def ts_winp(a, b, env=None):
"""Win probability of player a over b given their trueskill ratings.
Formula found at https://github.com/sublee/trueskill/issues/1#issuecomment-244699989"""
if not env:
env = trueskill.global_env()
epsilon = trueskill.calc_draw_margin(env.draw_probability, 2)
denom = math.sqrt(a.sigma**2 + b.sigma**2 + (2 * env.beta**2))
return phi((a.mu - b.mu - epsilon) / denom)
def __init__(self, name, daily_sigma_decay=0, k=3,
established_sigma=None, **kwargs):
super(TrueSkillSystem, self).__init__(name)
self.env = trueskill.TrueSkill(**kwargs)
self.daily_sigma_decay = daily_sigma_decay
self.established_sigma = established_sigma
self.k = k
self.two_p_draw_margin = trueskill.calc_draw_margin(
self.env.draw_probability, 2, env=self.env)
def __init__(self,
name,
daily_sigma_decay=0,
k=3,
established_sigma=None,
**kwargs):
super(TrueSkillSystem, self).__init__(name)
self.env = trueskill.TrueSkill(**kwargs)
self.daily_sigma_decay = daily_sigma_decay
self.established_sigma = established_sigma
self.k = k
self.two_p_draw_margin = trueskill.calc_draw_margin(
self.env.draw_probability, 2, env=self.env)
def predict(self,
teams: Tuple[str, str],
rosters: Tuple[Roster, Roster] = None,
drawable: bool = False) -> Tuple[float, float]:
"""Given two teams, return win/draw probabilities of them."""
env = self.env_drawable if drawable else self.env_undrawable
team1_ratings, team2_ratings = self._teams_ratings(teams, rosters)
size = len(team1_ratings) + len(team2_ratings)
delta_mu = (sum(r.mu
for r in team1_ratings) - sum(r.mu
for r in team2_ratings))
draw_margin = calc_draw_margin(env.draw_probability, size, env=env)
sum_sigma = sum(r.sigma**2
for r in chain(team1_ratings, team2_ratings))
denom = sqrt(size * env.beta**2 + sum_sigma)
p_win = env.cdf((delta_mu - draw_margin) / denom)
p_not_loss = env.cdf((delta_mu + draw_margin) / denom)
return p_win, p_not_loss - p_win
def __init__(self, name, trueskill_env, daily_sigma_decay=0, **kwargs):
super(RatingDeviationSystem, self).__init__(name, **kwargs)
self.env = trueskill_env
self.daily_sigma_decay = daily_sigma_decay
self.draw_margin = trueskill.calc_draw_margin(
self.env.draw_probability, 2, env=self.env)
def __init__(self, name, trueskill_env, daily_sigma_decay=0, **kwargs):
super(RatingDeviationSystem, self).__init__(name, **kwargs)
self.env = trueskill_env
self.daily_sigma_decay = daily_sigma_decay
self.draw_margin = trueskill.calc_draw_margin(
self.env.draw_probability, 2, env=self.env)
def win_probability(self, player, opponent):
delta_mu = player.rating.mu - opponent.rating.mu - calc_draw_margin(self.draw, 2, self.env)
denom = sqrt(2 * (self.beta * self.beta) + pow(player.rating.sigma, 2) + pow(opponent.rating.sigma, 2))
return cdf(delta_mu / denom)
def __init__(self, name, trueskill_env, daily_sigma_decay=0):
super(TrueSkillSystem, self).__init__(name)
self.env = trueskill_env
self.daily_sigma_decay = daily_sigma_decay
self.draw_margin = trueskill.calc_draw_margin(
self.env.draw_probability, 2, env=self.env)
