113 lines
3.6 KiB
Python
113 lines
3.6 KiB
Python
"""量化投注引擎（EV、泊松預測、海拔修正）。"""
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from __future__ import annotations
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import math
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import numpy as np
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import pandas as pd
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from scipy.stats import poisson
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def calculate_value_bet(true_prob: float, decimal_odds: float, *, stake: float = 1.0) -> tuple[float, bool]:
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"""計算期望值（EV）並判斷是否屬於 Value Bet。
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EV 計算：EV = (勝率 * 利潤) - (敗率 * 本金)
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其中利潤 = decimal_odds - 1。
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Returns
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-------
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ev_pct: float
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以本金為基底的 EV 百分比（EV / stake）。
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is_value_bet: bool
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當 EV > 0.03（3%）回傳 True。
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"""
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prob = float(true_prob)
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odds = float(decimal_odds)
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if not 0 <= prob <= 1 or odds <= 1 or stake <= 0:
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return 0.0, False
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profit = odds - 1
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ev = prob * profit - (1 - prob) * stake
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ev_pct = ev / stake
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return round(ev_pct, 6), ev_pct > 0.03
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class PoissonPredictor:
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"""球員進球分佈預測器（2x2 進球建模）。"""
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def __init__(
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self,
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home_attack: float,
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home_defense: float,
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away_attack: float,
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away_defense: float,
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league_avg_goals: float,
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) -> None:
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self.home_attack = float(home_attack)
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self.home_defense = float(home_defense)
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self.away_attack = float(away_attack)
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self.away_defense = float(away_defense)
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self.league_avg_goals = float(league_avg_goals)
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# 以攻守乘積估算 λ，並限制在合理範圍避免極端值發散。
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home_lambda = league_avg_goals * (self.home_attack / max(self.away_defense, 0.01))
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away_lambda = league_avg_goals * (self.away_attack / max(self.home_defense, 0.01))
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self.home_lambda = float(np.clip(home_lambda, 0.02, 6.5))
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self.away_lambda = float(np.clip(away_lambda, 0.02, 6.5))
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def predict_exact_score(self, home_goals: int, away_goals: int) -> float:
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"""回傳指定波膽（home_goals, away_goals）發生機率。"""
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p_home = poisson.pmf(home_goals, self.home_lambda)
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p_away = poisson.pmf(away_goals, self.away_lambda)
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return float(p_home * p_away)
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def predict_over_under_prob(self, line: float = 2.5, max_goals: int = 10) -> tuple[float, float]:
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"""回傳（under, over）機率。"""
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goals = pd.MultiIndex.from_product(
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[range(max_goals + 1), range(max_goals + 1)],
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names=['home', 'away'],
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).to_frame(index=False)
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def joint_prob(r: pd.Series) -> float:
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return float(poisson.pmf(r['home'], self.home_lambda) * poisson.pmf(r['away'], self.away_lambda))
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probs = goals.apply(joint_prob, axis=1)
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total_goals = goals['home'] + goals['away']
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under = float(probs[total_goals <= line].sum())
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over = float(probs[total_goals > line].sum())
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return under, over
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def adjust_away_defense_for_altitude(
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base_defense_rating: float,
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venue_altitude_meters: float,
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*,
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is_second_half: bool,
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penalty_factor: float = 0.35,
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) -> float:
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"""高海拔下修正客隊防守能力。
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當場地海拔高於 1500m 且處於下半場，套用對數懲罰，
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代表客隊在氧氣濃度降低下體能下降導致防守效率衰退。
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"""
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base = float(base_defense_rating)
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if venue_altitude_meters <= 1500 or not is_second_half:
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return base
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# 以 log(1 + altitude/1000) 做平滑遞增函式，避免低海拔時劇烈改變。
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altitude_penalty = penalty_factor * math.log1p(venue_altitude_meters / 1000)
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return base * (1 - min(max(altitude_penalty, 0), 0.45))
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__all__ = [
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'calculate_value_bet',
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'PoissonPredictor',
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'adjust_away_defense_for_altitude',
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]
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