{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T04:27:23Z","timestamp":1775795243684,"version":"3.50.1"},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2018,6,29]],"date-time":"2018-06-29T00:00:00Z","timestamp":1530230400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Mach Learn"],"published-print":{"date-parts":[[2019,1]]},"DOI":"10.1007\/s10994-018-5725-1","type":"journal-article","created":{"date-parts":[[2018,6,29]],"date-time":"2018-06-29T11:34:38Z","timestamp":1530272078000},"page":"127-147","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["Probabilistic movement models and zones of control"],"prefix":"10.1007","volume":"108","author":[{"given":"Ulf","family":"Brefeld","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6209-1516","authenticated-orcid":false,"given":"Jan","family":"Lasek","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2949-8781","authenticated-orcid":false,"given":"Sebastian","family":"Mair","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,6,29]]},"reference":[{"key":"5725_CR1","unstructured":"Avci, A., Bosch, S., Marin-Perianu, M., Marin-Perianu, R., & Havinga, P. (2010). Activity recognition using inertial sensing for healthcare, wellbeing and sports applications: A survey. In 23th International conference on architecture of computing systems 2010, pp. 1\u201310."},{"issue":"12","key":"5725_CR2","doi-asserted-by":"publisher","first-page":"1025","DOI":"10.2165\/00007256-200838120-00006","volume":"38","author":"S Barris","year":"2008","unstructured":"Barris, S., & Button, C. (2008). A review of vision-based motion analysis in sport. Sports Medicine, 38(12), 1025\u20131043.","journal-title":"Sports Medicine"},{"issue":"5","key":"5725_CR3","doi-asserted-by":"publisher","first-page":"338","DOI":"10.1002\/sam.11318","volume":"9","author":"J Brooks","year":"2016","unstructured":"Brooks, J., Kerr, M., & Guttag, J. (2016). Using machine learning to draw inferences from pass location data in soccer. Statistical Analysis and Data Mining: The ASA Data Science Journal, 9(5), 338\u2013349.","journal-title":"Statistical Analysis and Data Mining: The ASA Data Science Journal"},{"issue":"1","key":"5725_CR4","first-page":"39","volume":"22","author":"M Byrne","year":"2013","unstructured":"Byrne, M., Parry, T., Isola, R., & Dawson, A. (2013). Identifying road defect information from smartphones. Road & Transport Research, 22(1), 39\u201350.","journal-title":"Road & Transport Research"},{"issue":"5","key":"5725_CR5","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1016\/j.jsams.2009.09.004","volume":"13","author":"AJ Coutts","year":"2010","unstructured":"Coutts, A. J., Quinn, J., Hocking, J., Castagna, C., & Rampinini, E. (2010). Match running performance in elite Australian rules football. Journal of Science and Medicine in Sport, 13(5), 543\u2013548.","journal-title":"Journal of Science and Medicine in Sport"},{"issue":"1","key":"5725_CR6","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1145\/1327452.1327492","volume":"51","author":"J Dean","year":"2008","unstructured":"Dean, J., & Ghemawat, S. (2008). MapReduce: Simplified data processing on large clusters. Communications of the ACM, 51(1), 107\u2013113.","journal-title":"Communications of the ACM"},{"issue":"8","key":"5725_CR7","doi-asserted-by":"publisher","first-page":"2911","DOI":"10.1016\/j.patcog.2010.03.009","volume":"43","author":"T D\u2019Orazio","year":"2010","unstructured":"D\u2019Orazio, T., & Leo, M. (2010). A review of vision-based systems for soccer video analysis. Pattern Recognition, 43(8), 2911\u20132926.","journal-title":"Pattern Recognition"},{"issue":"6","key":"5725_CR8","doi-asserted-by":"publisher","first-page":"1652","DOI":"10.1016\/j.humov.2012.04.006","volume":"31","author":"S Fonseca","year":"2012","unstructured":"Fonseca, S., Milho, J., Travassos, B., & Ara\u00fajo, D. (2012). Spatial dynamics of team sports exposed by voronoi diagrams. Human Movement Science, 31(6), 1652\u20131659.","journal-title":"Human Movement Science"},{"issue":"1","key":"5725_CR9","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1214\/14-AOAS799","volume":"9","author":"A Franks","year":"2015","unstructured":"Franks, A., Miller, A., Bornn, L., & Goldsberry, K. (2015). Characterizing the spatial structure of defensive skill in professional basketball. The Annals of Applied Statistics, 9(1), 94\u2013121.","journal-title":"The Annals of Applied Statistics"},{"issue":"6","key":"5725_CR10","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1002\/scj.20254","volume":"36","author":"A Fujimura","year":"2005","unstructured":"Fujimura, A., & Sugihara, K. (2005). Geometric analysis and quantitative evaluation of sport teamwork. Systems and Computers in Japan, 36(6), 49\u201358.","journal-title":"Systems and Computers in Japan"},{"issue":"3","key":"5725_CR11","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1016\/j.jvlc.2007.11.001","volume":"19","author":"B Gottfried","year":"2008","unstructured":"Gottfried, B. (2008). Representing short-term observations of moving objects by a simple visual language. Journal of Visual Languages & Computing, 19(3), 321\u2013342.","journal-title":"Journal of Visual Languages & Computing"},{"issue":"2","key":"5725_CR12","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1007\/s10707-009-0095-2","volume":"15","author":"B Gottfried","year":"2011","unstructured":"Gottfried, B. (2011). Interpreting motion events of pairs of moving objects. GeoInformatica, 15(2), 247\u2013271.","journal-title":"GeoInformatica"},{"key":"5725_CR13","first-page":"199","volume-title":"A real-time tracking system for football match and training analysis","author":"Tvd Gr\u00fcn","year":"2011","unstructured":"Gr\u00fcn, Tvd, Franke, N., Wolf, D., Witt, N., & Eidloth, A. (2011). A real-time tracking system for football match and training analysis (pp. 199\u2013212). Berlin Heidelberg: Springer."},{"issue":"2","key":"5725_CR14","doi-asserted-by":"publisher","first-page":"22:1","DOI":"10.1145\/3054132","volume":"50","author":"J Gudmundsson","year":"2017","unstructured":"Gudmundsson, J., & Horton, M. (2017). Spatio-temporal analysis of team sports. ACM Computing Surveys, 50(2), 22:1\u201322:34.","journal-title":"ACM Computing Surveys"},{"key":"5725_CR15","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.compenvurbsys.2013.09.004","volume":"47","author":"J Gudmundsson","year":"2014","unstructured":"Gudmundsson, J., & Wolle, T. (2014). Football analysis using spatio-temporal tools. Computers, Environment and Urban Systems, 47, 16\u201327.","journal-title":"Computers, Environment and Urban Systems"},{"key":"5725_CR16","unstructured":"Haase, J. & Brefeld, U. (2014). Mining positional data streams. In International workshop on new frontiers in mining complex patterns, pp. 102\u2013116. Springer."},{"key":"5725_CR17","unstructured":"Harmon, M., Lucey, P., & Klabjan, D. (2016). Predicting shot making in basketball learnt from adversarial multiagent trajectories. ArXiv e-prints."},{"key":"5725_CR18","doi-asserted-by":"crossref","unstructured":"Horton, M., Gudmundsson, J., Chawla, S., & Estephan, J. (2015). Automated classification of passing in football. In Pacific-Asia conference on knowledge discovery and data mining, pp. 319\u2013330. Springer.","DOI":"10.1007\/978-3-319-18032-8_25"},{"key":"5725_CR19","doi-asserted-by":"crossref","unstructured":"Janetzko, H., Sacha, D., Stein, M., Schreck, T., Keim, D.\u00a0A., & Deussen, O. (2014). Feature-driven visual analytics of soccer data. In 2014 IEEE conference on visual analytics science and technology (VAST), pp. 13\u201322.","DOI":"10.1109\/VAST.2014.7042477"},{"issue":"2","key":"5725_CR20","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1007\/s10994-015-5520-1","volume":"102","author":"K Knauf","year":"2016","unstructured":"Knauf, K., Memmert, D., & Brefeld, U. (2016). Spatio-temporal convolution kernels. Machine Learning, 102(2), 247\u2013273.","journal-title":"Machine Learning"},{"issue":"2","key":"5725_CR21","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1080\/24748668.2009.11868478","volume":"9","author":"C Lago-Pe\u00f1as","year":"2009","unstructured":"Lago-Pe\u00f1as, C., Rey, E., Lago-Ballesteros, J., Casais, L., & Dom\u00ednguez, E. (2009). Analysis of work-rate in soccer according to playing positions. International Journal of Performance Analysis in Sport, 9(2), 218\u2013227.","journal-title":"International Journal of Performance Analysis in Sport"},{"key":"5725_CR22","doi-asserted-by":"crossref","unstructured":"Lasek, J. & Gagolewski, M. (2015). The winning solution to the AAIA\u201915 data mining competition: Tagging firefighter activities at a fire scene. In 2015 Federated conference on computer science and information systems (FedCSIS), pages 375\u2013380.","DOI":"10.15439\/2015F418"},{"issue":"6","key":"5725_CR23","doi-asserted-by":"publisher","first-page":"639","DOI":"10.1080\/13658810500105572","volume":"19","author":"P Laube","year":"2005","unstructured":"Laube, P., Imfeld, S., & Weibel, R. (2005). Discovering relative motion patterns in groups of moving point objects. International Journal of Geographical Information Science, 19(6), 639\u2013668.","journal-title":"International Journal of Geographical Information Science"},{"key":"5725_CR24","unstructured":"Le, H.\u00a0M., Carr, P., Yue, Y., & Lucey, P. (2017). Data-driven ghosting using deep imitation learning. In MIT sloan sports analytics conference."},{"issue":"12","key":"5725_CR25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1371\/journal.pone.0168768","volume":"11","author":"D Link","year":"2016","unstructured":"Link, D., Lang, S., & Seidenschwarz, P. (2016). Real time quantification of dangerousity in football using spatiotemporal tracking data. PLoS ONE, 11(12), 1\u201316.","journal-title":"PLoS ONE"},{"key":"5725_CR26","unstructured":"Lucey, P., Bialkowski, A., Carr, P., Foote, E., & Matthews, I. (2012). Characterizing multi-agent team behavior from partial team tracings: Evidence from the English Premier League. InProceedings of the twenty-sixth AAAI conference on artificial intelligence, AAAI\u201912, pp. 1387\u20131393. AAAI Press."},{"issue":"13","key":"5725_CR27","first-page":"61","volume":"2016","author":"JD Mazimpaka","year":"2016","unstructured":"Mazimpaka, J. D., & Timpf, S. (2016). Trajectory data mining: A review of methods and applications. Journal of Spatial Information Science, 2016(13), 61\u201399.","journal-title":"Journal of Spatial Information Science"},{"key":"5725_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s40279-016-0562-5","volume":"47","author":"D Memmert","year":"2016","unstructured":"Memmert, D., Lemmink, K. A. P. M., & Sampaio, J. (2016). Current approaches to tactical performance analyses in soccer using position data. Sports Medicine, 47, 1\u201310.","journal-title":"Sports Medicine"},{"key":"5725_CR29","doi-asserted-by":"crossref","unstructured":"Mohan, P., Padmanabhan, V.\u00a0N., & Ramjee, R. (2008). Nericell: Rich monitoring of road and traffic conditions using mobile smartphones. In Proceedings of the 6th ACM conference on embedded network sensor systems, SenSys \u201908, pp. 323\u2013336. ACM.","DOI":"10.1145\/1460412.1460444"},{"key":"5725_CR30","unstructured":"Mutschler, C., Ziekow, H., & Jerzak, Z. (2013). The DEBS 2013 grand challenge. In Proceedings of the 7th ACM international conference on distributed event-based systems, DEBS \u201913, pp. 289\u2013294, New York, NY: ACM."},{"key":"5725_CR31","unstructured":"Nakanishi, R., Maeno, J., Murakami, K., & Naruse, T. (2009). An approximate computation of the dominant region diagram for the real-time analysis of group behaviors. In Robot soccer world cup, pp. 228\u2013239. Springer."},{"key":"5725_CR32","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1016\/j.physa.2014.06.037","volume":"412","author":"T Narizuka","year":"2014","unstructured":"Narizuka, T., Yamamoto, K., & Yamazaki, Y. (2014). Statistical properties of position-dependent ball-passing networks in football games. Physica A: Statistical Mechanics and its Applications, 412, 157\u2013168.","journal-title":"Physica A: Statistical Mechanics and its Applications"},{"key":"5725_CR33","unstructured":"Paefgen, J., Michahelles, F., & Staake, T. (2011). GPS trajectory feature extraction for driver risk profiling. In Proceedings of the 2011 international workshop on trajectory data mining and analysis, TDMA \u201911, pp. 53\u201356, New York, NY: ACM."},{"key":"5725_CR34","unstructured":"Rossi, A., Pappalardo, L., Cintia, P., Fernandez, J., Iaia, F.\u00a0M., & Medina, D. (2017). Who is going to get hurt? Predicting injuries in professional soccer. In Proceedings the machine learning and data mining for sports analytics workshop (MLSA\u201917), ECML\/PKDD, CGI \u201900, pp. 227\u2013235."},{"key":"5725_CR35","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1016\/j.is.2014.10.001","volume":"58","author":"LH Son","year":"2016","unstructured":"Son, L. H. (2016). Dealing with the new user cold-start problem in recommender systems: A comparative review. Information Systems, 58, 87\u2013104.","journal-title":"Information Systems"},{"key":"5725_CR36","first-page":"614","volume-title":"What motion patterns tell ss about soccer teams","author":"J Sprado","year":"2009","unstructured":"Sprado, J., & Gottfried, B. (2009). What motion patterns tell ss about soccer teams (pp. 614\u2013625). Heidelberg: Springer."},{"key":"5725_CR37","unstructured":"Taki, T. & Hasegawa, J. (2000). Visualization of dominant region in team games and its application to teamwork analysis. In Proceedings of the international conference on computer graphics, CGI \u201900, pp. 227\u2013235, Washington, DC: IEEE Computer Society."},{"key":"5725_CR38","doi-asserted-by":"crossref","unstructured":"Taki, T., Hasegawa, J., & Fukumura, T. (1996). Development of motion analysis system for quantitative evaluation of teamwork in soccer games. In Proceedings of 3rd IEEE international conference on image processing, vol.\u00a03, pp. 815\u2013818.","DOI":"10.1109\/ICIP.1996.560865"},{"key":"5725_CR39","unstructured":"Turlach, B.\u00a0A. (1993). Bandwidth selection in kernel density estimation: A review. In CORE and institut de statistique."},{"key":"5725_CR40","first-page":"1","volume":"11","author":"F Ueda","year":"2014","unstructured":"Ueda, F., Masaaki, H., & Hiroyuki, H. (2014). The causal relationship between dominant region and offense-defense performance\u2014Focusing on the time of ball acquisition. Football Science, 11, 1\u201317.","journal-title":"Football Science"},{"key":"5725_CR41","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1515\/crll.1908.133.97","volume":"133","author":"G Voronoi","year":"1908","unstructured":"Voronoi, G. (1908). Nouvelles applications des param\u00e8tres continus \u00e0 la th\u00e9orie des formes quadratiques. premier m\u00e9moire. Sur quelques propri\u00e9t\u00e9s des formes quadratiques positives parfaites. Journal f\u00fcr die reine und angewandte Mathematik, 133, 97\u2013178.","journal-title":"Journal f\u00fcr die reine und angewandte Mathematik"},{"issue":"Supplement C","key":"5725_CR42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.apgeog.2016.09.001","volume":"76","author":"P Zhang","year":"2016","unstructured":"Zhang, P., Beernaerts, J., Zhang, L., & de Weghe, N. V. (2016). Visual exploration of match performance based on football movement data using the continuous triangular model. Applied Geography, 76(Supplement C), 1\u201313.","journal-title":"Applied Geography"},{"key":"5725_CR43","unstructured":"Zhao, Y., Yin, F., Gunnarsson, F., Hultkratz, F., & Fagerlind, J. (2016). Gaussian processes for flow modeling and prediction of positioned trajectories evaluated with sports data. In 2016 19th international conference on information fusion (FUSION), pp. 1461\u20131468."},{"key":"5725_CR44","first-page":"1543","volume":"29","author":"S Zheng","year":"2016","unstructured":"Zheng, S., Yue, Y., & Hobbs, J. (2016). Generating long-term trajectories using deep hierarchical networks. In Advances in Neural Information Processing Systems, 29, 1543\u20131551.","journal-title":"In Advances in Neural Information Processing Systems"},{"issue":"3","key":"5725_CR45","doi-asserted-by":"publisher","first-page":"29:1","DOI":"10.1145\/2743025","volume":"6","author":"Y Zheng","year":"2015","unstructured":"Zheng, Y. (2015). Trajectory data mining: An overview. ACM Transactions on Intelligent Systems and Technology, 6(3), 29:1\u201329:41.","journal-title":"ACM Transactions on Intelligent Systems and Technology"}],"container-title":["Machine Learning"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10994-018-5725-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-018-5725-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-018-5725-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,20]],"date-time":"2019-10-20T01:18:05Z","timestamp":1571534285000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10994-018-5725-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,6,29]]},"references-count":45,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2019,1]]}},"alternative-id":["5725"],"URL":"https:\/\/doi.org\/10.1007\/s10994-018-5725-1","relation":{},"ISSN":["0885-6125","1573-0565"],"issn-type":[{"value":"0885-6125","type":"print"},{"value":"1573-0565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,6,29]]},"assertion":[{"value":"21 June 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 June 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 June 2018","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}