2026-09-19T05:27:30Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1444872022-08-30T03:44:21Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Hosoi, Anette
Hylen, Spencer David
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2022-08-29T15:50:49Z
2022-08-29T15:50:49Z
2022-05
2022-05-27T16:19:53.063Z
https://hdl.handle.net/1721.1/144487
In professional sports, fan attendance at games is one of the largest drivers of revenue and a significant focus for all sports teams. While sports tickets can benefit from dynamic pricing techniques developed for airlines or hotels, they have constraints related to limited inventory, season tickets, and the attendance-revenue trade-off that make them unique and difficult to price with existing dynamic pricing systems. In this work, we present a novel dynamic pricing strategy for sports tickets, developed with an engineering approach alongside primary market ticket data provided by the San Antonio Spurs. Using dynamic programming and matrix completion for modeling customer demand, we provide optimal price recommendations for all time periods before a game. We use these recommendations, along with information on current prices, to provide a suite of ticket price optimization and analysis tools. These tools are led by our Manual Price Adjustment Guide, which combines our optimal price recommendations with ticketing analyst expertise for a hybrid solution designed to improve ticket pricing and increase team revenue.
M.Eng.
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
Copyright MIT
http://rightsstatements.org/page/InC-EDU/1.0/
Primary Market Dynamic Pricing for Sports Tickets: Theory and Application
Thesis
application/pdf
Master
Master of Engineering in Electrical Engineering and Computer Science
Publication
unknown
unknown
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<Abstract>In professional sports, fan attendance at games is one of the largest drivers of revenue and a significant focus for all sports teams. While sports tickets can benefit from dynamic pricing techniques developed for airlines or hotels, they have constraints related to limited inventory, season tickets, and the attendance-revenue trade-off that make them unique and difficult to price with existing dynamic pricing systems. In this work, we present a novel dynamic pricing strategy for sports tickets, developed with an engineering approach alongside primary market ticket data provided by the San Antonio Spurs. Using dynamic programming and matrix completion for modeling customer demand, we provide optimal price recommendations for all time periods before a game. We use these recommendations, along with information on current prices, to provide a suite of ticket price optimization and analysis tools. These tools are led by our Manual Price Adjustment Guide, which combines our optimal price recommendations with ticketing analyst expertise for a hybrid solution designed to improve ticket pricing and increase team revenue.</Abstract>
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