• William A. Sands U.S. Ski and SNOWboard Association, Park City, USA - Retired
  • Gregory C. Bogdanis National & Kapodistrian University of Athens – School of Physical Education & Sport Science, Athens, Greece
  • Gabriella Penitente Sheffield Hallam University – Academy of Sport and Physical Activity, Sheffeld, UK
  • Olyvia Donti National & Kapodistrian University of Athens – School of Physical Education & Sport Science, Athens, Greece



Media, Internet, Google


Despite information from world media, worldwide interest in artistic gymnastics has never been assessed. Memberships, equipment and apparel purchases, subscriptions, and other data have been used as indirect substitutes for gauging interest and participation in gymnastics. A readily available tool for assessing gymnastics interest could be of use in uncovering myriad trends. Aim of Study: This study sought to use a relatively new internet search tool called Google TrendsTM (GT) to assess gymnastics interest by records of search terms used in GoogleTM. Methods: GoogleTM searches involve the use of search terms that are recorded and then accessible by GT. As GoogleTM searches provide access to topics of interest nearly anywhere in the world, by anyone with internet access, then using Google TrendsTM, then GT could be used to harvest the number and types of searches involving the search-terms “men’s gymnastics” and “women’s gymnastics.” The tally of the search terms was obtained using filters such as country, region, and others. GT reports the search-term trends by calculating a relative percentage based on a sample of the largest number of specific search-term use during a particular time. Although the relative percentage approach is somewhat awkward, processing large amounts of data may be considered valuable and otherwise unattainable. Results and Conclusions: Results should be interpreted cautiously. However, the analysis revealed a litany of important trends in the worldwide interest in gymnastics.


Download data is not yet available.


Albert, J., Glickman, M. E., Swartz, T. B., & Koning, R. H. (2017). Handbook of Statistical Methods and Analyses in Sports. Boca Raton, FL: CRC Press. DOI:

Arora, V. S., Stuckler, D., & McKee, M. (2016). Tracking search engine queries for suicide in the United Kingdom, 2004-2013. Public Health, 137, 147-153. doi:10.1016/j.puhe.2015.10.015 DOI:

Avilez, J. L., Zevallos-Morales, A., & Taype-Rondan, A. (2017). Use of enhancement drugs amongst athletes and television celebrities and public interest in androgenic anabolic steroids. Exploring two Peruvian cases with Google Trends. Public Health, 146, 29-31. doi:10.1016/j.puhe.2017.01.011 DOI:

Biesecker, L. G. (2013). Hypothesis-generating research and predictive medicine. Genome Research, 23(7), 1051-1053. doi:10.1101/gr.157826.113 DOI:

Bogage, J. (2017). Youth sports study: Declining participation, rising costs and unqualified coaches. Retrieved from

Brown, E. W., Clark, M. A., Ewing, M. E., & Malina, R. M. (1998). Participation in youth sports: benefits and risks. Spotlight on Youth Sports, 21(2), 1-4.

Carlson, D., Scott, L., Planty, M., & Thompson, J. (2005). What Is the Status of High School Athletes 8 Years after Their Senior Year? Statistics in Brief. NCES 2005-303. Retrieved from Jessup, MD:

Catalani, V., Prilutskaya, M., Al-Imam, A., Marrinan, S., Elgharably, Y., Zloh, M., . . . Corazza, O. B. S., 8, 34. . (2018). Octodrine: New Questions and Challenges in Sport Supplements. Brain Sci, 8(2), 34. doi:10.3390/brainsci8020034 DOI:

Cervellin, G., Comelli, I., & Lippi, G. (2017). Is Google Trends a reliable tool for digital epidemiology? Insights from different clinical settings. J Epidemiol Glob Health, 7(3), 185-189. doi:10.1016/j.jegh.2017.06.001 DOI:

Cha, Y.-S., Hwang, S.-M., & Yang, P.-J. (2019). Achilles Tendon Injury and Seasonal Variation: An Analysis Using Google Trends. Korean J Sports Med, 37(4), 155-161. Retrieved from DOI:

D 'Jaen, M. D. (2007). Breaching the Great Firewall of China: Congress Overreaches in Attacking Chinese Internet Censorship. Seattle University Law Review, 31, 327-351.

Dewan, V., & Sur, H. (2018). Using google trends to assess for seasonal variation in knee injuries. Journal of Arthroscopy and Joint Surgery, 5(3), 175-178. doi: DOI:

Dowell, W. T. (2006). The Internet, Censorship, and China. 7 Geo. J. Int'l Aff, 111, 112.

F.I.G., F. I. d. G. (2020). Population. Retrieved from

Garrison, S. R., Dormuth, C. R., Morrow, R. L., Carney, G. A., & Khan, K. M. (2015). Seasonal effects on the occurrence of nocturnal leg cramps: a prospective cohort study. CMAJ: Canadian Medical Association Journal, 187(4), 248-253. doi:10.1503/cmaj.140497 DOI:

Governali, P., Gustafson, W., & Yelton, J. (2013). Coaches Column. Journal of Health, Physical Education, Recreation, 29(9), 44-45. doi:10.1080/00221473.1958.10630434 DOI:

Hand, D. J. (2020). Dark Data. Princeton, NJ: Princeton University Press.

Huberty, C. J., & Morris, J. D. (1989). Multivariate analysis versus multiple univariate analyses. Psychological Bulletin, 105(2), 302-308. DOI:

Hudson, M. A. (1988). World gymnastics officials say score fixing is hard to control. Los Angeles Times, 1,8.

Hunter, P. V., Delbaere, M., O'Connell, M. E., Cammer, A., Seaton, J. X., Friedrich, T., & Fick, F. (2017). Did online publishers "get it right"? Using a naturalistic search strategy to review cognitive health promotion content on internet webpages. BMC Geriatrics, 17(1), 125. doi:10.1186/s12877-017-0515-3 DOI:

Kerman, A. (2020). Gymnastics participation report. Retrieved from

Khurshudyan, I. (2020). Russia is bolstering its internet censorship powers – is it turning into China? Retrieved from

Lewis, M. (2003). Moneyball: The Art of Winning an Unfair Game. New York, NY: W. W. Norton & Company.

Lock, S. (2020). Participants in gymnastics in the U.S. from 2006 to 2017 Retrieved from

Mavragani, A., & Ochoa, G. (2019). Google Trends in Infodemiology and Infoveillance: Methodology Framework. JMIR Public Health Surveill, 5(2), e13439. doi:10.2196/13439 DOI:

Meyers, D. (2016). The End of the Perfect 10. New York: Touchstone.

Mnadla, S., Bragazzi, N. L., Rouissi, M., Chaalali, A., Siri, A., Padulo, J., . . . Knechtle, B. (2016). Infodemiological data of Ironman Triathlon in the study period 2004-2013. Data Brief, 9, 123-127. doi:10.1016/j.dib.2016.08.040 DOI:

Morgulev, E., Azar, O. H., & Lidor, R. (2018). Sports analytics and the big-data era. International Journal of Data Science and Analytics, 5(4), 213-222. doi:10.1007/s41060-017-0093-7 DOI:

North, J. (2012). Further development of the gymnastics participant model. (Project Report). Leeds Beckett University, Leeds Metropolitan University. Retrieved from

Nuti, S. V., Wayda, B., Ranasinghe, I., Wang, S., Dreyer, R. P., Chen, S. I., & Murugiah, K. (2014). The use of google trends in health care research: a systematic review. PloS One, 9(10), e109583. doi:10.1371/journal.pone.0109583 DOI:

Pajek, M. B., Cuk, I., Pajek, J., Kovac, M., & Leskosek, B. (2013). Is the quality of judging in women artistic gymnastics equivalent at major competitions of different levels? J Hum Kinet, 37, 173-181. doi:10.2478/hukin-2013-0038 DOI:

Petlichkoff, L. M. (1992). Youth sport participation and withdrawal: Is it simply a matter of FUN? Pediatric Exercise Science, 4, 105-110. DOI:

Porter, M. L. (1993). Exploratory data analysis uncovers unexpected relationships. Personal Engineering and Instrumentation News, 10(12), 21-28.

Ryan, M., Harrison, S., & Ismael, S. T. (2017). Forecasting Sports Popularity: Application of Time Series Analysis. Academic Journal of Interdisciplinary Studies, 6(2). Retrieved from DOI:

Ryan, T. J. (2012). SGMA: Olympics do impact sports participation.

Rynecki, N. D., Siracuse, B. L., Ippolito, J. A., & Beebe, K. S. (2019). Injuries sustained during high intensity interval training: are modern fitness trends contributing to increased injury rates? Journal of Sports Medicine and Physical Finess, 59(7), 1206-1212. doi:10.23736/s0022-4707.19.09407-6 DOI:

Sagiroglu, S., & Sinanc, D. (2013). Big data: A review. Paper presented at the 2013 International Conference on Collaboration Technologies and Systems (CTS), San Diego, CA. DOI:

Schneier, B. (2015). Data and Goliath: W.W. Norton & Company.

Shenk, D. (1997). Data smog. San Francisco, CA: HarperEdge.

Siegel, E. (2016). Predictive Analytics. Hoboken, NJ: Wiley and Sons.

Stein, M., Janetzko, H., Seebacher, D., Jäger, A., Nagel, M., Hölsch, J., . . . Grossniklaus, M. (2017). How to make sense of team sport data: from acquisition to data modeling and research aspects. Data, 2(1), 2. Retrieved from DOI:

Stoll, C. (1995). Silicon snake oil. New York, NY: Doubleday.

Tay Wee Teck, J., & McCann, M. (2018). Tracking internet interest in anabolic-androgenic steroids using Google Trends. The International journal on drug policy, 51, 52-55. doi:10.1016/j.drugpo.2017.11.001 DOI:

Tran, U. S., Andel, R., Niederkrotenthaler, T., Till, B., Ajdacic-Gross, V., & Voracek, M. (2017). Low validity of Google Trends for behavioral forecasting of national suicide rates. PloS One, 12(8), e0183149. doi:10.1371/journal.pone.0183149 DOI:

Trends, G. (2013). Understanding Google Trends Retrieved from

Wiley, K. E., Steffens, M., Berry, N., & Leask, J. (2017). An audit of the quality of online immunisation information available to Australian parents. BMC Public Health, 17(1), 76. doi:10.1186/s12889-016-3933-9 DOI:

Zhou, X., Ye, J., & Feng, Y. (2011). Tuberculosis surveillance by analyzing Google trends. IEEE Transactions on Biomedical Engineering, 58(8). doi:10.1109/tbme.2011.2132132 DOI:







How to Cite

Sands, W. A., Bogdanis, G. C., Penitente, G., & Donti, O. (2021). ASSESSING INTEREST IN ARTISTIC GYMNASTICS. Science of Gymnastics Journal, 13(1), 5-18.

Similar Articles

You may also start an advanced similarity search for this article.