CricRating Methodology
CricRating is built on structured data analysis and logical modeling. This page explains how the system evaluates player performance.
📦 Data Sources
CricRating uses structured cricket datasets, including match-level and aggregated player statistics.
These datasets are processed and normalized to ensure consistency before analysis.
⚙️ Core Metrics
Instead of relying on a single statistic, CricRating evaluates multiple performance dimensions.
- Aggression and scoring intent
- Boundary contribution vs running runs
- Consistency across innings
- Strike efficiency
- Bowling effectiveness and control
Each metric is calculated independently before being combined.
🧮 Scoring Model
Each metric is converted into a normalized score.
These scores are then weighted and combined to generate a final CricRating score out of 100.
This ensures that no single factor dominates the rating unfairly.
⚖️ Limitations
No model is perfect.
CricRating is based on available data, which may not capture every match context such as pitch conditions, opposition strength, or match pressure.
The goal is not perfection, but a meaningful and consistent way to compare players.
🔄 Updates & Improvements
The methodology evolves over time.
As new data becomes available and better models are developed, CricRating is updated to improve accuracy and relevance.
📊 See It in Action
Explore how these methods translate into real player rankings and insights.