Literature:

Modelling sport games
  1. Goddardi, J., and Asimakopoulus, I. (2004) Forecasting Football Results and the Efficiency of Fixed-odds Betting. Journal of Forecasting. 23, 51-66
  2. Forresta,T., D., Goddardb, J., Simmons, R. (2005) Odds-setters as forecasters: The case of English football. Journal of Forecasting. 21, 551-564
  3. Gustafsson,M., Hörnquist, M., Lombardi, A. (2006) Comparison and validation of community structures in complex networks. Physica A: Statistical Mechanics and its Applications.
  4. Flitman, A., M. (2006) Towards probabilistic footy tipping: a hybrid approach utilising genetically de.ned neural networks and linear programming. Computers & Operations Research. 33, 2003-2022
  5. Lebovic, J., H. and Sigelman, L (2001) The forecasting accuracy and determinants of football rankings. International Journal of Forecasting. 17, 105-120
  6. Clarke, S., R. Home advantage in balanced competitions - english soccer 1990-1996
  7. Carmichael, F. and Thomas, D. (2005) Home-Field Effect and Team Performance: Evidence From English Premiership Football Journal of Sports Economics 6, 264-281
  8. Massey, K. (1997) Statistical Models Applied to the Rating of Sports Teams
  9. Silva, C., F., Gracia, E., S. and Saliby, E. (2002) Soccer championship analysis using Monte Carlo simulation Proceedings of the 2002 Winter Simulation Conference
  10. Kuonen, D. (1997) Statistical models for knock-out soccer tournaments
  11. Carmichael, F. and Thomas, D. (2005) Does the Best Team Win? An Analysis of Team Performances at EURO 2004 Research Paper; Football Governance Research Centre No. 2
  12. Torgler, B. (2004) The economics of the FIFA football wordcup KYKLOS 57, 287-300
  13. Dixon, M., J. and Robinson, M., E. (1998) A birth process model for assoiation football matches. The Statistician 47, 523-538
  14. Knorr-Held, L. (2000) Dynamic rating of sports teams. The Statistician 49, 261-276
  15. Crowder, M., Dixon, M., Ledford, A. and Robinson, M. (2002) Dynamic modelling and prediction of English football league matches for betting. The Statistician 51, 157-168
  16. Hirotsu, N. and Wright, M. (2003) An evaluation of characteristics of teams in association fooball by using a Markov process model. The Statistician 52, 591-602
  17. Pollard,R. and Reep, C. (1997) Measuring the effectiveness of playing strategies at soccer. The Statistician 46, 541-550
  18. Karlis, D. and Ntzoufras, I. (2003) Analysis of sport data by using bivariate Poisson models. The Statistician 52, 381-393
  19. Dixon, M., J. and Coles, S., G. (1997) Modelling assosiation football scores and inefficiencies in the football betting market. Applied Statistics 46, 265-280

Betting strategies and management
  1. Kelly,J., L., Jr (1956) A new interpretation of information rate. The Bell System Technical Journal. 917-926
  2. Haigh, J. (2000) The Kelly criterion and bet comparisons in spread betting. The Statistician. 49, 531-539

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