---
_id: '24547'
abstract:
- lang: eng
  text: 'Over the last years, several approaches for the data-driven estimation of
    expected possession value (EPV) in basketball and association football (soccer)
    have been proposed. In this paper, we develop and evaluate PIVOT: the first such
    framework for team handball. Accounting for the fast-paced, dynamic nature and
    relative data scarcity of hand- ball, we propose a parsimonious end-to-end deep
    learning architecture that relies solely on tracking data. This efficient approach
    is capable of predicting the probability that a team will score within the near
    future given the fine-grained spatio-temporal distribution of all players and
    the ball over the last seconds of the game. Our experiments indicate that PIVOT
    is able to produce accurate and calibrated probability estimates, even when trained
    on a relatively small dataset. We also showcase two interactive applications of
    PIVOT for valuing actual and counterfactual player decisions and actions in real-time.'
author:
- first_name: Oliver
  full_name: Müller, Oliver
  id: '72849'
  last_name: Müller
- first_name: Matthew
  full_name: Caron, Matthew
  id: '60721'
  last_name: Caron
- first_name: Michael
  full_name: Döring, Michael
  last_name: Döring
- first_name: Tim
  full_name: Heuwinkel, Tim
  last_name: Heuwinkel
- first_name: Jochen
  full_name: Baumeister, Jochen
  id: '46'
  last_name: Baumeister
  orcid: 0000-0003-2683-5826
citation:
  ama: 'Müller O, Caron M, Döring M, Heuwinkel T, Baumeister J. PIVOT: A Parsimonious
    End-to-End Learning Framework for Valuing Player Actions in Handball using Tracking
    Data. In: <i>8th Workshop on Machine Learning and Data Mining for Sports Analytics
    (ECML PKDD 2021)</i>.'
  apa: 'Müller, O., Caron, M., Döring, M., Heuwinkel, T., &#38; Baumeister, J. (n.d.).
    PIVOT: A Parsimonious End-to-End Learning Framework for Valuing Player Actions
    in Handball using Tracking Data. <i>8th Workshop on Machine Learning and Data
    Mining for Sports Analytics (ECML PKDD 2021)</i>. European Conference on Machine
    Learning and Principles and Practice of Knowledge Discovery (ECML PKDD 2021),
    Online.'
  bibtex: '@inproceedings{Müller_Caron_Döring_Heuwinkel_Baumeister, title={PIVOT:
    A Parsimonious End-to-End Learning Framework for Valuing Player Actions in Handball
    using Tracking Data}, booktitle={8th Workshop on Machine Learning and Data Mining
    for Sports Analytics (ECML PKDD 2021)}, author={Müller, Oliver and Caron, Matthew
    and Döring, Michael and Heuwinkel, Tim and Baumeister, Jochen} }'
  chicago: 'Müller, Oliver, Matthew Caron, Michael Döring, Tim Heuwinkel, and Jochen
    Baumeister. “PIVOT: A Parsimonious End-to-End Learning Framework for Valuing Player
    Actions in Handball Using Tracking Data.” In <i>8th Workshop on Machine Learning
    and Data Mining for Sports Analytics (ECML PKDD 2021)</i>, n.d.'
  ieee: 'O. Müller, M. Caron, M. Döring, T. Heuwinkel, and J. Baumeister, “PIVOT:
    A Parsimonious End-to-End Learning Framework for Valuing Player Actions in Handball
    using Tracking Data,” presented at the European Conference on Machine Learning
    and Principles and Practice of Knowledge Discovery (ECML PKDD 2021), Online.'
  mla: 'Müller, Oliver, et al. “PIVOT: A Parsimonious End-to-End Learning Framework
    for Valuing Player Actions in Handball Using Tracking Data.” <i>8th Workshop on
    Machine Learning and Data Mining for Sports Analytics (ECML PKDD 2021)</i>.'
  short: 'O. Müller, M. Caron, M. Döring, T. Heuwinkel, J. Baumeister, in: 8th Workshop
    on Machine Learning and Data Mining for Sports Analytics (ECML PKDD 2021), n.d.'
conference:
  end_date: 2021-09-17
  location: Online
  name: European Conference on Machine Learning and Principles and Practice of Knowledge
    Discovery (ECML PKDD 2021)
  start_date: 2021-09-13
date_created: 2021-09-16T08:33:04Z
date_updated: 2023-02-28T08:58:24Z
department:
- _id: '196'
- _id: '172'
keyword:
- expected possession value
- handball
- tracking data
- time series classification
- deep learning
language:
- iso: eng
main_file_link:
- url: https://dtai.cs.kuleuven.be/events/MLSA21/papers/MLSA21_paper_muller.pdf
publication: 8th Workshop on Machine Learning and Data Mining for Sports Analytics
  (ECML PKDD 2021)
publication_status: inpress
status: public
title: 'PIVOT: A Parsimonious End-to-End Learning Framework for Valuing Player Actions
  in Handball using Tracking Data'
type: conference
user_id: '60721'
year: '2021'
...