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bet-tracker

Log betting entries, resolve outcomes, and analyze profit and loss metrics.

2|1|Updated May 1, 2026
Search Tags:#performance#risk management#statistics#betting#ROI#CLV
One-click install
npx skills add https://github.com/PuckAPI/claude-sports-analytics --skill bet-tracker
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bet-tracker
Source: https://github.com/PuckAPI/claude-sports-analytics/tree/main/skills/bet-tracker
Command: npx skills add https://github.com/PuckAPI/claude-sports-analytics --skill bet-tracker

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, scipy, and includes scripts (resource) components.

What problem does it solve?

This Skill helps users track, analyze, and interpret their betting results, enabling them to evaluate their edge and manage risk effectively.

Core Features & Use Cases

  • Bet Logging: Record bets at the time they are placed, including odds, stake, and model probabilities.
  • Outcome Resolution: Update open bets with actual results once the game concludes, calculating profit or loss.
  • Live Performance Metrics: Generate statistics such as win rate, ROI, drawdown, and average CLV to assess betting effectiveness.
  • Edge Detection: Detect signals of positive or negative expected value through CLV and win rate analysis.
  • Risk Management: Provide alerts for drawdowns, persistent negative CLV, and staking issues to prevent substantial losses.
  • Significance Testing: Conduct statistical tests to verify if a winning pattern is significant or likely due to chance.

Quick Start

Log each new bet immediately after placement to keep records consistent and then regularly update with outcomes and CLV calculations to review performance metrics.

Frequently Asked Questions about bet-tracker

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I track sports betting performance and calculate ROI?▼

To track sports betting performance, you log bets with odds, stake, and model probabilities, then update outcomes to calculate ROI, win rate, and drawdown for evaluating your edge.

How does Closing Line Value (CLV) analysis help evaluate my betting edge?▼

CLV analysis evaluates your betting edge by comparing your recorded odds against final market lines, detecting positive or negative expected value signals to optimize betting strategies.

Can I use statistical significance testing to verify my betting strategy?▼

Yes, statistical significance testing verifies if your winning pattern is genuine or due to chance by analyzing historical bet outcomes and profit data using scipy.

What is the best way to manage betting risk and prevent substantial drawdowns?▼

The best way to manage betting risk is by monitoring live performance metrics to trigger alerts for persistent negative CLV, staking issues, and drawdowns to prevent substantial losses.

Does this bet tracking tool require pandas and scipy to run?▼

Yes, the bet tracking tool requires pandas and scipy dependencies to process betting entries, calculate performance statistics, and conduct significance testing.

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