LEADER 02926oam 2200505 450 001 996465449503316 005 20210530074618.0 010 $a3-030-64912-1 024 7 $a10.1007/978-3-030-64912-8 035 $a(CKB)4100000011645248 035 $a(DE-He213)978-3-030-64912-8 035 $a(MiAaPQ)EBC6423162 035 $a(PPN)252515544 035 $a(EXLCZ)994100000011645248 100 $a20210530d2020 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aMachine learning and data mining for sports analytics $e7th International Workshop, MLSA 2020, co-located with ECML/PKDD 2020, Ghent, Belgium, September 14-18, 2020, proceedings /$fUlf Brefeld [and three others editors] 205 $a1st ed. 2020. 210 1$aCham, Switzerland :$cSpringer,$d[2020] 210 4$d℗2020 215 $a1 online resource (X, 141 p. 6 illus.) 225 1 $aCommunications in Computer and Information Science ;$v1324 311 $a3-030-64911-3 327 $aRoutine Inspection: A playbook for corner kicks -- How data availability aects the ability to learngood xG models -- Low-cost optical tracking of soccer players -- An Autoencoder Based Approach to SimulateSports Games -- Physical performance optimization in football -- Predicting Player Trajectoriesin Shot Situations in Soccer -- Stats Aren't Everything: Learning Strengths andWeaknesses of Cricket Players -- Prediction of tiers in the rankingof ice hockey players -- A Machine Learning Approach for Road CyclingRace Performance Prediction -- Mining Marathon Training Data to GenerateUseful User Proles -- Learning from partially labeled sequences forbehavioral signal annotation. 330 $aThis book constitutes the refereed post-conference proceedings of the 7th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2020, colocated with ECML/PKDD 2020, in Ghent, Belgium, in September 2020. Due to the COVID-19 pandemic the conference was held online. The 11 papers presented were carefully reviewed and selected from 22 submissions. The papers present a variety of topics within the area of sports analytics, including tactical analysis, outcome predictions, data acquisition, performance optimization, and player evaluation. 410 0$aCommunications in computer and information science ;$v1324. 606 $aMachine learning$vCongresses 606 $aData mining$vCongresses 606 $aSports$xData processing$vCongresses 615 0$aMachine learning 615 0$aData mining 615 0$aSports$xData processing 676 $a006.31 702 $aBrefeld$b Ulf 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bUtOrBLW 906 $aBOOK 912 $a996465449503316 996 $aMachine learning and data mining for sports analytics$91949689 997 $aUNISA