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Tire changes, fresh air, and yellow flags: Challenges in predictive analytics for professional racing

Publication ,  Journal Article
Tulabandhula, T; Rudin, C
Published in: Big Data
June 1, 2014

Our goal is to design a prediction and decision system for real-time use during a professional car race. In designing a knowledge discovery process for racing, we faced several challenges that were overcome only when domain knowledge of racing was carefully infused within statistical modeling techniques. In this article, we describe how we leveraged expert knowledge of the domain to produce a real-time decision system for tire changes within a race. Our forecasts have the potential to impact how racing teams can optimize strategy by making tire-change decisions to benefit their rank position. Our work significantly expands previous research on sports analytics, as it is the only work on analytical methods for within-race prediction and decision making for professional car racing.

Duke Scholars

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Published In

Big Data

DOI

EISSN

2167-647X

ISSN

2167-6461

Publication Date

June 1, 2014

Volume

2

Issue

2

Start / End Page

97 / 112

Related Subject Headings

  • 4905 Statistics
  • 4609 Information systems
  • 4605 Data management and data science
  • 0104 Statistics
  • 0103 Numerical and Computational Mathematics
 

Citation

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Tulabandhula, T., & Rudin, C. (2014). Tire changes, fresh air, and yellow flags: Challenges in predictive analytics for professional racing. Big Data, 2(2), 97–112. https://doi.org/10.1089/big.2014.0018
Tulabandhula, T., and C. Rudin. “Tire changes, fresh air, and yellow flags: Challenges in predictive analytics for professional racing.” Big Data 2, no. 2 (June 1, 2014): 97–112. https://doi.org/10.1089/big.2014.0018.
Tulabandhula, T., and C. Rudin. “Tire changes, fresh air, and yellow flags: Challenges in predictive analytics for professional racing.” Big Data, vol. 2, no. 2, June 2014, pp. 97–112. Scopus, doi:10.1089/big.2014.0018.
Journal cover image

Published In

Big Data

DOI

EISSN

2167-647X

ISSN

2167-6461

Publication Date

June 1, 2014

Volume

2

Issue

2

Start / End Page

97 / 112

Related Subject Headings

  • 4905 Statistics
  • 4609 Information systems
  • 4605 Data management and data science
  • 0104 Statistics
  • 0103 Numerical and Computational Mathematics