and we hope that we play as well as we possibly can and, most importantly, enjoy the experience.”

Squad: Amelia Cook, Airlia Philippidis, Ashlin Fraser, Jess Fleming, Skye Priede, Scarlett Dore, Elsie Graves, Maia Middleton, Melita Grigaliunaite, Aimee Fleming, Florrie Cooper. Head Coach: Lauren Hand. Assistant Coach: Alastair Roberts. Team Manager: Jen Woodworth.

City of Liverpool

City of Liverpool were the champions in this age group two years ago, claiming the clubs first-ever female U15 title with an 11-6 win against West London Penguin.

In 2025, much of that side return to the National Age Group Championships with goalkeeper of the tournament Isobella Taylor amongst those looking to impress once again in Coventry.

Penguin managed to get somewhat of their revenge to edge out Liverpool for top spot in Group B in the Qualification Round but Liverpool will be hoping that they can come out on top when it matter this weekend.

Ahead of the competition, Liverpool’s captain Abbie Evans shared her excitement of competing on the national stage this weekend.

She said: “We’re super excited to defend our title after winning gold at the U15 National Age Group Championships in 2023!

“We’ve been getting ready with some really tough and competitive National Conference League games, which have been such a great experience for us and so much fun!”

Squad: Jenna Binks, Holly Bromwell, Poppy Clarke, Abbie Evans (C), Nieve Folkes Sophie Freeman, Francesca Horrobin, Francesca Lucas, Tillie McGeehan, Sianna Tamlin, Isobella Taylor, Ataliah Taylor-Potts, Caitlin Wainwright, Lily Watson. Head Coach: Alice Byrne. Assistant Coach: Joanne Mountfield. Team Manager: Jon McGeehan.

West London Penguin

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Both the clubs U15 Open and Female sides came out on top at the Championships in November and this team will be looking to build on that momentum when the club return to the Midlands.

A slow start in last year’s final saw Penguin come up short in Gloucester with the City of Manchester managing to hold on to a 10-8 victory.

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He said: “We are very pleased to qualify for the finals and appreciate the opportunity to play some good quality games this weekend and gain some fantastic experience.”

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They recorded seven wins out of nine in their run to making the finals, only losing to fellow semi-finalists Worthing and City of Liverpool.

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Swim England’s official event’s photographer, Will Johnston Photography, will also be on hand throughout the weekend and the full gallery will be available here.

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From injury to NCAA comeback: Lindsey Sparks’ redemption with Cal Poly Beach Volleyball

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Lindsey Sparks sat on the side of UCLA’s beach volleyball courts for two and a half hours each day, unable to participate in practice yet required to attend every one.

Sparks was not far removed from becoming an NCAA Beach Volleyball champion, having played a pivotal role in the Bruins’ title-winning run as a freshman in 2019.

As a member of the fifth pairing Sparks had secured one of the three wins needed in the championship match, and was named to the 2019 NCAA All-Tournament Team.

In the summer after her sophomore season, the young star tore over a third of the cartilage on the backside of her kneecap as well as dislocating it, putting her final two years into jeopardy.

She underwent an experimental knee surgery for a torn medial patellofemoral ligament and injured cartilage on the patella, and was given a 50% chance she would ever play the sport she loved again.

For her entire junior and senior year seasons, Sparks had been relegated to watching practices and shagging balls when her knee was up to it.

Now, four years after the injury and six years after the championship, Sparks is back in the starting lineup, but this time for Cal Poly.

She just wrapped up her second and final regular season with the team while playing on the No. 3 line and was named an All-Big West Honorable Mention.

“I definitely lost hope I’d ever play again after the year mark,” Sparks said. “Then things took a turn for the better, and I’m just super lucky to be here.”

Finding her way back to the volleyball court was not an easy road for the graduate student, who is in her final year of eligibility after seven years on and off the injury report.

Sparks made her official comeback to NCAA action last season as a Mustang, but she had not expected to leave her former program UCLA, where she had rehabbed her injury.

In 2023, after two years of continuous work to strengthen her knee enough to take on the sand, she reached out to her coaches in the hopes of returning to the program for her sixth year.

Sparks found herself on a Zoom with one coach in September 2023 after receiving positive encouragement on her training all summer, when she received the most shocking news of her college career.

UCLA cut her from the team.

After years of enduring the frustration of being cast aside while she couldn’t play, her shot to prove the doubters wrong had just disappeared with no warning.

Still determined to finish her career as an athlete, Sparks turned to the transfer portal and caught the attention of Todd Rogers, former gold medalist and Cal Poly’s head coach.

Sparks transfers to Cal Poly

Sparks is in her seventh year of eligibility, using a redshirt year and transferring to Cal Poly as a graduate student in 2024. Emma Arredondo / Mustang News

Sparks had an initial interest in attending Cal Poly, stemming from her love of nature and positive experience in her visit before ultimately choosing UCLA. In fall of 2023, she reached out to Rogers.

Rogers, who previously tried to recruit her as a freshman, “welcomed [her] with open arms,” according to Sparks.

Sparks, after getting her Master’s in Transformative Coaching and Leadership from UCLA, she decided to pursue a Master’s in Nutrition at Cal Poly.

While Rogers knew he was not signing up for a 100 percent healthy Sparks this time around, he saw her as a valuable asset regardless due to her headstrong leadership.

“We’ve always needed more of those people who are comfortable caring for someone but are also giving them the elbow and saying ‘hey, you can be better than that,’” Rogers said.

Sparks got to work starting winter quarter 2024. Still in recovery, it took time for her to adjust to the practice regimen.

While injuries persisted, Sparks noted that the coaching staff allowed her to be active in practice as a leader and supported her through the injury, contrasting with her experience at UCLA.

“It means a lot for them to believe in me through the ups and the downs,” Sparks said. “They don’t just support me when I’m up.”

While it was uncertain where she would be in the lineup, if at all, she proved to be physically capable enough to not just be a starter, but land herself in the No. 3 spot.

Finally somewhat healthy, Sparks reclaimed some of the undeniable talent that had landed her on the All-Pac 12 Second Team in 2021 and the PAC-12 All-Freshman Team in 2019.

Sparks and Perry become reliable duo

That winter, Rogers selected then freshman Quinn Perry to be her partner for the season. Sparks began her Cal Poly career at 24 years old and Perry at 18, but the age gap did not matter, and neither did Sparks’s sudden appearance on the team.

The pair put up an incredible season at the No. 3 spot in 2024, boasting an 18-5 record and earning All-Big West honorable mentions.

In 2025, Rogers separated the two through the first half of the season before bringing them back together. They still hold strong at an 11-4 record this season.

Perry and Sparks work best with each other due to their willingness to have “uncomfortable conversations” about their play and conduct on the court, according to Perry. Their honesty with each other allows them to have a strong bond both on and off the sand.

“My favorite thing about Lindsey is that she is unapologetically herself, which is refreshing especially in this day and age,” Perry said.

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Cal Poly beach volleyball went 1-1 against NCAA No. 1 seed UCLA this season. Emma Arredondo / Mustang News Credit: Emma Arredondo / Mustang News

On April 4, 2025, Sparks found herself in a pivotal matchup in what might have been her last shot to showcase her capabilities against her former team.

Perry and Sparks won in straight sets with Sparks’s former coach Jenny Johnson Jordan coaching against her on the court.

In dramatic fashion, Izzy Martinez and Logan Walter took their matchup 20-18 in the third set, clinching a 3-2 Mustang win.

Sparks had taken her matchup against the Bruins before, this win marked the first time the Mustangs beat the Bruins in program history. Sparks described it as “the sweetest satisfaction ever.”

“I’m not gonna gloat too much, but it really did feel good,” Sparks said.

Sparks got her happy ending, but her sights are set higher. Cal Poly Beach Volleyball has entered the NCAA Championships for the second year in a row and will face off against LSU in the first round.

The only possible scenario where the Mustangs can face off against the No. 1 Bruins again will be if both teams advance to the championship match.

Sparks begins her final collegiate NCAA run at 1 p.m. against Louisiana State University on May 2.

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Cal Poly advances to NCAA Beach Volleyball quarterfinals after sweeping LSU

In the first match of her final NCAA Beach Volleyball Championship run, graduate student Lindsey Sparks made two diving saves to keep their second set alive, setting up her partner sophomore Quinn Perry for a hit back onto LSU’s side for the winning point. The play sealed the win for the No. 3 duo, and […]

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The play sealed the win for the No. 3 duo, and a 3-0 sweep for the No. 6 seed Mustangs against No. 11 seed LSU in their first round matchup in Gulf Shores, Alabama.

The Mustangs bottom three pairs delivered on Friday, with each winning in just two sets to clinch the win and move the Mustangs on to the quarterfinal round of the NCAA Championships.

All five Cal Poly pairs won their first sets, with the No. 1 and No. 2 matches being stopped early after the Mustangs secured the 3 wins needed to take the match.

Cal Poly’s No. 5 pair of freshman Elise Lenahan and senior Abby Reinard took down their opponents in dominant fashion, winning 21-10 in a blowout second set to seal their match.

Lenihan is the only member of the starting lineup who wasn’t a part of their tournament run last year.

No. 4 pair of redshirt junior Ella Connor and senior Madi Nichols also got the quick win, also by a wide margin in their second match, 21-14.

The Mustangs will move on to day two of the NCAA tournament on Saturday, May 3 to face No. 3 seeded Stanford, who won their match against Boise State on Friday.

Stanford beat Cal Poly earlier in the season, in a 4-1 win at the Center of Effort Challenge on April 11.

The Mustangs will be looking for redemption on the NCAA stage Saturday, with the match starting at 9 a.m. in Gulf Shores.

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Southern Illinois Salukis – Official Athletics Website

CARBONDALE, Ill. – Southern Illinois Volleyball has signed five freshmen to its 2025 recruiting class. Meghan Anderson, Emma Christian, Addison Kerr, Julia Laidig and Angelique Pena will join the Salukis in the fall. Head Coach Brittany Harry is proud of her inaugural class and is excited to get to work. Anderson, one of three setters in the […]

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Head Coach Brittany Harry is proud of her inaugural class and is excited to get to work.

Anderson, one of three setters in the class, will bring a winning mindset as the ultimate competitor, Harry believes.

“We are so happy to add Meghan to the Saluki family. She comes from the storied Skutt Catholic program in Omaha and has spent time in the program running a 6-2 and 5-1 during her career there where they have won several 4A State Championships. She has winning in her blood and is a fierce competitor that is sure to add immediate competition into our setter position.”

Christian will join the Salukis as the second Kansas City native, and Harry is excited to use her versatile skill set.

“Emma Christian is a do-it-all kind of player. Having played for Dynasty out of Kansas City she is a high-skilled player who has a really high volleyball IQ on the court. She has spent time as a setter and defensive specialist/libero and she brings this calm competitiveness energy to the court. We are thrilled to add Emma to our Saluki family.”

Kerr’s connection with Harry made her recruitment easier than most, and the first-year head coach is ready to get her into Davies Gym.

“It was so fun recruiting Addie to Carbondale. Addie is from Champaign, which is also my hometown and coincidentally her high school coach at St. Thomas More, Brad Dalton, was my freshman year JV coach way back at Central High School. Add the connection with both of us playing club at Illini Elite, it was an easy ‘yes’ to want Addie to come play for us at SIU. Addie will add depth to the setter position. I knew I was getting a gritty competitor with our common connections and I am so excited that she will be with us this fall in a Saluki uniform.”

Laidig has stayed true to Southern throughout her recruiting process, something that did not go unnoticed by Harry.

“Julia is a defensive specialist from Woodstock, IL who played club for VC United. From my first conversation with Julia, I knew I was getting an all-in kid who would fit the mold of the type of player we will recruit to SIU. It is fairly common for kids to reopen their recruitment when a coaching change occurs but that was not the case with Julia. Julia has stayed committed to SIU volleyball and it was great getting to know her this spring. Julia has experience playing just about every position on the court and I am excited to bring her poise and maturity to our program.”

Pena’s hitting prowess at the net makes her a natural fit for the current roster and has sky-high potential.

“Angie is one of those kids who we just clicked within the recruiting process. Angie is a utility hitter who has spent time at every position at the net. She has been trained with a lot of discipline having spent time playing club at Sports Performance and 1^st Alliance in Chicago. Along with top-notch training, she also brings a high standard of winning with her. Angie has a super high ceiling to improve and we are excited to add her arm to our gym in the fall.”

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