Building a Cricket Stats Dashboard with AWS

The Idea

I wanted to track my cricket performance over time: batting average, strike rate, scores by venue, performance against different bowling types. Nothing fancy, just a personal dashboard.

The Stack

S3: Store match data as JSON files (one file per match)

Lambda: Process new match data, calculate stats

DynamoDB: Store aggregated statistics

QuickSight: Visualize trends and patterns

EventBridge: Trigger weekly summary emails

The Data Model

Each match file looks like this:

{
  "date": "2024-11-10",
  "venue": "Local Ground",
  "opposition": "Team X",
  "innings": {
    "runs": 45,
    "balls": 38,
    "fours": 6,
    "sixes": 1,
    "dismissal": "caught",
    "bowling_type": "pace"
  }
}

Simple, easy to update from my phone after a match.

The Processing

Lambda function triggered on S3 upload:

1. Read the new match data
2. Calculate match-level stats (strike rate, boundary %)
3. Update career aggregates in DynamoDB
4. Trigger QuickSight refresh

The Dashboard

QuickSight shows:

• Career batting average over time
• Strike rate by venue
• Performance vs pace vs spin
• Recent form (last 10 innings)
• Best partnerships

What I Learned

Keep it simple: I started with complex schemas and multiple tables. Simplified to one S3 file per match and it's much easier to maintain.

Manual input is fine: I considered OCR from scorecards or API integrations. Typing 5 fields after a match is actually faster.

Visualizations matter: Seeing my average trend upward is more motivating than I expected. Data-driven practice works.

Cost

Basically free:

• S3: ~$0.01/month
• Lambda: Free tier covers it
• DynamoDB: Free tier covers it
• QuickSight: $9/month (only cost)

Next Steps

I'm thinking about:

• Adding bowling stats
• Comparing my stats to professional benchmarks
• Predicting optimal batting position based on conditions

If you're interested in the code, let me know. Happy to share the Lambda functions and QuickSight templates.