20,735 research outputs found

    Do Tournaments Have Incentive Effects?

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    Much attention has been devoted to studying models of tournaments or situations in which an individual\u27s payment depends only on his or her output or rank relative to that of other competitors. Academic interest derives from the fact that under certain sets of assumptions, tournaments have desirable normative properties because of the incentive structures they provide. Our paper uses nonexperimental data to test whether tournaments actually elicit effort responses. We focus on professional golf tournaments because information on the incentive structure (prize distribution) and measures of individual output (players\u27 scores) are both available. We find strong support for the proposition that the level and structure of prizes in PGA tournaments influence players\u27 performance

    Universal scaling in sports ranking

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    Ranking is a ubiquitous phenomenon in the human society. By clicking the web pages of Forbes, you may find all kinds of rankings, such as world's most powerful people, world's richest people, top-paid tennis stars, and so on and so forth. Herewith, we study a specific kind, sports ranking systems in which players' scores and prize money are calculated based on their performances in attending various tournaments. A typical example is tennis. It is found that the distributions of both scores and prize money follow universal power laws, with exponents nearly identical for most sports fields. In order to understand the origin of this universal scaling we focus on the tennis ranking systems. By checking the data we find that, for any pair of players, the probability that the higher-ranked player will top the lower-ranked opponent is proportional to the rank difference between the pair. Such a dependence can be well fitted to a sigmoidal function. By using this feature, we propose a simple toy model which can simulate the competition of players in different tournaments. The simulations yield results consistent with the empirical findings. Extensive studies indicate the model is robust with respect to the modifications of the minor parts.Comment: 8 pages, 7 figure

    Historical Relative Performance Index over Interconnectedness of Badminton Athletes

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    The paper proposes the Historical Relative Performance Index in order to quantitatively extract information in the scores hit in the sets of head-to-head game in badminton tournaments. The index is treated as the weights of the directed networks built between competing athletes. The paper also proposes the way to build the fully connected network based on the empirically found network in order to have relative index between athletes that have never nor will be met in series of games. Some further directions as well as implementation to small amount of data is described for advanced analysis

    The Incentive Effects of Tournaments Revisited: Evidence From the European PGA Tour

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    This analysis of data from the 1987 European Men\u27s Professional Golf Association (PGA) Tour strongly supports the hypothesis that the level and structure of prizes in PGA tournaments influence players\u27 performance. Specifically, players\u27 performance appears to vary positively with both the total money prizes awarded in a tournament and the marginal return to effort in the final round of play (a value that varies among players largely depending on how the prize money is allocated among finishers of different ranks). The authors suggest that these results, together with the similar results of their earlier study of the 1984 U.S. Men\u27s PGA Tour, may have implications for the design of compensation systems for certain groups of workers, such as corporate executives, college professors, and salespeople

    The allocation of rewards in athletic contests

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    Similar to most top-tier matches in professional basketball, baseball and soccer, high-level competitions in individualistic sports, such as the tennis tournaments of Wimble-don and Flushing Meadows, the golf tournaments of Augusta and St. Andrews, as well as the marathons of New York and London attract not only thousands of spectators, but also a TV audience of millions of fans. Moreover, these (and other) individualistic sports have recently received increased attention also from economists trying to test a number of hypotheses that can be derived from "tournament theory" or - as a synonym - from "contest theory". The chapter is structured as follows: We first provide a brief description of the development of prize money levels and structures in the three different individual sports men-tioned in the previous paragraph (and, consequently, athletes' incomes over the last years (section 2). We then summarize the basic insights and the core predictions of tour-nament/contest theory (section 3) and review the available literature on the incentive effects of tournament pay systems in athletic contests (section 4). Finally, section 5 concludes and raises some of the questions that have not been answered yet and that should, therefore, be dealt with in future research.

    Single-Elimination Brackets Fail to Approximate Copeland Winner

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    Single-elimination (SE) brackets appear commonly in both sports tournaments and the voting theory literature. In certain tournament models, they have been shown to select the unambiguously-strongest competitor with optimum probability. By contrast, we reevaluate SE brackets through the lens of approximation, where the goal is to select a winner who would beat the most other competitors in a round robin (i.e., maximize the Copeland score), and find them lacking. Our primary result establishes the approximation ratio of a randomly-seeded SE bracket is 2^{- Theta(sqrt{log n})}; this is underwhelming considering a 1/2 ratio is achieved by choosing a winner uniformly at random. We also establish that a generalized version of the SE bracket performs nearly as poorly, with an approximation ratio of 2^{- Omega(sqrt[4]{log n})}, addressing a decade-old open question in the voting tree literature

    On predictability of rare events leveraging social media: a machine learning perspective

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    Information extracted from social media streams has been leveraged to forecast the outcome of a large number of real-world events, from political elections to stock market fluctuations. An increasing amount of studies demonstrates how the analysis of social media conversations provides cheap access to the wisdom of the crowd. However, extents and contexts in which such forecasting power can be effectively leveraged are still unverified at least in a systematic way. It is also unclear how social-media-based predictions compare to those based on alternative information sources. To address these issues, here we develop a machine learning framework that leverages social media streams to automatically identify and predict the outcomes of soccer matches. We focus in particular on matches in which at least one of the possible outcomes is deemed as highly unlikely by professional bookmakers. We argue that sport events offer a systematic approach for testing the predictive power of social media, and allow to compare such power against the rigorous baselines set by external sources. Despite such strict baselines, our framework yields above 8% marginal profit when used to inform simple betting strategies. The system is based on real-time sentiment analysis and exploits data collected immediately before the games, allowing for informed bets. We discuss the rationale behind our approach, describe the learning framework, its prediction performance and the return it provides as compared to a set of betting strategies. To test our framework we use both historical Twitter data from the 2014 FIFA World Cup games, and real-time Twitter data collected by monitoring the conversations about all soccer matches of four major European tournaments (FA Premier League, Serie A, La Liga, and Bundesliga), and the 2014 UEFA Champions League, during the period between Oct. 25th 2014 and Nov. 26th 2014.Comment: 10 pages, 10 tables, 8 figure

    Do Tournaments Have Incentive Effects?

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    Much attention has been devoted to studying models of tournaments or situations in which an individual's payment depends only on his output or rank, relative to other competitors. Such models are of more than academic Interest as they may well describe the compensation structures applicable to many corporate executives and professors, to sales people whose bonuses depend on their relative outputs. and to the more obvious example of professional sports tournaments. Academic interest derives from the fact that under certain sets of assumptions tournaments have desirable normative properties because of the incentive structures they provide. Our paper uses nonexperimental data to test if tournaments actually elicit desired effort responses. We focus on golf tournaments because information on the incentive structure (prize distribution) and measures of individual output (players' scores) are both available. Under suitable assumptions, players' scores can be related to players' effort and implications for both players' overall tournament scores and their scores on the last round of a tournament drawn. In addition, data are available to control for factors other than the incentive structure that should affect output; these factors include player quality, quality of the rest of the field, difficulty of the course, and weather conditions. The data used in our analyses cane from the "1985 Golf Digest Almanac", the "Official 1985 PGA Tour Media Guide", and the "1984 PGA Tour Player Record". We find strong support for the proposition that the level and structure of prizes in PGA tournaments influence players' performance.

    Small World Network of Athletes: Graph Representation of the World Professional Tennis Player

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    The paper proposes an alternative way to observe and extract the multiple matches games of sports, i.e.: tennis tournament in the Athlete’s Historical Relative Performance Index and its representation as graph. The finding of the small world topology is elaborated along with further statistical patterns in the fashion of the weighted and directed network. The explanation of the sport tournament system as a highly optimized system is hypothetically proposed. Finally, some elaborations regarding to further directions of the usability of the proposed methodology is discussed
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