{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T09:56:07Z","timestamp":1777542967618,"version":"3.51.4"},"reference-count":37,"publisher":"Walter de Gruyter GmbH","issue":"3","license":[{"start":{"date-parts":[[2019,12,1]],"date-time":"2019-12-01T00:00:00Z","timestamp":1575158400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/3.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,12,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>This paper investigates the use of network analysis to identify key players on teams, and patterns of passing within teams, in association football. Networks are constructed based on passes made between players, and several centrality measures are investigated in combination with three different methods for evaluating individual passes. Four seasons of data from the Norwegian top division are used to identify key players and analyze matches from a selected team. The networks examined in this work have weights based on three different aspects of the passes made: their probability of being completed, the probability that the team keeps possession after the completed pass, and the probability of the pass being part of a sequence leading to a shot. The results show that using different metrics and network weights leads to the identification of key passers in different phases of play and in different positions on the pitch.<\/jats:p>","DOI":"10.2478\/ijcss-2019-0017","type":"journal-article","created":{"date-parts":[[2019,12,17]],"date-time":"2019-12-17T04:32:21Z","timestamp":1576557141000},"page":"44-68","source":"Crossref","is-referenced-by-count":9,"title":["Analyzing passing networks in association football based on the difficulty, risk, and potential of passes"],"prefix":"10.2478","volume":"18","author":[{"given":"A.S.","family":"Wiig","sequence":"first","affiliation":[{"name":"Department of Industrial Economics and Technology Management , NTNU , Trondheim , Norway"}]},{"given":"E.M.","family":"H\u00e5land","sequence":"additional","affiliation":[{"name":"Department of Industrial Economics and Technology Management , NTNU , Trondheim , Norway"}]},{"given":"M.","family":"St\u00e5lhane","sequence":"additional","affiliation":[{"name":"Department of Industrial Economics and Technology Management , NTNU , Trondheim , Norway"}]},{"given":"L.M.","family":"Hvattum","sequence":"additional","affiliation":[{"name":"Faculty of Logistics , Molde University College , Molde , Norway"}]}],"member":"374","published-online":{"date-parts":[[2019,12,16]]},"reference":[{"key":"2026042808573876566_j_ijcss-2019-0017_ref_001_w2aab3b7b2b1b6b1ab1ab1Aa","doi-asserted-by":"crossref","unstructured":"Arriaza-Ardiles, E., Mart\u00edn-Gonz\u00e1lez, J., Zuniga, M., S\u00e1nchez-Flores, J., de Saa, Y., & Garc\u00eda-Manso, J. (2018). Applying graphs and complex networks to football metric interpretation. Human Movement Science, 57, 236\u2013243.10.1016\/j.humov.2017.08.022","DOI":"10.1016\/j.humov.2017.08.022"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_002_w2aab3b7b2b1b6b1ab1ab2Aa","doi-asserted-by":"crossref","unstructured":"Barrat, A., Barthelemy, M., & Vespignani, A. (2007). The architecture of complex weighted networks: Measurements and models. In: Caldarelli, G., & Vespignani, A., eds., Large Scale Structure And Dynamics Of Complex Networks: From Information Technology to Finance and Natural Science, World Scientific, 67\u201392.10.1142\/9789812771681_0005","DOI":"10.1142\/9789812771681_0005"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_003_w2aab3b7b2b1b6b1ab1ab3Aa","doi-asserted-by":"crossref","unstructured":"Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., & Hwang, D.-U. (2006). Complex networks: Structure and dynamics. Physics Reports, 424, 175\u2013308.10.1016\/j.physrep.2005.10.009","DOI":"10.1016\/j.physrep.2005.10.009"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_004_w2aab3b7b2b1b6b1ab1ab4Aa","doi-asserted-by":"crossref","unstructured":"Brandes, U. (2001). A faster algorithm for betweenness centrality. Journal of Mathematical Sociology, 25, 163\u2013177.10.1080\/0022250X.2001.9990249","DOI":"10.1080\/0022250X.2001.9990249"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_005_w2aab3b7b2b1b6b1ab1ab5Aa","doi-asserted-by":"crossref","unstructured":"Brin, S. & Page, L. (1998). The anatomy of a large-scale hypertextual web search engine. Computer Networks and ISDN Systems, 30, 107\u2013117.10.1016\/S0169-7552(98)00110-X","DOI":"10.1016\/S0169-7552(98)00110-X"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_006_w2aab3b7b2b1b6b1ab1ab6Aa","unstructured":"Clemente, F., Martins, F., & Mendes, R. (2015). There are differences between centrality levels of volleyball players in different competitive levels? Journal of Physical Education and Sport, 15, 272."},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_007_w2aab3b7b2b1b6b1ab1ab7Aa","doi-asserted-by":"crossref","unstructured":"Clemente, F., Martins, F., & Mendes, R. (2016). Social network analysis applied to team sports analysis, Netherlands: Springer International Publishing.10.1007\/978-3-319-25855-3","DOI":"10.1007\/978-3-319-25855-3"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_008_w2aab3b7b2b1b6b1ab1ab8Aa","unstructured":"Csardi, G. & Nepusz, T. (2006). The igraph software package for complex network research. InterJournal, Complex Systems, 1695, 1\u20139."},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_009_w2aab3b7b2b1b6b1ab1ab9Aa","doi-asserted-by":"crossref","unstructured":"Dey, P., Ganguly, M., & Roy, S. (2017). Network centrality based team formation: A case study on T-20 cricket. Applied Computing and Informatics, 13, 161\u2013168.10.1016\/j.aci.2016.11.001","DOI":"10.1016\/j.aci.2016.11.001"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_010_w2aab3b7b2b1b6b1ab1ac10Aa","doi-asserted-by":"crossref","unstructured":"Dijkstra, E. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1, 269\u2013271.10.1007\/BF01386390","DOI":"10.1007\/BF01386390"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_011_w2aab3b7b2b1b6b1ab1ac11Aa","doi-asserted-by":"crossref","unstructured":"Duch, J., Waitzman, J., & Amaral, L. (2010). Quantifying the performance of individual players in a team activity. PloS One, 5, e10937.10.1371\/journal.pone.0010937288683120585387","DOI":"10.1371\/journal.pone.0010937"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_012_w2aab3b7b2b1b6b1ab1ac12Aa","doi-asserted-by":"crossref","unstructured":"Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27, 861\u2013874.10.1016\/j.patrec.2005.10.010","DOI":"10.1016\/j.patrec.2005.10.010"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_013_w2aab3b7b2b1b6b1ab1ac13Aa","doi-asserted-by":"crossref","unstructured":"Fewell, J., Armbruster, D., Ingraham, J., Petersen, A., & Waters, J. (2012). Basketball teams as strategic networks. PloS One, 7, e47445.10.1371\/journal.pone.0047445","DOI":"10.1371\/journal.pone.0047445"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_014_w2aab3b7b2b1b6b1ab1ac14Aa","doi-asserted-by":"crossref","unstructured":"Franks, A., D\u2019Amour, A., Cervone, D., & Bornn, L. (2016). Meta-analytics: tools for understanding the statistical properties of sports metrics. Journal of Quantitative Analysis in Sports, 12, 151\u2013165.10.1515\/jqas-2016-0098","DOI":"10.1515\/jqas-2016-0098"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_015_w2aab3b7b2b1b6b1ab1ac15Aa","doi-asserted-by":"crossref","unstructured":"Freeman, L. (1977). A set of measures of centrality based on betweenness. Sociometry, 35\u201341.10.2307\/3033543","DOI":"10.2307\/3033543"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_016_w2aab3b7b2b1b6b1ab1ac16Aa","doi-asserted-by":"crossref","unstructured":"Freeman, L. (1978). Centrality in social networks conceptual clarification. Social Networks, 1, 215\u2013239.10.1016\/0378-8733(78)90021-7","DOI":"10.1016\/0378-8733(78)90021-7"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_017_w2aab3b7b2b1b6b1ab1ac17Aa","doi-asserted-by":"crossref","unstructured":"Fu, H.-H., Lin, D., & Tsai, H.-T. (2006). Damping factor in Google page ranking. Applied Stochastic Models in Business and Industry, 22, 431\u2013444.10.1002\/asmb.656","DOI":"10.1002\/asmb.656"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_018_w2aab3b7b2b1b6b1ab1ac18Aa","doi-asserted-by":"crossref","unstructured":"Gama, J., Passos, P., Davids, K., Relvas, H., Ribeiro, J., Vaz, V., & Dias, G. (2014). Network analysis and intra-team activity in attacking phases of professional football. International Journal of Performance Analysis in Sport, 14, 692\u2013708.10.1080\/24748668.2014.11868752","DOI":"10.1080\/24748668.2014.11868752"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_019_w2aab3b7b2b1b6b1ab1ac19Aa","doi-asserted-by":"crossref","unstructured":"Gon\u00e7alves, B., Coutinho, D., Santos, S., Lago-Penas, C., Jim\u00e9nez, S., & Sampaio, J. (2017). Exploring team passing networks and player movement dynamics in youth association football. PloS One, 12, e0171156.10.1371\/journal.pone.0171156528374228141823","DOI":"10.1371\/journal.pone.0171156"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_020_w2aab3b7b2b1b6b1ab1ac20Aa","doi-asserted-by":"crossref","unstructured":"H\u00e5land, E., Wiig, A., St\u00e5lhane, M., & Hvattum, L. (2019). Evaluating passing ability in association football. IMA Journal of Management Mathematics, forthcoming.10.1093\/imaman\/dpz004","DOI":"10.1093\/imaman\/dpz004"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_021_w2aab3b7b2b1b6b1ab1ac21Aa","doi-asserted-by":"crossref","unstructured":"Kang, B., Huh, M., & Choi, S. (2015). Performance analysis of volleyball games using the social network and text mining techniques. Journal of the Korean Data and Information Science Society, 26, 619\u2013630.10.7465\/jkdi.2015.26.3.619","DOI":"10.7465\/jkdi.2015.26.3.619"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_022_w2aab3b7b2b1b6b1ab1ac22Aa","unstructured":"Lazova, V. & Basnarkov, L. (2015). PageRank approach to ranking national football teams. arXiv preprint arXiv:1503.01331."},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_023_w2aab3b7b2b1b6b1ab1ac23Aa","doi-asserted-by":"crossref","unstructured":"Liu, X.F., Liu, Y.-L., Lu, X.-H., Wang, Q.-X., & Wang, T.-X. (2016). The Anatomy of the Global Football Player Transfer Network: Club Functionalities versus Network Properties. PLoS ONE 11: e0156504.10.1371\/journal.pone.0156504","DOI":"10.1371\/journal.pone.0156504"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_024_w2aab3b7b2b1b6b1ab1ac24Aa","doi-asserted-by":"crossref","unstructured":"McHale, I. & Relton, S. (2018). Identifying key players in soccer teams using network analysis and pass difficulty. European Journal of Operational Research, 268, 339\u2013347.10.1016\/j.ejor.2018.01.018","DOI":"10.1016\/j.ejor.2018.01.018"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_025_w2aab3b7b2b1b6b1ab1ac25Aa","doi-asserted-by":"crossref","unstructured":"Opsahl, T., Agneessens, F., & Skvoretz, J. (2010). Node centrality in weighted networks: Generalizing degree and shortest paths. Social Networks, 32, 245\u2013251.10.1016\/j.socnet.2010.03.006","DOI":"10.1016\/j.socnet.2010.03.006"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_026_w2aab3b7b2b1b6b1ab1ac26Aa","unstructured":"Opta Sports (2018). World leaders in sports data. https:\/\/www.optasports.com\/, accessed on 13\/4\/2018."},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_027_w2aab3b7b2b1b6b1ab1ac27Aa","unstructured":"Page, L., Brin, S., Motwani, R., & Winograd, T. (1999). The PageRank citation ranking: Bringing order to the web. Technical report, Stanford InfoLab."},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_028_w2aab3b7b2b1b6b1ab1ac28Aa","doi-asserted-by":"crossref","unstructured":"Peixoto, D., Pra\u00e7a, G., Bredt, S., & Clemente, F (2017). Comparison of network processes between successful and unsuccessful offensive sequences in elite soccer. Human Movement, 18, 48\u201354.10.1515\/humo-2017-0044","DOI":"10.1515\/humo-2017-0044"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_029_w2aab3b7b2b1b6b1ab1ac29Aa","unstructured":"Pena, J. & Touchette, H. (2012). A network theory analysis of football strategies. arXiv preprint arXiv:1206.6904."},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_030_w2aab3b7b2b1b6b1ab1ac30Aa","unstructured":"Piette, J., Anand, S., & Pham, L. (2011). Evaluating basketball player performance via statistical network modeling. In: MIT Sloan Sports Analytics Conference."},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_031_w2aab3b7b2b1b6b1ab1ac31Aa","doi-asserted-by":"crossref","unstructured":"Pina, T., Paulo, A., & Ara\u00fajo, D. (2017). Network characteristics of successful performance in association football. A study on the UEFA champions league. Frontiers in Psychology, 8, 1173.10.3389\/fpsyg.2017.01173","DOI":"10.3389\/fpsyg.2017.01173"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_032_w2aab3b7b2b1b6b1ab1ac32Aa","doi-asserted-by":"crossref","unstructured":"Rojas-Mora, J., Ch\u00e1vez-Bustamante, F., del R\u00edo-Andrade, J., & Medina-Valdebenito, N. (2017). A methodology for the analysis of soccer matches based on pagerank centrality. In: Peris-Ortiz, M., \u00c1lvarez-Garc\u00eda, J., & Del R\u00edo Rama, M., eds., Sports Management as an Emerging Economic Activity, Springer, 257\u2013272.10.1007\/978-3-319-63907-9_16","DOI":"10.1007\/978-3-319-63907-9_16"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_033_w2aab3b7b2b1b6b1ab1ac33Aa","unstructured":"Sandefjord Fotball (2017): \u201cSportsplan,\u201d https:\/\/drive.google.com\/file\/d\/0B9wYsNKQFBUFMkRpejFDaFM3OFk\/, (accessed on 10\/04\/2018)."},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_034_w2aab3b7b2b1b6b1ab1ac34Aa","doi-asserted-by":"crossref","unstructured":"Szczepa\u0144ski, \u0141. & McHale, I. (2016). Beyond completion rate: evaluating the passing ability of footballers. Journal of the Royal Statistical Society: Series A (Statistics in Society), 179, 513\u2013533.10.1111\/rssa.12115","DOI":"10.1111\/rssa.12115"},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_035_w2aab3b7b2b1b6b1ab1ac35Aa","unstructured":"Verdens Gang AS (2018): \u201cVG LIVE,\u201d URL https:\/\/vglive.no\/."},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_036_w2aab3b7b2b1b6b1ab1ac36Aa","unstructured":"WhoScored.com (2018): \u201cWhoscored.com,\u201d URL https:\/\/www.whoscored.com\/."},{"key":"2026042808573876566_j_ijcss-2019-0017_ref_037_w2aab3b7b2b1b6b1ab1ac37Aa","unstructured":"Wood, S. (2006): Generalized additive models: an introduction with R, Boca Raton, Florida: Chapman and Hall\/CRC."}],"container-title":["International Journal of Computer Science in Sport"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/content.sciendo.com\/view\/journals\/ijcss\/18\/3\/article-p44.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/reference-global.com\/pdf\/10.2478\/ijcss-2019-0017","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T17:25:32Z","timestamp":1777397132000},"score":1,"resource":{"primary":{"URL":"https:\/\/reference-global.com\/article\/10.2478\/ijcss-2019-0017"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12,1]]},"references-count":37,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2019,12,16]]},"published-print":{"date-parts":[[2019,12,1]]}},"alternative-id":["10.2478\/ijcss-2019-0017"],"URL":"https:\/\/doi.org\/10.2478\/ijcss-2019-0017","relation":{},"ISSN":["1684-4769"],"issn-type":[{"value":"1684-4769","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,12,1]]}}}