Curling Şampiyonalarında Takım Performansı Yordayıcılarının Araştırılması: Başarıyı Yordayan Faktörlerin İncelenmesi

Öz

Curling, Kış Olimpiyat Oyunları'nın en çok izlenen branşlarından biridir. Stratejinin curling için büyük öneme sahip olması nedeniyle curling "buz üzerinde satranç" olarak adlandırılmaktadır. Günümüzde sporla ilgili verilerin hızla artmasıyla birlikte, oyun performansının analizi genel spor performansını iyileştirmek için son derece önemli bir yol sağlamaktadır. Bu araştırmanın amacı, elit seviyedeki curling takımlarının şampiyona performansını etkileyen bazı parametrelerin incelenmesidir. Araştırmada kullanılan veriler, Dünya Curling Federasyonu şampiyona sonuçları veritabanından alınmıştır. Çalışmaya dahil edilen veriler, Dünya Erkek/Kadın Curling Şampiyonası (2021 - 2022 - 2023) ve Avrupa Erkek/Kadın Curling Şampiyonası sonuçlarını (2019 - 2021 - 2022) içermektedir. Çoklu doğrusal regresyon analizi, Draw Shot Challenge mesafesi, atış performansı, çalınan puanlar, çaldırılan puanlar, çekiç hakkı kullanım verimliliği, rakibi bir sayı almaya zorlama durumu ve şampiyonada alınan – verilen edilen puanların farkı gibi bağımsız değişkenlerin takım başarısını ne ölçüde açıkladığını belirlemek için yapılmıştır. İstatistiksel analizler için SPSS 24.0 yazılımı kullanılmıştır. Sonuçlar, R değeri 0.902 ve düzeltilmiş R-kare değeri 0.804 elde edilmiştir. Dünya ve Avrupa Curling Şampiyonalarında takım başarısını etkileyen faktörleri inceleyen bu çalışmada, alınan – verilen puan farkı, draw shot challenge mesafesi ve çekiç hakkı kullanım verimliliğinin şampiyona başarısını yordadığı sonucuna varılmıştır.

Anahtar Kelimeler

• Buz üzerinde satranç
• Strateji
• Maç analizi

Exploring Predictors of Team Performance in Curling Championships: An Investigation of Factors Predicting Success

Öz

Curling is one of the most popular sports of the Olympic Winter Games. As strategy is very important for curling, it is called “chess on the ice”. Given the exponential surge in sports-related data, the analysis of game performance has assumed paramount importance, as it provides a valuable avenue for improving overall athletic performance. The aim of this research was to examine the effect of some parameters on championship performance of elite level curling teams. The data used in this study were taken from the World Curling Federation Historical Results database. World Mens/Womens Curling Championships (2021 – 2022 – 2023) and European Mens/Womens Curling Championships results (2019 – 2021 – 2022) included in the study. A multiple linear regression analysis was conducted to determine the extent to which the independent variables, namely Draw Shot Challenge distance, shot performance, stolen points for, stolen points against, hammer efficiency, force efficiency, and difference of generated and given points, explained team success. Statistical Package for Social Sciences 24.0 software used for statistical analyses. The results revealed an R-value of 0.902 and an adjusted R-squared value of 0.804. In the study investigating the factors influencing team success in World and European Curling Championships, it was concluded that the difference of points generated and given points, Draw Shot Challenge distance, and hammer use efficiency predicts championship success.

Anahtar Kelimeler

• Chess on the ice
• Strategy
• Game analysis

Kaynakça

1. Ahmad, Z. F., Holte, R. C., & Bowling, M. (2016). Action selection for hammer shots in curling. IJCAI, (pp. 561-567). Retrieved from: https://www.ijcai.org/Proceedings/16/Papers/086.pdf
2. Bradley, J. L. (2009). The sports science of curling: A Practical review. Journal of Sports Science & Medicine, 8(4), 495. Retrieved from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3761524/
3. Buckingham, M.-P., Marmo, B. A., & Blackford, J. R. (2006). Design and use of an instrumented curling brush. Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications, 220(4), 199-205. https://doi.org/10.1243/14644207JMDA70
4. Collins, J., & Durand-Bush, N. (2010). Enhancing the cohesion and performance of an elite curling team through a self-regulation intervention. International Journal of Sports Science & Coaching, 5(3), 343-362. https://doi.org/10.1260/1747-9541.5.3.343
5. Collins, J., & Durand-Bush, N. (2014). Strategies used by an elite curling coach to nurture athletes’ self-regulation: A Single case study. Journal of Applied Sport Psychology, 26(2), 211-224. https://doi.org/10.1080/10413200.2013.819823
6. Collins, J., & Durand-Bush, N. (2019). The Optimal team functioning model: A Grounded theory framework to guide teamwork in curling. Journal of Applied Sport Psychology, 31(4), 405-426. https://doi.org/10.1080/10413200.2018.1512536
7. David, C. (2012). An Analysis of curling strategy. Journal of Quantitative Analysis in Sports, 8(3), 1-15. https://doi.org/10.1515/1559-0410.1500
8. Gwon, J., Kim, H., Bae, H., & Lee, S. (2020). Path planning of a sweeping robot based on path estimation of a curling stone using sensor fusion. Electronics, 9(3), 457. https://doi.org/10.3390/electronics9030457

9. Haggerty, M. (2013). From island to ice: A Journey of curling stones. World Curling Federation. https://worldcurling.org/2013/09/from-island-to-ice-a-journey-of-curling-stones/
10. Heo, M.-H., & Kim, D. (2013). The development of a curling simulation for performance improvement based on a physics engine. Procedia Engineering, 60, 385-390. https://doi.org/10.1016/j.proeng.2013.07.048
11. Howard, R. (2010). Curl to win: Expert advice to improve your game. Harper Collins.
12. Hughes, M. (2003). Notational analysis. In T. Reilly (Ed.), Science and Soccer (pp. 253-272). Routledge.
13. Hughes, M., Robertson, K., & Nicholson, A. (1988). An analysis of 1984 World Cup of association football. In T. Reilly, A. Lees, K. Davids & W. Murphy (Eds.) Science and Football (363-367). E&FN Spon.
14. Ito, T., & Kitasei, Y. (2015). Proposal and implementation of "digital curling". 2015 IEEE Conference on Computational Intelligence and Games (CIG), (pp. 469-473). Retrieved from: https://ieeexplore.ieee.org/abstract/document/7317945
15. Kawamura, T., Kamimura, R., Suzuki, S., & Iizuka, K. (2015). A study on the curling robot will match with human result of one end game with one human. 2015 IEEE Conference on Computational Intelligence and Games (CIG), (pp. 489-495). IEEE. Retrieved from: https://ieeexplore.ieee.org/abstract/document/7317934
16. Kim, C.-H., & Yoon, H. (2008). The analysis on the world curling games for the improvement in performance ability. The Korea Journal of Sports Science, 17(2), 47-57. https://doi.org/10.1016/j.proeng.2013.07.048
17. Kim, H. (2009). The analysis on result of junior curling games. The Korea Journal of Sports Science, 18(1), 1109-1117.
18. Kim, T.-W., Lee, S.-C., Kil, S.-K., Choi, S.-H., & Song, Y.-G. (2021). A Case study on curling stone and sweeping effect according to sweeping conditions. International Journal of Environmental Research and Public Health, 18(2), 833. https://doi.org/10.3390/ijerph18020833
19. Kostuk, K. J., & Willoughby, K. A. (2006). Curling's paradox. Computers & Operations Research, 33(7), 2023-2031. https://doi.org/10.1016/j.cor.2004.09.026
20. Kostuk, K.J., Willoughby, K.A., & Saedt, A. P. (2001). Modelling curling as a Markov process. European Journal of Operational Research, 133(3), 557-565. https://doi.org/10.1016/S0377-2217(00)00202-2
21. Lee, S., Park, S., Kim, T., & Kil, S. (2019). Development of speed/trajectory measurement system using smart glasses for beginning or unskilled curlers. Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology, 233(1), 145-159. https://doi.org/10.1177/1754337118809864
22. Marmo, B., Farrow, I., Buckingham, M., & Blackford, J. (2006). Frictional heat generated by sweeping in curling and its effect on ice friction. Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications, 220(4), 189-197. https://doi.org/10.1243/14644207JMDA93
23. Marmo, B. A., Buckingham, M.-P., & Blackford, J. R. (2006). Optimising sweeping techniques for Olympic Curlers. In The Engineering of Sport 6 (pp. 249-254). Springer. Retrieved from: https://link.springer.com/chapter/10.1007/978-0-387-45951-6_45
24. Masui, F., Hirata, K., Otani, H., Yanagi, H., & Ptaszynski, M. (2016). Informatics to support tactics and strategies in curling. International Journal of Automation Technology, 10(2), 244-252. https://doi.org/10.20965/ijat.2016.p0244
25. Neyedly, A. (2012). Filling up the house: building an appraisal strategy for curling archives in Manitoba. University of Manitoba (Canada). Retrieved from: https://www.proquest.com/docview/1322073524?pq-origsite=gscholar&fromopenview=true&sourcetype=Dissertations%20&%20Theses
26. Otani, H., Masui, F., Hirata, K., Yanagi, H., & Ptaszynski, M. (2016). Analysis of curling team strategy and tactics using Curling Proceedings of the 4th International Congress on Sport Sciences Research and Technology Support (icSPORTS 2016), 182-187. Retrieved from: https://www.scitepress.org/papers/2016/60446/60446.pdf
27. Paquette, K. J., & Sullivan, P. (2012). Canadian curling coaches’ use of psychological skills training. The Sport Psychologist, 26(1), 29-42. https://doi.org/10.1123/tsp.26.1.29
28. Park, S., & Lee, S. (2017). The characteristic analysis of winners and losers in curling: Focused on shot type, shot accuracy, blank end and average score. Korean Journal of Sport Science, 28(2), 517-528.
29. Park, S. G., & Lee, S. (2013). Curling Analysis based on the possession of the last stone per end. Procedia Engineering, 60, 391-396. https://doi.org/10.1016/j.proeng.2013.07.028
30. Schumaker, R.P., Solieman, O.K., & Chen, H. (2010). Sports data mining: The field. In R. Sharda & Stefan Voß (Eds.) Sports Data Mining, (1-13). Springer. Retrieved from: https://link.springer.com/chapter/10.1007/978-1-4419-6730-5_1
31. Shank, V. (2012). Attentional demands in the execution phase of Curling. University of Ottawa (Canada). Shank, V., & Lajoie, Y. (2013). Attentional demands in the execution phase of curling in novices and experts. International Journal of Kinesiology & Sports Science, 1(1), 1-8. http://dx.doi.org/10.7575/aiac.ijkss.v.2n.1p.1
32. Steele, A. M., Johnson, B. T., & Kraft, J. (2014). Physical fitness levels for beginning curlers. Research Quarterly for Exercise and Sport, 85(S1), A87.
33. Stewart, N. W., & Hall, C. (2016). The effects of cognitive general imagery use on decision accuracy and speed in curling. The Sport Psychologist, 30(4), 305-313. https://doi.org/10.1123/tsp.2016-0001
34. Tamminen, K.A., & Crocker, P.R. (2013). “I control my own emotions for the sake of the team”: Emotional self-regulation and interpersonal emotion regulation among female high-performance curlers. Psychology of Sport and Exercise, 14(5), 737-747. https://doi.org/10.1016/j.psychsport.2013.05.002
35. Turriff, S. (2016). Curling: Steps to success. Human Kinetics.
36. Westlund-Stewart, N., & Hall, C. (2017). The effects of cognitive general imagery training on decision-making abilities in curling: A single-subject multiple baseline approach. Journal of Applied Sport Psychology, 29(2), 119-133. https://doi.org/10.1080/10413200.2016.1213331
37. Wieting, S. G., & Lamoureux, D. (2019). Curling in Canada. In S. G. Wieting (Ed.) Sport and memory in North America (pp. 140-153). Routledge.
38. Willoughby, K. A., & Kostuk, K. J. (2004). Preferred scenarios in the sport of curling. Interfaces, 34(2), 117-122. https://doi.org/10.1287/inte.1030.0049
39. Willoughby, K. A., & Kostuk, K. J. (2005). An analysis of a strategic decision in the sport of curling. Decision Analysis, 2(1), 58-63. https://doi.org/10.1287/deca.1050.0032
40. Yanagi, H., Miyakoshi, K., Nakajima, Y., Yamamoto, N., & Isaka, T. (2008). Measurement of forces exerted during sweeping in curling. ISBS-Conference Proceedings Archive. Retrieved from: https://ojs.ub.uni-konstanz.de/cpa/article/view/1996