socceraction.xthreat.ExpectedThreat¶

class socceraction.xthreat.ExpectedThreat(l=16, w=12, eps=1e-05)¶

An implementation of the Expected Threat (xT) model.

The xT model [1] can be used to value actions that successfully move the ball between two locations on the pitch by computing the difference between the long-term probability of scoring on the start and end location of an action.

Parameters:

l (int) – Amount of grid cells in the x-dimension of the grid.
w (int) – Amount of grid cells in the y-dimension of the grid.
eps (float) – The desired precision to calculate the xT value of a cell. Default is 5 decimal places of precision (1e-5).

l¶

Amount of grid cells in the x-dimension of the grid.

Type:: int

w¶

Amount of grid cells in the y-dimension of the grid.

Type:: int

eps¶

The desired precision to calculate the xT value of a cell. Default is 5 decimal places of precision (1e-5).

Type:: float

heatmaps¶

The i-th element corresponds to the xT value surface after i iterations.

Type:: list(np.ndarray)

xT¶

The final xT value surface.

Type:: np.ndarray

scoring_prob_matrix¶

The probability of scoring when taking a shot for each cell.

Type:: np.ndarray, shape(M,N)

shot_prob_matrix¶

The probability of choosing to shoot for each cell.

Type:: np.ndarray, shape(M,N)

move_prob_matrix¶

The probability of choosing to move for each cell.

Type:: np.ndarray, shape(M,N)

transition_matrix¶

When moving, the probability of moving to each of the other zones.

Type:: np.ndarray, shape(M*N,M*N)

References

Methods

`__init__`
`fit`	Fits the xT model with the given actions.
`interpolator`	Interpolate over the pitch.
`rate`	Compute the xT values for the given actions.
`save_model`	Save the xT value surface in JSON format.