Tim B. Swartz

2.0k citations
99 papers · 1.2k · h-index 17

Impact in

Papers in

    • Sports Analytics and Performance 49
    • Statistical Methods and Bayesian Inference 19
    • Statistical Distribution Estimation and Applications 8
    • Advanced Statistical Methods and Models 8
    • Statistical Methods and Inference 6

Tim B. Swartz

89 papers receiving 1.1k citations

Peers

Tim B. Swartz
Comparison fields: 5 of 138
  • Statistics and Probability 342
  • Orthopedics and Sports Medicine 146
  • Economics and Econometrics 467
  • Statistics, Probability and Uncertainty 112
  • Tourism, Leisure and Hospitality Management 19
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Citations per field
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Citations per year

Countries citing papers authored by Tim B. Swartz

Since Specialization
Citations

This map shows the geographic impact of Tim B. Swartz's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tim B. Swartz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim B. Swartz more than expected).

Fields of papers citing papers by Tim B. Swartz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tim B. Swartz. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tim B. Swartz. The network helps show where Tim B. Swartz may publish in the future.

Co-authors

The 25 scholars most cited alongside Tim B. Swartz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tim B. Swartz Line = papers co-authored together Tim B. Swartz links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 99 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2000178
2 1995147
3 199153
4 200441
5 199840
6 200137
7 200436
8 200730
9 199830
10 200927
11 201525
12 201424
13 200122
14 201621
15 201021
16 201520
17
The best batsmen and bowlers in one-day cricket : : general
200316
18 201616
19
Bayesian Analysis of Binary Data Subject to Misclassification
199616
20 199716

About Tim B. Swartz

Tim B. Swartz is a scholar working on Economics and Econometrics, Statistics and Probability, Artificial Intelligence, Orthopedics and Sports Medicine and Biomedical Engineering, having authored 99 papers that have together received 1.2k indexed citations. Recurring topics across this work include Sports Analytics and Performance (49 papers), Statistical Methods and Bayesian Inference (19 papers), Sports Performance and Training (14 papers), Sports Dynamics and Biomechanics (14 papers), Bayesian Methods and Mixture Models (12 papers), Statistical Distribution Estimation and Applications (8 papers), Advanced Statistical Methods and Models (8 papers) and Statistical Methods and Inference (6 papers). The work is most often cited by research in Statistics and Probability (342 citations), Orthopedics and Sports Medicine (146 citations), Economics and Econometrics (467 citations), Statistics, Probability and Uncertainty (112 citations) and Tourism, Leisure and Hospitality Management (19 citations). Tim B. Swartz has collaborated with scholars based in Canada, United States and Sri Lanka. Frequent co-authors include Michael Evans, Michael L. Evans, Paramjit Gill, Richard Routledge, Jack Davis, David Beaudoin, Saman Muthukumarana, Irwin Guttman, Tae Young Yang and Yoel Haitovsky. Their work appears in journals such as Journal of Quantitative Analysis in Sports, Canadian Journal of Statistics, The American Statistician, International Journal of Sports Science & Coaching and Journal of Statistical Computation and Simulation.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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