After the first World Cup 1987, rugby undergoes rule revisions aimed at more dynamic games. There have been some analyses of the KPIs (Key Performance Indicators) so far, but not many ones as detailed dynamic network structure of tactics concerned with selected attack and defense areas, plays, and human resources. In current study, the tactics for try in Rugby World Cup 2019 was investigated by network centrality, core-periphery analysis and correspondence analysis. Bootstrap test and ROC analysis were used to validate the data of try contribution structure. The average score of try balance of final 8 teams was “3.94” and that of “not win” teams was “-2.23”. We categorized these indices into team performance, and tested Monte Carlo methods with bootstrap hypothesis testing to assess the standardized values. Furthermore, to test the precision of sensitivity and specificity of standardized try balance values, the Area Under the Curve (AUC) of the receiver–operator curve (ROC) analysis was executed. In final 8 stage, the feature of tactics for try in first 20 minutes and last 20 minutes were analyzed. The results suggested the tactics of “attack channel diversity” in first 20 minutes and tactics of “defense and substitute diversity” in last 20 minutes. In addition, network correspondence analysis of the top 4 teams’ performance in the tournament yielded interesting results regarding tactics of the attack and defense methods, and of the transition of human resources.
Published in | American Journal of Sports Science (Volume 9, Issue 1) |
DOI | 10.11648/j.ajss.20210901.12 |
Page(s) | 8-16 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2021. Published by Science Publishing Group |
Network Centrality, Core-periphery, AUC Curve of ROC, Correspondence Analysis, Rugby World Cup 2019, Performance Analysis
[1] | Sasaki, K., Yamamoto, T., Murakami, J., & Ueno, U. (2013b) Defense performance analysis of rugby union in Rugby World Cup 2011: network analysis of the turnover contributors, Performance Analysis of Sport IX, 94-99. |
[2] | Sasaki, K, Yamamoto, T., Miyao M., Katsuta, T., & Kono, I. (2017a). Network centrality analysis to determine the tactical leader of a sports team. International Journal of Performance Analysis in Sport, 17 (6), 822-831. |
[3] | Watson, N., Durbach, J., Hendricks, S., & Stewart, T. (2017). On the validity of team performance indicators in rugby union. International Journal of performance analysis in sport, 17 (4), 609-621. |
[4] | Ungureanu, A. N., Rrustio, P. R., Mattina, L., & Lupo, C. (2019). Biology of sport. 36 (3), 265–272. |
[5] | Bennett, M., Bezodis, N., Shearer, D. A., Locke, D., & Kinduff, L. P. (2019). Descriptive conversion of performance indicators in rugby Union. Journal of Science and medicine in sport, 22, 330-334. |
[6] | Iwai, Y., Iwabuchi, K., Nakayama, M., Kunda, M., Watanabe, I., Yamamoto, T., Murakami, J., Shimozono, H., Terada, Y., Hayasaka, K., Kajiyama, T., Katsuta, T., Kono, I., & Sasaki, K. (2019). Clustering men’s world rugby sevens by temporal attack-defense Performance. Japanese Journal of Rugby Science, 31 (2), 66-68. |
[7] | Inoue, K., Shimozono, S., Yoshida, H., & Kurata, H. (2012). Application of Approximate Pattern Matching in Two Dimensional Spaces to Grid Layout for Biochemical Network Maps, Plos ONE, 7 (6), 37739. |
[8] | Junker. B., & Schreiber, F. (2008). Analysis of Biological Networks. Hoboken (NJ): John & Wiley & Sons, Inc, 1-13. |
[9] | Borgatti, S. P., & Everett, M. G. (1999). Models of core / periphery structures. Social Networks, 21 (4), 375-395. |
[10] | Newell, P., & Timmons, R. (2016). The Globalization and Environment Reader. Hoboken (NJ): Blackwell Publishing. |
[11] | Sanz-Leon, P., Knock, S. A., Spiegler, A., & Jirsa, V. K. (2015). Mathematical framework for large-scale brain network modeling in The Virtual Brain. NeuroImage, 111, 385-430. |
[12] | Suzuki, T. (2017). Network Analysis. 2nd.ed. Tokyo (JPN): Kyouritsu Shuppan. |
[13] | Shalley, C. E., & Perry-Smith, J. E. (2008). The emergence of team creative cognition: the role of diverse outside ties, socio-cognitive network centrality, and team evolution. Strategic Entrepreneurship Journal, 2 (1), 23–41. |
[14] | Sasaki, K., Komatsu, K., Yamamoto, T., Ueno, Y., Katsuta, T., & Kono, I. (2013a). Cognitive societal human values of sports: After the 2011 disaster of Japan. Social Sciences, 2 (1), 1–6. |
[15] | Pereira V. H., Gama, M. C. T., Sousa, F. A. B., Lewis, T. G., Gobatto, C. A., & Manchado-Gobatto, F. B. (2015). Complex network models reveal correlations among network metrics, exercise intensity and role of body changes in the fatigue process. Scientific Report, 2015, 5, 10489. |
[16] | Hambrick M. E. (2019). Social Network Analysis in Sport Research. Cambridge Scholars Publishing. |
[17] | Putnam, R. D. (2001). Bowling alone: The Collapse and Revival of American Community. Simon and Schuster. |
[18] | Sasaki, K., Watanabe, I., Yamamoto, T., Yamashita, S., Tanaka, A., & Okuwaki, T. (2017b). An empirical study of Japanese women's rugby injury 2016. Japanese Journal of Rugby Science, 28 (1), 56-60. |
[19] | Sasaki, K., Sato, H., Nakamura, A., Yamamoto, T., Watanabe, I., Katsuta, T., & Kono, I. (2020). Clarifying the structure of serious head and spine injury in youth Rugby Union players. PLOS ONE, 15 (7), e0235035. |
[20] | Duch, J., Weitzman, J. S., & Amaral, L. A. N. (2010). Qualifying the performance of individual players in a team activity. PloS ONE, 5 (6), e10937. |
[21] | Passos, P., Davis, K., Araujo, D., Paz, N., Minguens, J., & Mendes, J. (2011). Network as a novel tool for studying team ball sports as complex social systems. Journal of Science and Medicine in Sport, 14, 170-176. |
[22] | Yamamoto, Y., & Yokoyama, K. (2011). Common and unique network dynamics in football games. PLOS One, 6 (12), e29638. |
[23] | Zuo, X. N., Ehmke, R., Mennes, M., Imperati, D., Castellanos, F. X., Sporns, O., & Milham, M. P. (2011) Network centrality in the human functional connections. Cereb Cortex, 22 (8), 18621875. |
[24] | Ramos J, Lopes RJ, & Araújo D. (2018). What’s next in complex networks? Capturing the concept of attacking play in invasive team sports. Sports Medicine, 48 (1), 17-28. |
[25] | Kojaku, S. & Matsuda, N. (2018) Core-periphery structure requires something else in the network. New Journal of physics, 20, 043012. |
[26] | Nordlund (2018). Power-relational core–periphery structures: Peripheral dependency and core dominance in binary and valued networks. Network Science, 6 (3), 348-369. |
[27] | Akoberg, A. K. (2007). Understanding diagnostic test 3: Receiver operating characteristic curves. Acta paediatr, 96 (5), 644–647. |
[28] | Fruchterman, T. M. L., and Reingold, E. M. (1991). Graph drawing by force-directed placement. Software, 21 (11), 1129–64. |
[29] | Wan, J. (2011). An Introduction to Bootstrap Analysis. Tokyo (JPN): Kyouritsu Shuppan. |
[30] | Greenwood, J. (2003). Total Rugby. 5th ed. (2003). London (UK): A&C Black. |
[31] | Kirkwood, G., Parekh, N., Ofori-Asenso, R., & Pollock, A. M. (2015). Concussion in youth rugby union and rugby league: a systematic review. British Journal of Sports Medicine, 49 (8), 1-5. |
[32] | Mc Fie, S., Brown, J., Hendricks, S., Posthumus, M., Readhead, C., Lambert, M., September, A., & Viljoen, W. (2016). Incidence and factors associated with concussion injuries at the 2011 to 2014 South African Rugby Union Youth Week Tournaments. Clinical Journal of Sport Medicine, 26 (5), 398-404. |
[33] | Veale, P., Pearce, A. J., & Carlson, J. S. (2007). Profile of position movement demands in elite junior Australian Rules Football James. Journal of Sports Science and Medicine, 10 (12), 3. |
[34] | Quarrie, K., & Hopkins, W. G. (2007). Changes in player characteristics and match activities in Bledisloe Cup rugby union from 1972 to 2004. Journal of Sports Sciences, 25 (8), 895-903. |
[35] | Highman, D. G., Pyne, D. B., Anson, J. M., & Eddy, A. (2012). Movement patterns in rugby sevens: Effects of tournament level, fatigue and substitute players. Journal of Science and Medicine in Sport, 15 (3), 277-282. |
[36] | Rey W., Lago-Ballesteros, J., & Padron-Cabo, A. Timing and tactical analysis of player substitutions in the UEFA Champions League. (2017). International Journal of Performance Analysis in Sport, 17 (6), 840-850. |
[37] | Gregory, J., Denvir, K., Farrell, G., & Simms, C. K. (2019). Does ball carrier technique influence tackler head injury assessment risk in elite rugby union? Journal of Sports Sciences, 37 (3), 262-267. |
[38] | Raftery, M., Tucker, R., & Falvey, E. C. (2019). Getting tough on concussion: how welfare-driven law change may improve player safety—a Rugby Union experience. British Journal of Sports Medicine, 2019-101885. |
[39] | Mitchell, S., and Tierney, G. J. (2020). Sanctioning of breakdown infringements during the knockout stage of the 2019 rugby world cup. International Journal of Sports Science & Coaching, 0 (0), 1-8. Doi.org/10.1177/1747954120970922 |
[40] | Amayo, J., & Tiemery, G. J., (2020). Does tackle height influence offload success in rugby union? Analysis from the 2019 Rugby World Cup. International Journal of sports science & coaching, 0 (0), 1-6. doi.org/10.1177/1747954120973660 |
[41] | Sasaki, K., Furuta, H., & Furukawa, T., (2019). Rugby play network structure which become a node-point in the game. Japanese Journal of Rugby Sciences, 30 (1), 3-9. |
APA Style
Koh Sasaki, Takumi Yamamoto, Ichiro Watanabe, Mitsuyuki Nakayama, Kensuke Iwabuchi, et al. (2021). Network Centrality and Core-periphery Analysis to Clarify the Tactics for Try in Rugby World Cup 2019. American Journal of Sports Science, 9(1), 8-16. https://doi.org/10.11648/j.ajss.20210901.12
ACS Style
Koh Sasaki; Takumi Yamamoto; Ichiro Watanabe; Mitsuyuki Nakayama; Kensuke Iwabuchi, et al. Network Centrality and Core-periphery Analysis to Clarify the Tactics for Try in Rugby World Cup 2019. Am. J. Sports Sci. 2021, 9(1), 8-16. doi: 10.11648/j.ajss.20210901.12
AMA Style
Koh Sasaki, Takumi Yamamoto, Ichiro Watanabe, Mitsuyuki Nakayama, Kensuke Iwabuchi, et al. Network Centrality and Core-periphery Analysis to Clarify the Tactics for Try in Rugby World Cup 2019. Am J Sports Sci. 2021;9(1):8-16. doi: 10.11648/j.ajss.20210901.12
@article{10.11648/j.ajss.20210901.12, author = {Koh Sasaki and Takumi Yamamoto and Ichiro Watanabe and Mitsuyuki Nakayama and Kensuke Iwabuchi and Takashi Katsuta and Ichiro Kono}, title = {Network Centrality and Core-periphery Analysis to Clarify the Tactics for Try in Rugby World Cup 2019}, journal = {American Journal of Sports Science}, volume = {9}, number = {1}, pages = {8-16}, doi = {10.11648/j.ajss.20210901.12}, url = {https://doi.org/10.11648/j.ajss.20210901.12}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajss.20210901.12}, abstract = {After the first World Cup 1987, rugby undergoes rule revisions aimed at more dynamic games. There have been some analyses of the KPIs (Key Performance Indicators) so far, but not many ones as detailed dynamic network structure of tactics concerned with selected attack and defense areas, plays, and human resources. In current study, the tactics for try in Rugby World Cup 2019 was investigated by network centrality, core-periphery analysis and correspondence analysis. Bootstrap test and ROC analysis were used to validate the data of try contribution structure. The average score of try balance of final 8 teams was “3.94” and that of “not win” teams was “-2.23”. We categorized these indices into team performance, and tested Monte Carlo methods with bootstrap hypothesis testing to assess the standardized values. Furthermore, to test the precision of sensitivity and specificity of standardized try balance values, the Area Under the Curve (AUC) of the receiver–operator curve (ROC) analysis was executed. In final 8 stage, the feature of tactics for try in first 20 minutes and last 20 minutes were analyzed. The results suggested the tactics of “attack channel diversity” in first 20 minutes and tactics of “defense and substitute diversity” in last 20 minutes. In addition, network correspondence analysis of the top 4 teams’ performance in the tournament yielded interesting results regarding tactics of the attack and defense methods, and of the transition of human resources.}, year = {2021} }
TY - JOUR T1 - Network Centrality and Core-periphery Analysis to Clarify the Tactics for Try in Rugby World Cup 2019 AU - Koh Sasaki AU - Takumi Yamamoto AU - Ichiro Watanabe AU - Mitsuyuki Nakayama AU - Kensuke Iwabuchi AU - Takashi Katsuta AU - Ichiro Kono Y1 - 2021/01/28 PY - 2021 N1 - https://doi.org/10.11648/j.ajss.20210901.12 DO - 10.11648/j.ajss.20210901.12 T2 - American Journal of Sports Science JF - American Journal of Sports Science JO - American Journal of Sports Science SP - 8 EP - 16 PB - Science Publishing Group SN - 2330-8540 UR - https://doi.org/10.11648/j.ajss.20210901.12 AB - After the first World Cup 1987, rugby undergoes rule revisions aimed at more dynamic games. There have been some analyses of the KPIs (Key Performance Indicators) so far, but not many ones as detailed dynamic network structure of tactics concerned with selected attack and defense areas, plays, and human resources. In current study, the tactics for try in Rugby World Cup 2019 was investigated by network centrality, core-periphery analysis and correspondence analysis. Bootstrap test and ROC analysis were used to validate the data of try contribution structure. The average score of try balance of final 8 teams was “3.94” and that of “not win” teams was “-2.23”. We categorized these indices into team performance, and tested Monte Carlo methods with bootstrap hypothesis testing to assess the standardized values. Furthermore, to test the precision of sensitivity and specificity of standardized try balance values, the Area Under the Curve (AUC) of the receiver–operator curve (ROC) analysis was executed. In final 8 stage, the feature of tactics for try in first 20 minutes and last 20 minutes were analyzed. The results suggested the tactics of “attack channel diversity” in first 20 minutes and tactics of “defense and substitute diversity” in last 20 minutes. In addition, network correspondence analysis of the top 4 teams’ performance in the tournament yielded interesting results regarding tactics of the attack and defense methods, and of the transition of human resources. VL - 9 IS - 1 ER -