# Scope of the workshop

Sports Analytics has become an increasingly important field in recent years, with the use of advanced analytical techniques and data analysis transforming the way sports teams and organizations operate. From player evaluation and performance prediction to match strategy and tactics, the impact of data-driven decision-making in sports cannot be ignored. Moreover, as the volume of available data grows and analytical methods become more sophisticated, the potential benefits of Sports Analytics continue to expand. In particular, the use of machine learning and data mining techniques has opened up new opportunities for Sports Analytics researchers and practitioners.

The workshop will cover a range of topics related to Sports Analytics, including:

- Match analysis and strategy
- Player recruitment, valuation, and team spending
- Talent identification and development
- Training and performance optimization
- Injury prevention and management
- Performance prediction and evaluation
- Match outcome and league ranking prediction
- Tournament design and scheduling optimization
- Betting odds modeling and analysis

We look forward to receiving high-quality submissions from researchers and practitioners in both the sports and machine learning/data mining communities. The workshop will provide a valuable opportunity to showcase the latest advances in Sports Analytics research, foster collaborations between researchers from different backgrounds, and inspire further research in this exciting and rapidly evolving field.


# Submissions

The workshop welcomes papers covering both predictive and descriptive Machine Learning, Data Mining, and related approaches to Sports Analytics settings. The scope of the workshop includes, but is not limited to, the list of topics mentioned above. We adopt a broad definition of sports and are open to submissions on electronic sports (i.e., e-sports) that relate to any of these topics.

There are two types of papers that can be submitted:

- Long papers: These papers will be 9 pages of content and an unlimited number of references in the Springer LNCS style. Long papers should report on novel, unpublished work that might not be quite mature enough for a conference or journal submission.
- Extended abstracts: These papers will be 2 pages in Springer LNCS style and should summarize recent publications that fit the scope of the workshop.

Papers are to be submitted in pdf format via the CMT system at https://cmt3.research.microsoft.com/ECMLPKDDWorkshopTrack2025/ (choose "Workshop on Machine Learning and Data Mining for Sports Analytics (MLSA)" from the drop-down when creating the submission).

Each submission will be reviewed by at least two members of the Program Committee based on technical quality, relevance, significance, and clarity. Submitting a paper to the workshop means that at least one author should present the paper at the workshop if the paper is accepted.


# Key dates

Paper submission: 14/06/2025
Author notification: 14/07/2025
Workshop: 15/09/2025 or 19/092025


# Contact

Hugo Rios-Neto: hugoriosneto@dcc.ufmg.br
Pieter Robberechts: pieter.robberechts@kuleuven.be
Maaike Van Roy: maaike.vanroy@kuleuven.be
Albrecht Zimmermann: albrecht.zimmermann@unicaen.fr

Workshop site: https://dtai.cs.kuleuven.be/events/MLSA25/