Publications

Baseball

Bailey, S.R., Loeppky, J., & Swartz, T.B. (2020). The prediction of batting averages in Major League Baseball. Stats, 9, 84-93.

Swartz, P., Grosskopf, M., Bingham, D.R., & Swartz, T.B. (2017). The quality of pitches in major league baseball. The American Statistician, 71(2), 148-154.

Loughin, T. M., & Bargen, J. L. (2008). Assessing pitcher and catcher influences on base stealing in Major League Baseball. Journal of sports sciences, 26(1), 15-20.

Yang, T.Y. & Swartz, T.B. (2004). A two-stage Bayesian model for predicting winners in major league baseball. Journal of Data Science, 2, 61-73.

Swartz, T.B. (2003). Bayesian modeling and computations in final-offer arbitration. Journal of Business and Economic Statistics, 21(1), 74-79

Basketball

van Bommel, M., Bornn, L., Chow-White, P., & Gao, C. (2021). Home sweet home: Quantifying home court advantages for NCAA basketball statistics. Journal of Sports Analytics, 7(1), 25-36.

Chu, D., & Swartz, T.B. (2020). Foul accumulation in the NBA. Journal of Quantitative Analysis in Sports, 16(4), 301-309.

Beaudoin, D., & Swartz, T. B. (2018). A computationally intensive ranking system for paired comparison data. Operations Research Perspectives, 5, 105-112.

Liu, Y., Schulte, O., & Li, C. (2018). Model trees for identifying exceptional players in the NHL and NBA drafts. In International workshop on machine learning and data mining for sports analytics (pp. 93-105). Springer, Cham.

Wu, S., & Swartz, T. B. (2017). Using AI to correct play-by-play substitution errors. In Proceedings of the MIT Sloan Sports Analytics Conference, Boston, MA, USA (pp. 3-4).

Franks, A., Miller, A., Bornn, L., & Goldsberry, K. (2015) Characterizing the Spatial Structure of Defensive Skill in Professional Basketball. The Annals of Applied Statistics, 9(1), 94-121.

Miller, A.,Bornn, L., Adams, R., & Goldsberry, K. (2014) Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball. International Conference on Machine Learning (ICML).

Swartz, T.B., & Arce, A. (2014). New insights involving the home team advantage . International Journal of Sports Science and Coaching, 9(4), 681-692.

Swartz, T. B., Tennakoon, A., Nathoo, F., Tsao, M., & Sarohia, P. (2011). Ups and downs: team performance in best-of-seven playoff series. Journal of Quantitative Analysis in Sports, 7(4).

Cricket

Epasinghe Dona, N., Nguyen, R., Gill, P.S., & Swartz, T.B. (2022). Expected economy rate. Studies of Applied Economics, 40(1), 1-14.

Thomson, J., Perera, H., & Swartz, T.B. (2021). Contextual batting and bowling in limited overs cricket. South African Statistical Journal, 55, 73-86.

Perera, H., Davis, J., & Swartz, T. B. (2018). Assessing the impact of fielding in Twenty20 cricket. Journal of the Operational Research Society, 69(8), 1335-1343.

Swartz, T.B. (2017). Research directions in cricket. Handbook of Statistical Methods and Analyses in Sports. Chapman & Hall/CRC Handbooks of Modern Statistical Methods, 445-460.

Perera, H., Davis, J., & Swartz, T.B. (2016). Optimal lineups in Twenty20 cricket. Journal of Statistical Computation and Simulation, 86(14), 2888-2900.

Perera, H., & Swartz, T.B. (2016). Muralitharan and Sangakkara: Forging identity and pride in a small island nation. More than Cricket and Football: International Sport and the Challenge of Celebrity, Editors J.N. Rosen and M.M. Smith, University Press of Mississippi, 186-203.

Silva, R., Perera, H., Davis, J., & Swartz, T.B. (2016). Tactics for Twenty20 cricket. South African Statistical Journal, 50(2), 261-271. 

Davis, J., Perera, H., & Swartz, T.B. (2015) A simulator for Twenty20 cricket. The Australian and New Zealand Journal of Statistics, 57(1), 55-71. 

Davis, J., Perera, H., & Swartz, T.B. (2015). Player evaluation in Twenty20 cricket. Journal of Sports Analytics, 1(1), 19-31. 

Silva, R., Manage, B.W., & Swartz, T.B. (2015). A study of the powerplay in one-day cricket . European Journal of Operational Research, 244(3), 931-938.

Perera, H., Gill, P.S., & Swartz, T.B. (2014). Declaration guidelines in test cricket . Journal of Quantitative Analysis in Sports, 10(1), 15-26.

Perera, H., & Swartz, T.B. (2013). Resource estimation in Twenty20 cricket. IMA Journal of Management Mathematics, 24(3), 337-347.

Valero, J., & Swartz, T.B. (2012). An investigation of synergy between batsmen in opening partnerships. Sri Lankan Journal of Applied Statistics, 13, 87-98.

Bhattacharya, R., Gill, P.S. & Swartz, T.B. (2011). Duckworth-Lewis and Twenty20 cricket. Journal of the Operational Research Society, 62(11), 1951-1957.

Swartz, T.B. (2011). Drafts versus auctions in the Indian Premier League. South African Statistical Journal, 45(2), 249-272.

Swartz, T. B., Gill, P. S., & Muthukumarana, S. (2009). Modelling and simulation for one‐day cricket. Canadian Journal of Statistics, 37(2), 143-160.

Swartz, T. B., Gill, P. S., Beaudoin, D., & De Silva, B. M. (2006). Optimal batting orders in one-day cricket. Computers & operations research, 33(7), 1939-1950.

Beaudoin, D. & Swartz, T.B. (2003). The best batsmen and bowlers in one-day cricket. South African Statistical Journal, 37(2), 203-222

Cycling

Yogev, A., Arnold, J., Clarke, D. C., Guenette, J. A., Sporer, B. C., & Koehle, M. (2023). The Effect of Severe Intensity Bouts on Muscle Oxygen Saturation Responses in Trained Cyclists. Frontiers in Sports and Active Living.

Yogev, A., Arnold, J., Clarke, D.C., Guenette, J. A., Sporer, B. C., & Koehle, M. S. (2022). Comparing the Respiratory Compensation Point With Muscle Oxygen Saturation in Locomotor and Non-locomotor Muscles Using Wearable NIRS Spectroscopy During Whole-Body Exercise. Frontiers in Physiology, 483.

Weigend, F. C., Clarke, D. C., Obst, O., & Siegler, J. (2022). A hydraulic model outperforms work-balance models for predicting recovery kinetics from intermittent exercise. Annals of Operations Research, 1-25.

Skiba, P. F., & Clarke, D. C. (2021). The W' balance model: Mathematical and methodological considerations. International Journal of Sports Physiology and Performance. 16(11): 1561-1572.

Skiba, P. F., & Clarke, D.C., Vanhatalo, A., Jones, A. M. (2014) Validation of a novel intermittent W′ model for cycling using field data. International Journal of Sports Physiology and Performance. 9(6): 900-4.

Football

Wu, L. Y., & Swartz, T. B. (2023). The calculation of player speed from tracking data. International Journal of Sports Science & Coaching, 18(2), 516–522.

Mirzaei, A., Schulte, M., Bahrami, M., & Mousavi, M. (2022). Sports Match Outcome Prediction with Spatio-Temporal Graph Representation Learning. Cascadia Symposium on Statistics in Sports, Vancouver, Canada.

Reyers, M., & Swartz, T. B. (2021). Quarterback evaluation in the national football league using tracking data. AStA Advances in Statistical Analysis, 1-16.

Nguyen, R., Day, J., Warton, D., & Lane, O. (2020). Fitzroy - an R package to encourage reproducible sports analysis. The R Journal, 12, 155–162. https://doi.org/10.32614/rj-2021-005.

Chu, D., Reyers, M., Thomson, J., & Wu, L.Y. (2019). Route identification in the National Football League. Journal of Quantitative Analysis in Sports, 16, 121 - 132.

Golf

Wu, Y., Chow-White, P., & Swartz, T. B. (2019). Net best-ball team composition in golf. Journal of Sports Analytics, 5(3), 169-179.

Yousefi, K., & Swartz, T.B. (2013). Advanced putting metrics in golf. Journal of Quantitative Analysis in Sports, 9(3), 239-248.

Swartz, T. B. (2011). An Investigation of Equitable Stroke Control.

Swartz, T. B. (2009). A new handicapping system for golf. Journal of Quantitative Analysis in Sports, 5(2).

Hockey

Kumagai, B., Moreau, R., Kroetch, K. and Swartz, T.B. (2024). Dynamic prediction of the National Hockey League draft with rankordered logit models. International Journal of Forecasting         

Davis, M.J., Swartz, T.B., Schulte, O., Gamboa Higuera, J.C. and Javan, M. (2023). Match predictions in the National Hockey League using box scores. In Statistics Meets Sports: What We Can Learn from Sports Data, Editors Y. Dominicy and C. Ley. Cambridge Scholars Publishing: Cambridge UK, 27-42.           

Liu, G., Luo, Y., Schulte, O., & Poupart, P. (2022). Uncertainty-Aware Reinforcement Learning for Risk-Sensitive Player Evaluation in Sports Game. Advances in Neural Information Processing Systems, 35, 20218-20231.

Schulte, O. (2022). Valuing Actions and Ranking Hockey Players With Machine Learning. In Linköping Hockey Analytics Conference (pp. 2-9).

Liu, G., Schulte, O., Poupart, P., Rudd, M., & Javan, M. (2020). Learning agent representations for ice hockey. Advances in Neural Information Processing Systems, 33, 18704-18715.

Luo, Y. Schulte, O (2020). Inverse reinforcement learning for team sports: Valuing actions and players (Doctoral dissertation, Applied Sciences: School of Computing Science). 

Sun, X., Davis, J., Schulte, O., & Liu, G. (2020). Cracking the Black Box: Distilling Deep Sports Analytics. https://doi.org/10.1145/3394486.3403367.

Tingling, P. M., Masri, K., & Chu, D. (2019). Catch and release? NHL expansion draft endowment effects. Sport, Business and Management: An International Journal, 9(3), 30-312. 

Liu, G., & Schulte, O. (2018). Deep reinforcement learning in ice hockey for context-aware player evaluation. arXiv preprint arXiv:1805.11088.

Liu, G., Zhu, W., & Schulte, O. (2018). Interpreting deep sports analytics: Valuing actions and players in the NHL. In International Workshop on Machine Learning and Data Mining for Sports Analytics (pp. 69-81). Springer, Cham.

Liu, Y., Schulte, O., & Li, C. (2018). Model trees for identifying exceptional players in the NHL and NBA drafts. In International workshop on machine learning and data mining for sports analytics (pp. 93-105). Springer, Cham.

Silva, R., Davis, J., & Swartz, T.B. (2018). The evaluation of pace of play in hockey. Journal of Sports Analytics, 4(2), 145-151.

Schulte, O., Khademi, M., Gholami, S., Zhao, Z., Javan, M., & Desaulniers, P. (2017). A Markov Game model for valuing actions, locations, and team performance in ice hockey. Data Mining and Knowledge Discovery, 31(6), 1735-1757.

Schulte, O., Zhao, Z., Javan, M., & Desaulniers, P. (2017). Apples-to-apples: Clustering and ranking NHL players using location information and scoring impact. In Proceedings of the MIT Sloan Sports Analytics Conference.

Swartz, T.B. (2017). Hockey analytics. Wiley StatsRef: Statistics Reference Online, 1-10.

Tingling, P. M. (2017). Educated guesswork: Drafting in the national hockey league. Handbook of Statistical Methods and Analyses in Sports (pp. 327-339). Boca Raton, Florida, United States: CRC Press.

Beaudoin, D., Schulte, O., & Swartz, T. B. (2016). Biased penalty calls in the National Hockey League. Statistical Analysis and Data Mining: The ASA Data Science Journal, 9(5), 365-372.

Routley, K. D., & Schulte, O., (2015). A markov game model for valuing player actions in ice hockey (Doctoral dissertation, Applied Sciences:).

Swartz, T.B. & Arce, A. (2014). New insights involving the home team advantage . International Journal of Sports Science and Coaching, 9(4), 681-692.

Swartz, T. B., Tennakoon, A., Nathoo, F., Tsao, M., & Sarohia, P. (2011). Ups and downs: team performance in best-of-seven playoff series. Journal of Quantitative Analysis in Sports, 7(4).

Tingling, P., Masri, K. & Martell, M. (2011). Does Order Matter? An Empirical Analysis of the NHL Draft. Sport, Business and Management: An International Journal 1.2.

Beaudoin, D. & Swartz, T.B. (2010). Strategies for pulling the goalie in hockey. The American Statistician, 64(3), 197-204.

Summers, A. E., Swartz, T. B., & Lockhart, R. A. (2007). Optimal drafting in hockey pools. In Statistical thinking in sports (pp. 275-288). Chapman and Hall/CRC.

Pickleball

Gill, P., & Swartz, T.B. (2019). A characterization of the degree of weak and strong links in doubles sports. Journal of Quantitative Analysis in Sports, 15(2), 155-162.

Rugby

Guan, T., Nguyen, R., Cao, J., & Swartz, T.B. (2022). In-game win probabilities for the National Rugby League. The Annals of Applied Statistics, 16(1), 349-367.

Soccer

Guan, T. and Swartz, T.B. (2024). Acceleration and age in soccer. International Journal of Sports Science and Coaching, https://doi.org/10.1177/17479541241232504 

Epasinghege Dona, N. and Swartz, T.B. (2023). A causal investigation of pace of play in soccer. Statistica Applicata - Italian Journal of Applied Statistics, 35(1), Article 6. 

Guan, T., Cao, J., & Swartz, T. B. (2023). Parking the bus. Journal of Quantitative Analysis in Sports, 19(4), 263–272. https://doi.org/10.1515/jqas-2021-0059. 

Epasinghege Dona, N., & Swartz, T. B. (2023). Causal analysis of tactics in soccer: The case of throw-ins. IMA Journal of Management Mathematics, 1–16. https://doi.org/10.1093/imaman/dpad022. 

Wu, L. Y., & Swartz, T. B. (2023). The calculation of player speed from tracking data. International Journal of Sports Science & Coaching, 18(2), 516–522.

Liu, G., Luo, Y., & Schulte, O., & Poupart, P. (2022). Uncertainty-Aware Reinforcement Learning for Risk-Sensitive Player Evaluation in Sports Game. Advances in Neural Information Processing Systems, 35, 20218-20231.

Wu, L.Y., & Swartz, T.B. (2022). Evaluation of off-the-ball actions in soccer. To appear in Statistical Applicata - Italian Journal of Applied Statistics.

Guan, T., Cao, J., & Swartz, T.B. (2021). Should you park the bus?.

Wu, L. Y., Danielson, A. J., Hu, X. J., & Swartz, T. B. (2021). A contextual analysis of crossing the ball in soccer. Journal of Quantitative Analysis in Sports, 17(1), 57-66.

Liu, G., Luo, Y., Schulte, O., & Kharrat, T. (2020). Deep Soccer Analytics: Learning an action-value function for evaluating soccer players. Data Mining and Knowledge Discovery, 34(5), 1531–1559. https://doi.org/10.1007/s10618-020-00705-9.

Sun, X., Davis, J., Schulte, O., & Liu, G. (2020). Cracking the Black Box: Distilling Deep Sports Analytics. https://doi.org/10.1145/3394486.3403367.

Silva, R., & Swartz, T.B. (2016). Analysis of substitution times in soccer. Journal of Quantitative Analysis in Sports, 12(3), 113-122.

Swartz, T.B., Arce, A., & Parameswaran, M. (2013). Assessing value of the draft positions in Major League Soccer's Superdraft. The Sport Journal, 16, Article 9.

Swimming

Eisenhardt, D., Kits, A., Madeleine, P., Samani. A., Clarke, D. C., & Kristiansen, M. (2023). Augmented-reality swim goggles accurately and reliably measure swim performance metrics in recreational swimmers. Frontiers in Sports and Active Living. 5.

Tennis

Epasinghege Dona, N., Gill, P.S. and Swartz, T.B. (2024). What does rally length tell us about player characteristics in tennis? Journal of the Royal Statistical Society, Series A 

Tea, P., & Swartz, T. B. (2022). The analysis of serve decisions in tennis using Bayesian hierarchical models. Annals of Operations Research, 1-16.

Others

Peng, K., Brodie, R.T., Clarke, D.C. and Swartz, T.B. (2024). Bayesian inference for the impulse-response model of athletic training and performance. International Journal of Performance Analysis in Sport, 24(1), 74-89. 

Charlton, B. T., Forsyth, S., & Clarke, D. C. (2022). Low Energy Availability and Relative Energy Deficiency in Sport: What Coaches Should Know. International Journal of Sports Science & Coaching, 17(2), 445-460.

Peng, K., Clarke, D.C. & Swartz, T.B. (2022). Reyers, M. & Swartz, T.B. (2021). Bayesian approaches for critical velocity modelling of data from intermittent efforts. International Journal of Sports Science and Coaching, 17(4), 868-879.

Swartz, T.B. (2020). Where should I publish my sports paper? The American Statistician, 74, 103-108.

Chu, D., Wu, Y., & Swartz, T. B. (2018). Modified kelly criteria. Journal of Quantitative Analysis in Sports, 14(1), 1-11.

Skiba, P. F., Jackman, S., Clarke, D.C., Vanhatalo, A., Jones, A. M. (2014) Effect of work and recovery durations on W' reconstitution during intermittent exercise. Medicine and Science in Sports and Exercise. 46(7):1433-40.

Clarke, D. C., Skiba, P. F. (2013) Rationale and resources for teaching mathematical modeling of athletic training and performance. Advances in Physiology Education. 37(2): 134-152.

Swartz, T. B. (2007). Improved draws for highland dance. Journal of Quantitative Analysis in Sports, 3(1).

Insley, R., Mok, L. & Swartz, T.B. (2004). Issues related to sports gambling. The Australian and New Zealand Journal of Statistics, 46, 219-232.