Big Data, Efficient Markets, and the End of Daily Fantasy Sports As We Know It?
Autor: | Ryan Elmore, Andrew Urbaczewski |
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Rok vydání: | 2018 |
Předmět: |
Big Data
Marketing Information Systems and Management business.industry Process (engineering) 05 social sciences Big data 050801 communication & media studies Advertising Sports analytics Fantasy Computer Science Applications Through-the-lens metering Efficient-market hypothesis Power (social and political) 0508 media and communications Phenomenon 0502 economics and business Humans Business 050207 economics Sports Information Systems |
Zdroj: | Big Data. 6:239-247 |
ISSN: | 2167-647X 2167-6461 |
DOI: | 10.1089/big.2018.0057 |
Popis: | Fantasy sports are a popular way for individuals to add another layer of enjoyment to their interest in sports. While fantasy sports have been around for many years, access to big data sets and computer power to process them is a relatively new phenomenon, as well as the ability to compete in daily competitions and not just season-long campaigns. We posit that access to new and yet unforeseen data, models, and computing power to manage it, when viewed through the lens of efficient market hypothesis, will cause the daily fantasy sports market to change dramatically. We compare with several other markets to show the effects, when similar technologies become available. |
Databáze: | OpenAIRE |
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