Probability = (Club Power * Accuracy / Distance) * (1 + (Skill Points / 100)) * (Wind Modifier) * (Terrain Modifier)

In reality, in many games, the probability of a Hole-in-One might be determined by certain stats. For example, maybe the player's accuracy, the strength of the club, the distance to the hole, terrain modifiers, etc. So the calculator could take these inputs and compute the probability.

import math

def calculate_probability(distance, club_power, wind, accuracy, bonus_skill): # Apply wind to effective distance adjusted_distance = distance + wind # Calculate the difference between club power and adjusted distance difference = abs(club_power - adjusted_distance) # Base probability could be inversely proportional to the difference base_prob = 1 - (difference / (adjusted_distance ** 0.5)) # Clamp probability between 0 and 1 base_prob = max(0, min(1, base_prob)) # Multiply by accuracy and skill modifiers total_prob = base_prob * accuracy * (1 + bonus_skill) # Clamp again in case modifiers go over 1 total_prob = max(0, min(1, total_prob)) return total_prob * 100 # Convert to percentage

Alternatively, perhaps the skill is represented as a percentage chance. So if a player has 70% accuracy and the difficulty of the hole is high, the chance is low.

Another angle: Maybe the Hole-in-One in Pangya is based on a hidden value, and the calculator uses player stats to estimate chance. For example, using club type's skill level, player's overall level, and game modifiers.

Once the probability is calculated, the user might want to simulate, say, 1000 attempts to get the expected success rate (like, on average, how many attempts are needed).