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Cited by 45

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The Advantage of Playing Home in NBA: Microscopic, Team-Specific and Evolving Features

Ribeiro, Haroldo V., Mukherjee, Satyam, Zeng, Xiao Han T.·2016·PLOS ONE
DOI 10.1371/journal.pone.0152440
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Research works printed but not linked: 76

  1. L Kahn, 2000, The sports business as a labor market laboratory, Journal of Economic Perspectives, 14, 75, 10.1257/jep.14.3.75 · DOI · Paper page
  2. E Ben-Naim, 2013, Randomness in Competitions, Journal of Statistical Physics, 151, 458, 10.1007/s10955-012-0648-x · DOI
  3. E Ben-Naim, 2007, Scaling in tournaments, Europhysics Letters, 77, 30005, 10.1209/0295-5075/77/30005 · DOI
  4. E Ben-Naim, 2007, Efficiency of competitions, Physical Review E, 76, 026106, 10.1103/PhysRevE.76.026106 · DOI
  5. C Sire, 2007, Universal statistical properties of poker tournaments, Journal of Statistical Mechanics: Theory and Experiment, P08013
  6. C Sire, 2009, Understanding baseball team standings and streaks, The European Physical Journal B, 67, 473, 10.1140/epjb/e2008-00405-5 · DOI
  7. A Heuer, 2009, Fitness, chance, and myths: an objective view on soccer results, The European Physical Journal B, 67, 445, 10.1140/epjb/e2009-00024-8 · DOI
  8. HV Ribeiro, 2010, Dynamics of tournaments: the soccer case, The European Physical Journal B, 75, 327, 10.1140/epjb/e2010-00115-5 · DOI
  9. A Gabel, 2012, Random Walk Picture of Basketball Scoring, Journal of Quantitative Analysis in Sports, 8, 10.1515/1559-0410.1416 · DOI
  10. HV Ribeiro, 2012, Anomalous diffusion and long-range correlations in the score evolution of the game of cricket, Physical Review E, 86, 022102, 10.1103/PhysRevE.86.022102 · DOI
  11. HV Ribeiro, 2013, Move-by-move dynamics of the advantage in chess matches reveals population-level learning of the game, PLoS ONE, 8, e54165, 10.1371/journal.pone.0054165 · DOI
  12. A Clauset, 2015, Safe leads and lead changes in competitive team sports, Physical Review E, 91, 06281, 10.1103/PhysRevE.91.062815 · DOI
  13. Ben-Naim E, Vazquez F, Redner S (2005) What is the most competitive sport?. arXiv:physics/0512143v1 · arXiv
  14. Y de Saá Guerra, 2011, Competitiveness analysis in the NBA regular seasons, Education Physical Training Sport, 80, 17
  15. Y de Saá Guerra, 2012, A model for competitiveness level analysis in sports competitions: Application to basketball, Physica A, 391, 2997, 10.1016/j.physa.2012.01.014 · DOI
  16. Y de Saá Guerra, 2013, Basketball scoring in NBA games: an example of complexity, Journal of Systems Science and Complexity, 26, 94, 10.1007/s11424-013-2282-3 · DOI
  17. F Erčulj, 2015, Basketball Shot Types and Shot Success in Different Levels of Competitive Basketball, PLoS ONE, 10, e0128885, 10.1371/journal.pone.0128885 · DOI
  18. J Duch, 2010, Quantifying the performance of individual players in a team activity, PLoS ONE, 5, e10937, 10.1371/journal.pone.0010937 · DOI · Paper page
  19. F Radicchi, 2011, Who Is the Best Player Ever? A Complex Network Analysis of the History of Professional Tennis, PLoS ONE, 6, e17249, 10.1371/journal.pone.0017249 · DOI
  20. JH Fewell, 2012, Basketball Teams as Strategic Networks, PLoS ONE, 7, e47445, 10.1371/journal.pone.0047445 · DOI
  21. S Mukherjee, 2013, Complex Network Analysis in Cricket: Community structure, player’s role and performance index, Advances in Complex Systems, 16, 3, 10.1142/S0219525913500318 · DOI
  22. S Mukherjee, 2013, Quantifying individual performance in Cricket—A network analysis of Batsmen and Bowlers, Physica A, 393, 624, 10.1016/j.physa.2013.09.027 · DOI
  23. J Sampaio, 2015, Exploring Game Performance in the National Basketball Association Using Player Tracking Data, PLoS ONE, 10, e0132894, 10.1371/journal.pone.0132894 · DOI
  24. F Radicchi, 2012, Universality, Limits and Predictability of Gold-Medal Performances at the Olympic Games, PLoS ONE, 7, e40335, 10.1371/journal.pone.0040335 · DOI
  25. S Saavedra, 2012, Is coaching experience associated with effective use of timeouts in basketball?, Scientific Reports, 2, 676, 10.1038/srep00676 · DOI
  26. R Willer, 2012, Reciprocity on the Hardwood: Passing Patterns among Professional Basketball Players, PLoS ONE, 7, e49807, 10.1371/journal.pone.0049807 · DOI
  27. EL Uhlmann, 2014, Selfish Play Increases during High-Stakes NBA Games and Is Rewarded with More Lucrative Contracts, PLoS ONE, 9, e95745, 10.1371/journal.pone.0095745 · DOI
  28. M Perc, 2014, The Matthew effect in empirical data, Journal of The Royal Society Interface, 11, 20140378, 10.1098/rsif.2014.0378 · DOI
  29. G Yaari, 2011, The Hot (Invisible?) Hand: Can Time Sequence Patterns of Success/Failure in Sports Be Modeled as Repeated Random Independent Trials?, PLoS ONE, 6, e24532, 10.1371/journal.pone.0024532 · DOI
  30. JR Bock, 2012, Hitting Is Contagious in Baseball: Evidence from Long Hitting Streaks, PLoS ONE, 7, e51367, 10.1371/journal.pone.0051367 · DOI
  31. G Yaari, 2012, “Hot Hand” on Strike: Bowling Data Indicates Correlation to Recent Past Results, Not Causality, PLoS ONE, 7, e30112, 10.1371/journal.pone.0030112 · DOI
  32. P Csapo, 2014, “Hand down, Man down.” Analysis of Defensive Adjustments in Response to the Hot Hand in Basketball Using Novel Defense Metrics, PLoS ONE, 9, e114184, 10.1371/journal.pone.0114184 · DOI
  33. B Schwartz, 1977, The Home Advantage, Social Forces, 55, 641, 10.2307/2577461 · DOI · Paper page
  34. KS Courneya, 1992, The home advantage in sport competitions: A literature review, Journal of Sport and Exercise Psychology, 14, 13, 10.1123/jsep.14.1.13 · DOI · Paper page
  35. AM Nevill, 1999, Home Advantage in Sport: An Overview of Studies on the Advantage of Playing at Home, Sports Medicine, 28, 221, 10.2165/00007256-199928040-00001 · DOI · Paper page
  36. A Nevill, 2005, The extent and causes of home advantage: Some recent insights, Journal of Sports Sciences, 23, 335, 10.1080/02640410500074375 · DOI
  37. R Pollard, 1986, Home advantage in soccer: A retrospective analysis, Journal of Sports Sciences, 4, 237, 10.1080/02640418608732122 · DOI · Paper page
  38. AM Nevill, 1996, Factors associated with home advantage in English and Scottish soccer matches, Journal of Sports Sciences, 14, 181, 10.1080/02640419608727700 · DOI
  39. R Pollard, 2006, Worldwide regional variations in home advantage in association football, Journal of Sports Sciences, 24, 231, 10.1080/02640410500141836 · DOI
  40. L Page, 2007, The second leg home advantage: Evidence from European football cup competitions, Journal of Sports Sciences, 25, 1547, 10.1080/02640410701275219 · DOI
  41. J Monks, 2009, The Impact of Seeding, Home Continent, and Hosting on FIFA World Cup Results, Journal of Sports Economics, 10, 391, 10.1177/1527002508328757 · DOI
  42. D Riedl, 2014, Finale furioso: referee-biased injury times and their effects on home advantage in football, Journal of Sports Sciences, 33, 327, 10.1080/02640414.2014.944558 · DOI
  43. K Staufenbiel, 2015, Home advantage in soccer—A matter of expectations, goal setting and tactical decisions of coaches?, Journal of Sports Sciences, 33, 1932, 10.1080/02640414.2015.1018929 · DOI
  44. SR Bray, 2005, Batting last as a home advantage factor in men’s NCAA tournament baseball, Journal of Sports Sciences, 23, 681, 10.1080/02640410400022136 · DOI
  45. W Levernier, 2007, An Analysis of the Home-Field Advantage in Major League Baseball Using Logit Models: Evidence from the 2004 and 2005 Seasons, Journal of Quantitative Analysis in Sports, 3, 1559, 10.2202/1559-0410.1045 · DOI
  46. EJ McGuire, 1992, Aggression as a Potential Mediator of the Home Advantage in Professional Ice Hockey, Journal of Sport & Exercise Psychology, 14, 148, 10.1123/jsep.14.2.148 · DOI
  47. GA Agnew, 1994, Crowd effects and the home advantage, International Journal of Sport Psychology, 25, 53
  48. MA Gómez, 2011, Comparison of the home advantage in nine different professional team sports in Spain, Perceptual and motor skills, 113, 150, 10.2466/05.PMS.113.4.150-156 · DOI
  49. MB Jones, 2007, Home Advantage in the NBA as a Game-Long Process, Journal of Quantitative Analysis in Sports, 3, 1559, 10.2202/1559-0410.1081 · DOI
  50. R Pollard, 2013, Variations in home advantage in the national basketball leagues of Europe, Revista de Psicología del Deporte, 22, 263
  51. S Thomas, 2008, Home advantage in the Six Nations Rugby Union Tournament, Perceptual and Motor Skills, 106, 113, 10.2466/pms.106.1.113-116 · DOI
  52. SR Clarke, 2005, Home advantage in the Australian football league, Journal of Sports Sciences, 23, 375, 10.1080/02640410500074391 · DOI
  53. J Prieto, 2013, Home Advantage in Men’s and Women’s Spanish First and Second Division Water Polo Leagues, Journal of human kinetics, 37, 137, 10.2478/hukin-2013-0034 · DOI
  54. R Marcelino, 2009, Home advantage in high-level volleyball varies according to set number, Journal of Sports Science and Medicine, 8, 352
  55. R Pollard, 2012, Re-assessment of home advantage in Spanish handball: comment on Gutierrez, et al. (2012), Perceptual & Motor Skills, 115, 937, 10.2466/06.05.PMS.115.6.937-943 · DOI
  56. T Oliveira, 2012, Effects of game location, period, and quality of opposition in elite handball performances, Perceptual and Motor Skills, 114, 783, 10.2466/30.06.PMS.114.3.783-794 · DOI
  57. J Smiatek, 2012, A statistical view on team handball results: home advantage, team fitness and prediction of match outcomes, arXiv:1207.0700 · arXiv
  58. B Morley, 2005, An investigation of home advantage and other factors affecting outcomes in English one-day cricket matches, Journal of Sports Sciences, 23, 261, 10.1080/02640410410001730133 · DOI · Paper page
  59. RH Koning, 2011, Home advantage in professional tennis, Journal of Sports Sciences, 29, 19, 10.1080/02640414.2010.516762 · DOI
  60. AM Nevill, 1997, Identifying home advantage in international tennis and golf tournaments, Journal of Sports Sciences, 15, 437, 10.1080/026404197367227 · DOI
  61. NJ Balmer, 2001, Home advantage in the Winter Olympics (1908–1998), Journal of Sports Sciences, 19, 129, 10.1080/026404101300036334 · DOI
  62. NJ Balmer, 2003, Modelling home advantage in the Summer Olympic Games, Journal of Sports Sciences, 21, 469, 10.1080/0264041031000101890 · DOI
  63. MB Jones, 2013, The home advantage in individual sports: An augmented review, Psychology of Sport and Exercise, 14, 397, 10.1016/j.psychsport.2013.01.002 · DOI
  64. JP Jamieson, 2010, The home field advantage in athletics: A meta-analysis, Journal of Applied Social Psychology, 40, 1819, 10.1111/j.1559-1816.2010.00641.x · DOI
  65. AM Nevill, 2002, The influence of crowd noise and experience upon refereeing decisions in football, Psychology of Sport and Exercise, 3, 261, 10.1016/S1469-0292(01)00033-4 · DOI
  66. TD Myers, 2014, Achieving external validity in home advantage research: generalizing crowd noise effects, Frontiers in Psychology, 5, 532, 10.3389/fpsyg.2014.00532 · DOI
  67. A Anders, 2014, Is home-field advantage driven by the fans? Evidence from across the ocean, Applied Economics Letters, 21, 1165, 10.1080/13504851.2014.914139 · DOI
  68. C Goumas, 2014, Home advantage in Australian soccer, Journal of Science and Medicine in Sport, 17, 119, 10.1016/j.jsams.2013.02.014 · DOI
  69. MA Gómez, 2010, An analysis of defensive strategies used by home and away basketball teams, Perceptual and Motor Skills, 110, 159, 10.2466/pms.110.1.159-166 · DOI
  70. R Pollard, 2008, Home advantage in football: A current review of an unsolved puzzle, The Open Sports Sciences Journal, 1, 12, 10.2174/1875399X00801010012 · DOI
  71. R Pollard, 2002, Evidence of a reduced home advantage when a team moves to a new stadium, Journal of Sports Sciences, 20, 969, 10.1080/026404102321011724 · DOI
  72. R Johnston, 2008, On referee bias, crowd size, and home advantage in the English soccer Premiership, Journal of Sports Sciences, 26, 563, 10.1080/02640410701736780 · DOI
  73. MA Gómez, 2011, Reduced home advantage for basketball teams from capital cities in Europe, European Journal of Sport Science, 11, 143, 10.1080/17461391.2010.499970 · DOI · Paper page
  74. R Pollard, 2005, Long-term trends in home advantage in professional team sports in North America and England (1876–2003), Journal of Sports Sciences, 23, 337, 10.1080/02640410400021559 · DOI · Paper page
  75. R Pollard, 2006, Worldwide regional variations in home advantage in association football, Journal of Sports Sciences, 24, 231, 10.1080/02640410500141836 · DOI
  76. R Pollard, 2014, Comparison of home advantage in men’s and women’s football leagues in Europe, European Journal of Sport Science, 14, S77, 10.1080/17461391.2011.651490 · DOI

Cited by

Metadata

Authors
Ribeiro, H. V., Mukherjee, S., & Zeng, X. H. T.
Venue
PLOS ONE
Publisher
Public Library of Science (PLoS)
Published
2016-03-25
Volume
11
Issue
3
Pages
e0152440
ISSN
1932-6203
DOI
10.1371/journal.pone.0152440
Cited by
45
References
1
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (vor)

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