پیش بینی نتایج در مسابقات تنیس با استفاده از بازارهای شرط بندی مسابقات
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|13350||2010||12 صفحه PDF||سفارش دهید|
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|شرح||تعرفه ترجمه||زمان تحویل||جمع هزینه|
|ترجمه تخصصی - سرعت عادی||هر کلمه 90 تومان||11 روز بعد از پرداخت||642,240 تومان|
|ترجمه تخصصی - سرعت فوری||هر کلمه 180 تومان||6 روز بعد از پرداخت||1,284,480 تومان|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Forecasting, Volume 26, Issue 3, July–September 2010, Pages 564–575
Klaassen and Magnus (2003) provide a model of the probability of a given player winning a tennis match, with the prediction updated on a point-by-point basis. This paper provides a point-by-point comparison of that model with the probability of a given player winning the match, as implied by betting odds. The predictions implied by the betting odds match the model predictions closely, with an extremely high correlation being found between the model and the betting market. The results for both men’s and women’s matches also suggest that there is a high level of efficiency in the betting market, demonstrating that betting markets are a good predictor of the outcomes of tennis matches. The significance of service breaks and service being held is anticipated up to four points prior to the end of the game. However, the tendency of players to lose more points than would be expected after conceding a break of service is not captured instantaneously in betting odds. In contrast, there is no evidence of a biased reaction to a player winning a game on service.
Traditional studies of the forecasts obtained from sports betting markets have been limited to examining bets placed before events begin. Such studies do not allow any updating of the predictions of outcomes during events. With the exception of Borghesi (2007), Easton and Uylangco (2007) and Gil and Levitt (2007), there has been little examination of within-match sports betting markets, that is, betting markets where betting continues during the event. The research literature has therefore failed to keep pace with betting markets where within-match betting has become increasingly important. The absence of studies of within-match betting markets is unfortunate, as such an analysis is more in line with financial markets, where information becomes available throughout each day. In addition, highly liquid within-match betting markets avoid the complexities of financial markets, such as the diversity of information available to market participants, while simultaneously avoiding the artificiality of experimental studies, as documented by Levitt and List, 2007a and Levitt and List, 2007b. This paper extends the analysis of within-match betting markets by comparing the ability of betting markets to predict outcomes in tennis matches with predictions made using the model developed by Klaassen and Magnus (2003). The study uses data collected from 49 matches played during the 2007 Australian Open Tennis Championship. Betting data were collected before and after each point on a continuous basis, with the final data set comprising data for 7404 points. Each of these points provides new information as to the outcomes of matches. Such an analysis provides a far more comprehensive examination of market reactions to within-match information arrival than previous studies. By way of comparison, Gil and Levitt (2007) use the thinly-traded Intrade betting market (www.intrade.com) to examine reactions to each of the 122 goals scored in 50 soccer matches in the 2002 World Cup. Borghesi (2007) examines within-match betting for NFL football games and Easton and Uylangco (2007) examine within-match betting for cricket matches, but these studies are incomplete, as they are unable to compare the information arrival with a detailed model of match outcomes, as is provided by the Klaassen and Magnus (2003) tennis model. The paper is organised as follows. Section 2 provides a discussion of the Klaassen and Magnus model and the data collection. The results are presented in Section 3, and Section 4 provides a summary.