{
  "abstract": "NBA offenses increasingly reflect a “space-and-pace” approach, yet it remains unclear whether recent tempo changes primarily reflect long-run strategic adaptation or the 2018–19 14-second offensive-rebound shot-clock reset. We combined team-season metrics with shot-location data from the NBA Stats API across 21 seasons (2004–05–2024–25; > 420,000 field-goal attempts). Analyses included spatial heatmaps and a Spatial Allocation Index (SAI), segmented regression for league Pace, and multivariate OLS models for Offensive Rating (ORtg). Heatmaps showed a substantial reduction in mid-range attempts and greater concentration at the rim and beyond the arc; SAI increased from 58.98% to 69.99%. Segmented regression identified a marked change around 2018–19, with an immediate increase in Pace and a post-2018 trend that flattened and became slightly negative (pre-2018 slope ≈ 0.44 possessions/season; post-2018 net slope ≈ −0.26). Turnover percentage declined despite higher tempo (p < 0.001). The 2018–19 reset aligned with a step change in tempo, while subsequent seasons show consolidation rather than continued acceleration. Over the longer run, shot allocation became increasingly concentrated at the rim and from three-point range, indicating co-evolution in tempo and shot-location strategy.",
  "abstract_shown": true,
  "affiliations": [
    "School of Physical Education, Shanghai University of Sport, Shanghai, China",
    "Department of Physical Education, Capital Normal University, Beijing, China",
    "College of Teacher Education, Capital Normal University, Beijing, China"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
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        0
      ],
      "name": "Shuming Cui"
    },
    {
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        1
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      "name": "Zhenxing Yang"
    },
    {
      "affs": [
        2
      ],
      "name": "Hemu Du"
    },
    {
      "name": "Rongheng Liu"
    },
    {
      "name": "Shijie Liu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5yr9n4320z3dh.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pone.0358360",
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  "id": "5yr9n4320z3dh",
  "issns": [
    "1932-6203"
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  "landing_url": "https://doi.org/10.1371/journal.pone.0358360",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
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      "2002|Sports Analytics and Performance"
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      "/Research and analysis methods/Mathematical and statistical techniques/Statistical methods/Regression analysis/Linear regression analysis"
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      "/Research and analysis methods/Mathematical and statistical techniques/Statistical methods/Time series analysis"
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      "/Social sciences/Psychology/Behavior/Recreation/Sports"
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      "/Social sciences/Psychology/Cognitive psychology/Decision making"
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      "/Social sciences/Psychology/Collective human behavior/Team behavior"
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  "pdf_url": "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0358360&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-18",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/5yr9n4320z3dh.ris",
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  "subjects": [
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      "origin": "plos:statistical methods",
      "subfield": "statistics"
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  "title": "Shot-location polarization and post-2018 pace stabilization in the NBA: Evidence from 21 seasons of team and shot-coordinate data (2004–2025)",
  "title_text": "Shot-location polarization and post-2018 pace stabilization in the NBA: Evidence from 21 seasons of team and shot-coordinate data (2004–2025)",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:49Z",
  "url": "https://research.draconitic.com/paper/5yr9n4320z3dh",
  "venue": "PLOS One",
  "versions": []
}