Sequential movement pattern-mining (SMP) in field-based team-sport: A framework for quantifying spatiotemporal data and improve training specificity? Article Swipe
Ryan White
,
Anna Palczewska
,
Dan Weaving
,
Neil Collins
,
Ben Jones
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1080/02640414.2021.1982484
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1080/02640414.2021.1982484
Athlete external load is typically quantified as volumes or discretised threshold values using distance, speed and time. A framework accounting for the movement sequences of athletes has previously been proposed using radio frequency data. This study developed a framework to identify sequential movement sequences using GPS-derived spatiotemporal data in team-sports and establish its stability. Thirteen rugby league players during one match were analysed to demonstrate the application of the framework. The framework (Sequential Movement Pattern-mining [SMP]) applies techniques to analyse i) geospatial data (i.e., decimal degree latitude and longitude), ii) determine players turning angles, iii) improve movement descriptor assignment, thus improving movement unit formation and iv) improve the classification and identification of players' frequent SMP. The SMP framework allows for sub-sequences of movement units to be condensed, removing repeated elements, which offers a novel technique for the quantification of similarities or dis-similarities between players and playing positions. The SMP framework provides a robust and stable method that allows, for the first time the analysis of GPS-derived data and identifies the frequent SMP of field-based team-sport athletes. The application of the SMP framework in practice could optimise the outcomes of training of field-based team-sport athletes by improving training specificity.
Related Topics
Concepts
Movement (music)
Computer science
Global Positioning System
Team sport
Field (mathematics)
Athletes
Training (meteorology)
Identification (biology)
Data mining
Artificial intelligence
Mathematics
Geography
Physical therapy
Botany
Pure mathematics
Meteorology
Telecommunications
Philosophy
Aesthetics
Medicine
Biology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1080/02640414.2021.1982484
- https://www.tandfonline.com/doi/pdf/10.1080/02640414.2021.1982484?needAccess=true
- OA Status
- bronze
- Cited By
- 8
- References
- 24
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3203163901
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3203163901Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1080/02640414.2021.1982484Digital Object Identifier
- Title
-
Sequential movement pattern-mining (SMP) in field-based team-sport: A framework for quantifying spatiotemporal data and improve training specificity?Work title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-09-27Full publication date if available
- Authors
-
Ryan White, Anna Palczewska, Dan Weaving, Neil Collins, Ben JonesList of authors in order
- Landing page
-
https://doi.org/10.1080/02640414.2021.1982484Publisher landing page
- PDF URL
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https://www.tandfonline.com/doi/pdf/10.1080/02640414.2021.1982484?needAccess=trueDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
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https://www.tandfonline.com/doi/pdf/10.1080/02640414.2021.1982484?needAccess=trueDirect OA link when available
- Concepts
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Movement (music), Computer science, Global Positioning System, Team sport, Field (mathematics), Athletes, Training (meteorology), Identification (biology), Data mining, Artificial intelligence, Mathematics, Geography, Physical therapy, Botany, Pure mathematics, Meteorology, Telecommunications, Philosophy, Aesthetics, Medicine, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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8Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 5, 2023: 1, 2021: 1Per-year citation counts (last 5 years)
- References (count)
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24Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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