penaltyblog.models.FootballProbabilityGrid#

class penaltyblog.models.FootballProbabilityGrid(goal_matrix: ndarray[Any, dtype[_ScalarType_co]], home_goal_expectation: float, away_goal_expectation: float)[source]#

Bases: object

Class for calculating probabilities of football outcomes.

__init__(goal_matrix: ndarray[Any, dtype[_ScalarType_co]], home_goal_expectation: float, away_goal_expectation: float)[source]#

Calculate probabilities of football outcomes.

Parameters:

• goal_matrix (List[List[float]] Matrix of probabilities for each goal difference)

• home_goal_expectation (float Expected number of goals for home)

• away_goal_expectation (float Expected number of goals for away)

Methods

__init__(goal_matrix, home_goal_expectation, ...)	Calculate probabilities of football outcomes.
asian_handicap(home_away, strike)	Calculate probabilities for asian handicap market
total_goals(over_under, strike)	Calculate probabilities for total goals market

Attributes

away_win	Probability of away win
both_teams_to_score	Probability of both teams scoring
draw	Probability of draw
home_draw_away	1x2 Probabilities
home_win	Probability of home win

asian_handicap(home_away: str, strike: float) → float[source]#

Calculate probabilities for asian handicap market

Parameters:

• home_away (str) – ‘home’ or ‘away’

• strike (float) – Handicap value

property away_win: float#

Probability of away win

property both_teams_to_score: float#

Probability of both teams scoring

property draw: float#

Probability of draw

property home_draw_away: List[float]#

1x2 Probabilities

property home_win: float#

Probability of home win

total_goals(over_under: str, strike: float) → float[source]#

Calculate probabilities for total goals market

Parameters:

• over_under (str) – ‘over’ or ‘under’

• strike (float) – Total goals value