Following the success of last season, my thoughts obviously turned to whether this can be repeated. Or more accurately, what can be expected from the algorithm betting model in future seasons both in terms of return and the variability of those returns. “Monte Carlo” is the name given to simulations which make use of computer generated random numbers to identify the range of possible outputs a model may generate in the ‘real world’. Each random number generates an input from a user defined probability distribution which is run through the user’s model to produce a simulated outcome on each run. Run this simulation thousands of times and you generate a probability distribution for the output of your model. Assigning a probability distribution to football match results
Defines functional for binary mixture of non-additive hard-spheres using a Kierlik-Rosinberg formulation based on the Rosenfeld hard sphere functional. Uses functional to determine the two-body direct correlation function, partial structure factors, and radial distribution functions. Phase diagram is calculated. Radial distribution functions compared to MC simulations and show good agreement.
R.Seetharaman, R. Pratheep, Einstein, and A. Lenus. International Journal on Recent and Innovation Trends in Computing and Communication, 3 (3):
915--918(March 2015)
F. A. Mazyad, and C. Fonlupt. International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI), 4 (1):
01 - 14(February 2015)