Who Is the Best Player Ever? A Complex Network Analysis of the History of Professional Tennis

We considered all matches played by professional tennis players between 1968 and2010, and, on the basis of this data set, constructed a directed and weighted network of contacts. The resulting graph showed complex features, typical of many real networked systems studied in literature. We developed a diffusion algorithm and applied it to the tennis contact network in order to rank professional players. Jimmy Connors was identified as the best player in the history of tennis according to our ranking procedure. We performed a complete analysis by determining the best players on specific playing surfaces as well as the best ones in each of the years covered by the data set. The results of our technique were compared to those of two other well established methods. In general, we observed that our ranking method performed better: it had a higher predictive power and did not require the arbitrary introduction of external criteria for the correct assessment of the quality of players. The present work provides novel evidence of the utility of tools and methods of network theory in real applications.

[1]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

[2]  D J PRICE,et al.  NETWORKS OF SCIENTIFIC PAPERS. , 1965, Science.

[3]  J. Duch,et al.  Quantifying the Performance of Individual Players in a Team Activity , 2010, PloS one.

[4]  Brian Skinner,et al.  The Price of Anarchy in Basketball , 2009, 0908.1801.

[5]  A. Vespignani,et al.  The architecture of complex weighted networks. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[6]  Claudio Castellano,et al.  Universality of citation distributions: Toward an objective measure of scientific impact , 2008, Proceedings of the National Academy of Sciences.

[7]  Santo Fortunato,et al.  Diffusion of scientific credits and the ranking of scientists , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[8]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[9]  Albert-László Barabási,et al.  The origin of bursts and heavy tails in human dynamics , 2005, Nature.

[10]  Woo-Sung Jung,et al.  Quantitative and empirical demonstration of the Matthew effect in a study of career longevity , 2008, Proceedings of the National Academy of Sciences.

[11]  Attila Szolnoki,et al.  Coevolutionary Games - A Mini Review , 2009, Biosyst..

[12]  R. N. Onody,et al.  Complex network study of Brazilian soccer players. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[13]  Carl T. Bergstrom,et al.  Big Macs and Eigenfactor scores: Don't let correlation coefficients fool you , 2009, J. Assoc. Inf. Sci. Technol..

[14]  Sergei Maslov,et al.  Finding scientific gems with Google's PageRank algorithm , 2006, J. Informetrics.

[15]  Adilson E. Motter,et al.  A Poissonian explanation for heavy tails in e-mail communication , 2008, Proceedings of the National Academy of Sciences.

[16]  Jürgen Kurths,et al.  Evidence for a bimodal distribution in human communication , 2010, Proceedings of the National Academy of Sciences.

[17]  G. Szabó,et al.  Evolutionary games on graphs , 2006, cond-mat/0607344.

[18]  Woo-Sung Jung,et al.  On the Distribution of Career Longevity and the Evolution of Home Run Prowess in Professional Baseball , 2008 .

[19]  S. Redner,et al.  Understanding baseball team standings and streaks , 2008 .

[20]  Alessandro Vespignani,et al.  Epidemic spreading in scale-free networks. , 2000, Physical review letters.

[21]  Filippo Radicchi Human Activity in the Web , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[22]  Manjit,et al.  Neurology , 1912, NeuroImage.

[23]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[24]  Andreas Heuer,et al.  Soccer: Is scoring goals a predictable Poissonian process? , 2010, 1002.0797.

[25]  Carl T. Bergstrom,et al.  Assessing citations with the Eigenfactor™ Metrics , 2008, Neurology.

[26]  Jurgen Kurths,et al.  Synchronization in complex networks , 2008, 0805.2976.

[27]  E. Ben-Naim,et al.  Scaling in tournaments , 2007 .

[28]  S. Fortunato,et al.  Statistical physics of social dynamics , 2007, 0710.3256.

[29]  Mason A. Porter,et al.  Mutually-antagonistic interactions in baseball networks , 2009, 0907.5241.

[30]  Mark E. J. Newman,et al.  The Structure and Function of Complex Networks , 2003, SIAM Rev..

[31]  Albert-László Barabási,et al.  Error and attack tolerance of complex networks , 2000, Nature.

[32]  E. Ben-Naim,et al.  What is the most competitive sport , 2005 .

[33]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.