Merge pull request #6 from ian-shepherd/development

1.1.3 added new functions and Implied Odds and Probability enhancement

Author: ian-shepherd

CHANGELOG.md

@@ -1,5 +1,11 @@
 # Change Log
 
+### 1.1.3 2023-06-09 Added new functionality to implied_odds() and implied_prob()
+* added functionality to pass various methods to account for margin of bookmaker
+
+### 1.1.2 2023-06-07 Added expected value function
+* added expected_value_calc() calculates the expected value of given odds based on implied probability
+
 ### 1.1.1 2023-05-29 Added unit tests and fixed bugs
 * Added unit tests for all functions
 * Reduced complexity of convert_odds()

__init__.py

@@ -1,3 +1,3 @@
-__version__ = "1.1.2"
+__version__ = "1.1.3"
 
 from .pybettor import *  # noqa: F401, F403

pybettor/__init__.py

@@ -1,11 +1,15 @@
-__version__ = "1.1.2"
+__version__ = "1.1.3"
 
 from .bet_calc import bet_calc  # noqa: F401
 from .bet_prob import bet_prob  # noqa: F401
 from .break_even import break_even  # noqa: F401
+from .clv_calc import clv_calc  # noqa: F401
 from .convert_odds import convert_odds  # noqa: F401
+from .edge_calc import edge_calc  # noqa: F401
 from .expected_value_calc import expected_value_calc  # noqa: F401
 from .fair_odds import fair_odds  # noqa: F401
+from .hold_calc import hold_calc  # noqa: F401
+from .hfa_calc import hfa_calc  # noqa: F401
 from .implied_odds import implied_odds  # noqa: F401
 from .implied_prob import implied_prob  # noqa: F401
 from .kelly_bet import kelly_bet  # noqa: F401

pybettor/clv_calc.py

@@ -0,0 +1,35 @@
+from .implied_prob import implied_prob
+
+
+def clv_calc(
+    bet_odds: int or float, close_odds: int or float, category: str = "us"
+) -> float:
+    """Calculate Closing Line Value
+    This function calculates the closing line value (CLV) for a given bet.
+
+    Args:
+        bet_odds (int, float): Odds or Implied Win Probability for the bet
+        close_odds (int, float): Closing Odds or Implied Win Probability for the bet
+        category (str, optional): type of odds. Defaults to "us". \n
+            'us', American Odds \n
+            'dec', Decimal Odds \n
+            'frac', Fractional Odds
+
+    Returns:
+        float: Closing Line Value (CLV) of a bet
+    """
+
+    assert isinstance(bet_odds, (int, float)), "bet_odds must be numeric"
+    assert isinstance(close_odds, (int, float)), "close_odds must be numeric"
+    assert category in [
+        "us",
+        "frac",
+        "dec",
+    ], "input category must be either: ('us', 'dec', 'frac')"
+
+    bet_prob = implied_prob(bet_odds, category=category)[0]
+    close_prob = implied_prob(close_odds, category=category)[0]
+
+    clv = (close_prob - bet_prob) / bet_prob
+
+    return clv

pybettor/convert_odds.py

@@ -1,3 +1,4 @@
+from typing import Union
 from fractions import Fraction
 from .implied_odds import implied_odds
 from .implied_prob import implied_prob
@@ -44,12 +45,14 @@ def _convert_frac_to_frac(odds):
     return frac
 
 
-def convert_odds(odds, cat_in="us", cat_out="all") -> list or dict:
+def convert_odds(
+    odds: Union[int, float, list], cat_in="us", cat_out="all"
+) -> list or dict:
     """Odds Converter
     This function converts any odds or probability.
 
     Args:
-        odds (float): Odds, or lines, for a given bet(s) (-115, -105)
+        odds (int, float, list): Odds, or lines, for a given bet(s) (-115, -105)
         cat_in (str, optional):  \n
             'us', American Odds \n
             'dec', Decimal Odds \n

pybettor/edge_calc.py

@@ -0,0 +1,30 @@
+from .implied_prob import implied_prob
+
+
+def edge_calc(
+    win_prob: int or float, odds: int or float, category: str = "us"
+) -> float:
+    """Calculate the edge of a bet given the win probability and odds.
+
+    Args:
+        win_prob (intorfloat): _description_
+        odds (intorfloat): _description_
+        category (str, optional): _description_. Defaults to "us".
+
+    Returns:
+        float: edge of the bet
+    """
+
+    assert isinstance(win_prob, (int, float)), "win_prob must be numeric"
+    assert 0 <= win_prob <= 1, "win_prob must be in the range of 0 to 1 inclusive"
+    assert isinstance(odds, (int, float)), "odds must be numeric"
+    assert category in [
+        "us",
+        "frac",
+        "dec",
+        "prob",
+    ], "input category must be either: ('us', 'dec', 'frac', 'prob')"
+
+    edge = win_prob - implied_prob(odds, category=category)[0]
+
+    return edge

pybettor/hfa_calc.py

@@ -0,0 +1,30 @@
+import numpy as np
+
+
+def hfa_calc(win_p_neutral: int or float, win_p_leag_hm: int or float) -> float:
+    """Calculate Home Field Advantage
+    This function calculates the home field advantage (HFA) for a given bet.
+
+    Args:
+        win_p_neutral (int, float): Win Probability Neutral Site
+        win_p_leag_hm (int, float): Win Probability League Home
+
+    Returns:
+        float: Home Field Advantage (HFA) of a bet
+    """
+
+    assert isinstance(win_p_neutral, (int, float)), "win_p_neutral must be numeric"
+    assert (
+        0 <= win_p_neutral <= 1
+    ), "win_p_neutral must be in the range of 0 to 1 inclusive"
+    assert isinstance(win_p_leag_hm, (int, float)), "win_p_leag_hm must be numeric"
+    assert (
+        0 <= win_p_leag_hm <= 1
+    ), "win_p_leag_hm must be in the range of 0 to 1 inclusive"
+
+    log_odds_tm = np.log(win_p_neutral) - np.log(1 - win_p_neutral)
+    log_odds_lg = np.log(win_p_leag_hm) - np.log(1 - win_p_leag_hm)
+
+    hfa = np.exp(log_odds_tm + log_odds_lg) / (1 + np.exp(log_odds_tm + log_odds_lg))
+
+    return hfa

pybettor/hold_calc.py

@@ -0,0 +1,31 @@
+from typing import Union  # noqa: F401
+from .implied_prob import implied_prob
+
+
+def hold_calc(odds, category: str = "us", **kwargs) -> float:
+    """Sportsbook Hold Calculator
+    This function calculates the hold perrcentage that the sportsbook has for the given bet.
+
+    Args:
+        odds int, float, list): odds of an event
+        category (str, optional): type of odds. Defaults to "us". \n
+            'us', American Odds \n
+            'dec', Decimal Odds \n
+            'frac', Fractional Odds
+        **kwargs: keyword arguments to pass to implied_prob
+
+    Returns:
+        float: hold percentage of odds
+    """
+
+    # Error handling
+    if not all(isinstance(line, (int, float)) for line in odds):
+        raise ValueError("Lines must be numeric")
+
+    imp_probs = implied_prob(odds, category=category, **kwargs)
+    if isinstance(imp_probs, dict):
+        hold = imp_probs.get("margin")
+    else:
+        hold = 1 - (1 / sum(imp_probs))
+
+    return hold