1 option
Machine Learning and Data Mining for Sports Analytics : 7th International Workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings / edited by Ulf Brefeld, Jesse Davis, Jan Van Haaren, Albrecht Zimmermann.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Communications in computer and information science 1865-0937 ; 1324
- Communications in Computer and Information Science, 1865-0937 ; 1324
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Computer engineering.
- Computer networks.
- Education-Data processing.
- Social sciences-Data processing.
- Artificial Intelligence.
- Computer Engineering and Networks.
- Computers and Education.
- Computer Application in Social and Behavioral Sciences.
- Computer Communication Networks.
- Local Subjects:
- Artificial Intelligence.
- Computer Engineering and Networks.
- Computers and Education.
- Computer Application in Social and Behavioral Sciences.
- Computer Communication Networks.
- Physical Description:
- 1 online resource (X, 141 pages) : 6 illustrations
- Edition:
- 1st ed. 2020.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2020.
- System Details:
- text file PDF
- Summary:
- This 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.
- Contents:
- Routine 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.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-64912-8
- 9783030649128
- Access Restriction:
- Restricted for use by site license.
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.