Bidding Strategies for Fantasy-Sports Auctions.

Lecture Notes in Computer Science(2016)

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摘要
Fantasy sports is a fast-growing, multi-billion dollar industry [10] in which competitors assemble virtual teams of athletes from real professional sports leagues and obtain points based on the statistical performance of those athletes in actual games. Users (team managers) can add, drop, and trade players throughout the season, but the pivotal event is the player draft that initiates the competition. One common drafting mechanism is the so-called auction draft: managers bid on athletes in rounds until all positions on each roster have been filled. Managers start with the same initial virtual budget and take turns successively nominating athletes to be auctioned, with the winner of each round making a virtual payment that diminishes his budget for future rounds. Each manager tries to obtain players that maximize the expected performance of his own team. In this paper we initiate the study of bidding strategies for fantasy sports auction drafts, focusing on the design and analysis of simple strategies that achieve good worst-case performance, obtaining a constant fraction of the best value possible, regardless of competing managers’ bids. Our findings may be useful in guiding bidding behavior of fantasy sports participants, and perhaps more importantly may provide the basis for a competitive auto-draft mechanism to be used as a bidding proxy for participants who are absent from their league’s draft.
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