Leaderboard Explanation
for Users
Game Tutorial
The leaderboard points system is designed to ensure fairness and equal opportunity for all participants, regardless of the amount they commit to their predictions. Here's how it works:
Multiplier Calculation: Your multiplier is determined by the ratio of your total correct predictions to the total predictions you placed. This multiplier reflects how effectively you've turned your predictions into successful outcomes.
Points Calculation: Points are calculated using the formula: √((Total prediction value - Total win value) x Multiplier). This formula considers the difference between the total value you committed to your predictions and the total value you won, divided by your multiplier. If the result of (Total prediction value - Total win value) is greater than 0 (indicating a net gain), the formula is applied to calculate your points.
Objective: The main goal is to ensure fairness among users, regardless of the size of their predictions.
Risk-Reward Relationship: The system rewards users based on the risk they take relative to their successful predictions. Users who take higher risks by committing more value to their predictions (resulting in higher multipliers) and achieve positive results will earn more points.
Example: Consider two users, Alice and Bob, with different prediction strategies:
Alice:
Total Prediction Value: $300
Total Win Value: $3000
Multiplier: 10 (3000/300)
Points: √((3000 - 300) x 10) ≈ 164 (High reward for successful high-risk prediction)
Bob:
Total Prediction Value: $1000
Total Win Value: $2000
Multiplier: 2 (2000/1000)
Points: √((2000 - 1000) x 2) ≈ 45 (Lower reward for successful lower-risk prediction)
In this scenario, despite Alice having a much higher multiplier, both Alice and Bob end up with similar points. This illustrates how the system rewards users based on the risk they take relative to their successful predictions, rather than favoring users who commit larger amounts. Despite the significant difference in their multipliers and prediction values, the points balance out to ensure fairness in the leaderboard system.
Game Tutorial
Leaderboard Explanation for Users
The leaderboard points system is designed to ensure fairness and equal opportunity for all participants, regardless of the amount they commit to their predictions. Here's how it works:
Multiplier Calculation: Your multiplier is determined by the ratio of your total correct predictions to the total predictions you placed. This multiplier reflects how effectively you've turned your predictions into successful outcomes.
Points Calculation: Points are calculated using the formula: √((Total prediction value - Total win value) x Multiplier). This formula considers the difference between the total value you committed to your predictions and the total value you won, divided by your multiplier. If the result of (Total prediction value - Total win value) is greater than 0 (indicating a net gain), the formula is applied to calculate your points.
Objective: The main goal is to ensure fairness among users, regardless of the size of their predictions.
Risk-Reward Relationship: The system rewards users based on the risk they take relative to their successful predictions. Users who take higher risks by committing more value to their predictions (resulting in higher multipliers) and achieve positive results will earn more points.
Example: Consider two users, Alice and Bob, with different prediction strategies:
Alice:
Total Prediction Value: $300
Total Win Value: $3000
Multiplier: 10 (3000/300)
Points: √((3000 - 300) x 10) ≈ 164 (High reward for successful high-risk prediction)
Bob:
Total Prediction Value: $1000
Total Win Value: $2000
Multiplier: 2 (2000/1000)
Points: √((2000 - 1000) x 2) ≈ 45 (Lower reward for successful lower-risk prediction)
In this scenario, despite Alice having a much higher multiplier, both Alice and Bob end up with similar points. This illustrates how the system rewards users based on the risk they take relative to their successful predictions, rather than favoring users who commit larger amounts. Despite the significant difference in their multipliers and prediction values, the points balance out to ensure fairness in the leaderboard system.