  Go gaming is a struggle between adversaries, black and white simple stones,
and aim to control the most Go board territory for success. Rules are simple
but Go game fighting is highly intricate. Stones placement and interaction on
board is random-appearance, likewise interaction phenomena among basic elements
in physics thermodynamics, chemistry, biology, or social issues. We model the
Go game dynamic employing an Ising model energy function, whose interaction
coefficients reflect the application of rules and tactics to build long-term
strategies. At any step of the game, the energy function of the model assesses
the control and strength of a player over the board. A close fit between
predictions of the model with actual game's scores is obtained. AlphaGo
computer is the current top Go player, but its behavior does not wholly reveal
the Go gaming nature. The Ising function allows for precisely model the
stochastic evolutions of Go gaming patterns, so, to advance the understanding
on Go own-dynamic -beyond the player`s abilities. The analysis of the frequency
and combination of tactics shows the formation of patterns in the groups of
stones during a game, regarding the turn of each player, or if human or
computer adversaries are confronted.

Artificial Intelligence;Applied Physics;Data Analysis, Statistics and Probability