The relationship between the countries' performances at the major sport events with their performance at the Olympic Games

The purpose of this study was study of Relationship between countries performance at multi-sport events and world championships with their performance at Olympic Game. The population of all the countries in the Olympic Games medals have been won that their number is equal 1166 (excluding repeat). Based on Morgan table, samples were selected equal 321. Information was collected from multiple sites such as international federations, Olympic Continental Councils and international Olympic committee. Also, for analyzing used descriptive and inferential statistics (Kolmogorov-Smirnov test and Spearman correlation coefficient) by SPSS software and significant level p≤0.05. The results showed that there is positive and significantly relationship between the number of medals of gold, silver, bronze and total medals won by countries at former Olympic Games, world championships, Asian and Pan-American Games with the number of Medals of gold, silver, bronze and total medals won at upcoming Olympic Games, However, there is not significantly relationship between the number of medals of gold, silver, bronze and total medals won at all-African Games with the number of medals of gold, silver, bronze and total medals won at Olympic Games. 

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  • Bernard A, Busse M.. Who wins the Olympic Games? Economic resources and medal totals. Rev Econ Stat, 2004; 86(1): 413- 417.
  • Condon EM, Bruce LG, Wasil EA. Predicting the success of nations at the Summer Olympics using neural networks. Comp Oper Res, 1999; 26: 1243-1265.
  • Corral JD, Rodriguez JP. Are differences in ranks good predictors for Grand Slam?. Int J Forecasting, 2010; 26: 551– 563.
  • Forrest D, Goddard J, Simmons R. Odds-setters as forecasters: The case of English football. Int J Forecasting, 2005; 21: 551– 564.
  • Forrest D, Ismael S, Tena JD. Forecasting national team medal totals at the Summer Olympic Games. Int J Forecasting, 2010; 26: 576–588.
  • Forrest D, Simmons R. Forecasting sport: the behaviour and performance of football Tipsters. Int J Forecasting, 2000; 16: 317–331
  • Goddard J. Regression models for forecasting goals and match results in association football. Int J Forecasting, 2010; 21: 331– 340.
  • Grant A, Johnstone D. Finding profitable forecast combinations using probability scoring rules. Int J Forecasting, 2010; 26: 498–510.
  • Kuper GH, Sterken E. Participation and Performance at the London 2012 Olympics. University of Groningen, 2012, www.rug.nl/feb.
  • Hematinezhad M, Gholizadeh MH, Ramezaniyan MR, Shafiee SH, Ghazi Zahedi A. Predicting the success of nations in Asian games using neural network. Sport Sci Pract Asp, 2010; 8(1): 33-42.
  • McHale I, Morton A. A Bradley-Terry type model for forecasting tennis match results. Int J Forecasting, 2011; 27(2): 619- 630.
  • Mohammadi A. Mathematical models for ranking countries participating in the 2006 Asian Games. Olympic, 2010; (51): 7- 19.
  • Sajadi N. Analysis of mass media role in the Olympics during the twentieth century. Harekat, 2009; (3): 39-56.
  • Stanula A, Maszczyk A, Roczniok R, Pietraszewski P, Ostrowski A,Zając A, Strzała M. The Development and Prediction of Athletic Performance in Freestyle Swimming. Journal of Human Kinetics, 2012; 32(1): 97–107.
  • Strumbelj E, Vracar P. Simulating a basketball match with a homogeneous Markov model and forecasting the outcome. Int J Forecasting, 2012; 28(2): 532-542.