Chapter 2 Literature Review
2.1 Introduce of Association of Tennis Professionals
The Association of Tennis Professionals (ATP) was formed in September 1972, and organized the worldwide tennis tour for male professional players. The name of organization was ATP TOUR in 1990, and in 2001 changed into ATP, and then in 2009, it changed into the current name ATP World Tour. ATP is governing 5 levels of the tournament, which are ATP World Tour Finals, ATP World Tour Masters 1000, ATP World Tour 500 series, ATP World Tour 250 series and ATP Challenger Tour. This structure was once changed in 2009, and replaced Tennis Masters Series tournaments, ATP International Series Gold and ATP International Series with ATP World Tour Masters 1000, ATP World Tour 500 series, ATP World Tour 250 series. ATP also provides two ranking systems, Emirates ATP Rankings1 a 52-weel rolling ranking, and the Emirates ATP Rankings Race to London2, a year to date ranking. There is the other organization, International Tennis Federation, who is governing the 4 Grand Slam games and ITF Men’s Circuit.
In this study, the ATP games are defined the results of 4 Grand Slam games, ATP World Tour Masters 1000, ATP World Tour 500 series, and ATP World Tour 250 series. The data of ATP World Tour contain all 4 levels from 1995 to 2014; while due to data limited Grand Slam data only include Australia Open 2015 and the other 3 Grand Slam 2014 records. A summary of ATP tours and Grand Slam tournaments is listed in table 2.1.1.
1 Emirates ATP Rankings is used for determining qualification for entry and seeding in all tournaments. Within the ATP Rankings period consisting of the past 52 weeks, points are accumulated, except for ATP World Tour Finals, whose points are dropped following the last ATP event of the year. The player with the most points by season's end is the World Number 1 of the year.
2 Which is used for determining qualification for entry and seeding in all tournaments. Within the ATP Rankings period consisting of the past 52 weeks, points are accumulated, except for ATP World Tour Finals, whose points are dropped following the last ATP event of the year. The player with the most points by season's end is the World Number 1 of the year.
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Table 2.2.1 Summary of ATP Tours and Grand Slam Games
Event category Contains Winner's ranking
points Governing body
Grand Slam Australian Open in, French Open in, Wimbledon in and the US Open 2,000 ITF
ATP World Tour Finals Barclays ATP World Tour Finals 1100 to 1500 ATP (2009-present)
ATP World Tour Masters 1000
Indian Wells, Miami, Monte-Carlo, Madrid, Rome, Canada, Cincinnati,
Shanghai and Paris 1000 ATP
ATP World Tour 500 series
Rotterdam Open, Rio Open, Mexican Open, Dubai Tennis Championships, Barcelona Open, Halle Open, Queen's Club
Championships, German Open, Washington Open, China Open, Japan Open, Vienna Open, Swiss Indoors
500 ATP
ATP World Tour 250
series 39 Tournaments 250 ATP
ATP Challenger Tour 178 Tournaments 80 to 125 ATP
ITF Men's Circuit 534 Tournaments 18 to 35 ITF
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2.2 Tennis Matches Related Literature
Studies of professional tennis are mostly focused on the prediction of the outcomes of the match. For instance, del Corral and Prieto-Rodríguez (2010) tested whether the difference in rankings between individual players are good predictors for Grand Slam outcomes. They used probit models and bootstrapping techniques to examine data from 2005 to 2008. The results denoted that the most relevant variable is the ATP or WTA rankings. McHale and Morton (2011) employed a forecasting model based on the Bradley-Terry model without relying on the official ranking, but based on the results of past matches, the length of time after past matches and the surface of contest to predict match winners. Their model revealed a better prediction than that of ranking model. Knottenbelt, Spanias and Madurska (2012) applied a hierarchical Markvo model to estimate of the probability of each player winning a professional singles tennis match. When using their model with a data set of historical match statistics and bookmakers odds, the model yields a 3.8% return on investment over 2173 ATP matches played. Several other predicting models for tennis matches outcomes have been also presented over the years (Boulier and Stekler, 1999; Clarke and Dyte, 2000; Klaassen and Magnus, 2003; Scheibehenne and Broder, 2007; McHale and Morton, 2011)
Moreover, there are also several studies applying Data Envelopment Analysis (DEA) methodology to evaluate the efficiency of professional tennis plays. Ramon, Ruiz and Sirvent (2012) applied the DEA model that use no input specifications and nine performance outputs.
The result denoted similar rankings as the official ATP rankings. Halkos and Tzeremes (2012) also evaluated the performance of professional tennis players by using DEA approach. The evaluation indicated 39 out of 229 male tennis players are efficient under CRS assumption, and a highly competitive environment of professional tennis was revealed. Chitnis and Vaidya (2014) employed DEA model to measure the performance of professional tennis
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players. They concluded that the DEA approach of measuring performance of an individual tennis player is quite different from the conventional method adopted by ATP World Tour Rankings. Chitnis and Vaidya also found that tennis is a game where not only physical but also psychological factors of a player are tested continuously and hence identifying the weaknesses and potential areas for improvement becomes necessary.
In addition, there are other studies of tennis focus on different topics such as measuring the best player in the history, creating a new ranking system or classifying tennis players.
Radicchi (2011) considered all matches played by professional tennis players between 1968 and 2010, and a diffusion algorithm was applied to the tennis contact network in order to rank professional players. As a result, total win and win against top players are the most relevant factors and Jimmy Connors is determined as the best player ever with Ivan Lendl and John McEnroe following behind. Baker and McHale (2014) conducted a research that a dynamic paired comparison model is used to measure who’s the best player of the Open Era of men’s professional tennis since 1968. And the result suggested that Roger Federer is the best player, with Bjorn Borg and Jimmy Connors close behind. There are also studies showed other ranking system differ from the official ATP one, and provide more information about which player is better. (Dahl 2012; Han, Xie, Li, Zhu, and Wang, 2014)
2.3 Talent Identification Background and Related Literature
Talent identification is a big business in every way such as sport, art and even education.
Researches of these fields are attempting to find a way to identify the best talent. Bloomfield, Fricker and Fitch (1995) defined effective elements of talent identification like strength, power, flexibility and speed. Bompa (1999) revealed that in the late 1960s and early 1970s, researchers in many East European countries tried to find talent identifications, which can be underpinned with scientific theory and evidence. Moreover, Lykken (1998) indicated that
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psychological factors such like persistence, and the capacity to concentrate and confidence is also important. Abbott, Button, Pepping and Collins (2005) revealed that many TI models overemphasis on early identification rather than the development of potentially talented performers. The concept of the talent is revised as a complex, dynamical system in which future behaviors emerge from an interaction of key performance determinants such as psychological behaviors, motor abilities, and physical characteristics. Papic, Rohulj and Plestina (2009) present a fuzzy exert system for scouting and evaluation of young sports talent, and the results show high reliability and accuracy of the developed system which makes the possibility of wrong selection of sports and the time losing in training of
inappropriate sports reduced significantly. These studies reveal that not only physical factors are highly related to talent identification but also have to consider psychological factors which are keys to performance of athletes.
2.4 Background and Related Literatures of Sport Psychology
Weinberg (2014) indicated that stress can be either positive and helpful to performance or negative and harmful to performance, and how it works is depend on the control of the stress. A major source of stress is uncertainty, and one of the most effective ways to get control over stress is to develop confidence. Sport psychologists define self-confidence as the belief that one can perform as wanted. To build self-confidence is important to one’s
performance. At the end of 2004, Andy Roddick said about Roger Federer (winner of the most Grand Slam singles titles in men’s tennis), “He’s got an aura about him in the locker room. Mentally, he’s so confident right now. A lot of his success right now is between the ears.” These comments by Roddick are echoed by Federer himself, who has said, “I believe strongly in my capabilities. There’s a lot of confidence as well, with my record over the past few years. I’ve built up this feeling on big points that I can do it over and over again. Things
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are now just coming automatically.”3 Another example from elite tennis player is that Jimmy Connors once said,
“The whole thing is never to get negative about yourself. Sure, it’s possible that the other guy you’re playing is tough and that he may have beaten you the last time you played, and okay, maybe you haven’t been playing all that well yourself.
But the minute you start thinking about these things you’re dead. I go out to every match convinced that I’m going to win. That’s all there is to it.”4
Moreover, Bandura (1997) revealed that level of self-confidence can be raised by the performance accomplishment if the experiences are successful.
Additionally, mental toughness, other psychological factor, is considered related to performance. Dewhurst, Anderson, Cotter, Crust and Clough (2012) found out mental toughness is related to outcome performance measures in sport and other competitive situations. And mentally tough individuals have an enhanced ability to prevent unwanted information from interfering with current goals. Newland, Newton, Finch, Harbke, and Podlog (2013) revealed that basketball performance can be partially predicted by mental toughness. Similarly, Gonzalez-Diaz, Gossner and Rogers (2012) indicated that career
success is significantly related individual critical ability which is how a player response to the importance of the situation. And it also shows that some aspects of the critical ability are related to psychological skills that are difficult to learn, but still can be improved by training, or simply through experience.
In consequence, these studies suggested that mental toughness and self-confidence have positive affect to the performance. Both psychological factors can be improved by several way, and one of them is the success experience form the past.
3 Weinberg, R. S., & Gould, D. 2014. Foundations of Sport and Exercise Psychology, 6E. Human Kinetics.
4 Weinberg, R. S., & Gould, D. 2014. Foundations of Sport and Exercise Psychology, 6E. Human Kinetics.