Monitoring Data Changes

This integration scenario explains how to efficiently monitor updates across MLB data using the Daily Change Log feed. Instead of repeatedly polling multiple endpoints, applications can use the change log to detect which data has changed and selectively refresh only the affected resources.

This approach is especially useful for keeping schedules, standings, player profiles, and game results current while conserving API call limits.

This scenario is commonly used to:

• Detect schedule or game status changes
• Refresh standings after game completion
• Monitor player profile updates
• Keep cached data synchronized
• Reduce unnecessary polling of core feeds

Overview

The Daily Change Log acts as a centralized index of data modifications for a given date. It does not return full datasets. Instead, it provides entity IDs and timestamps indicating what has changed.

Your application can then use those IDs to call the appropriate MLB feeds and retrieve updated data only where needed.

A typical workflow looks like this:

Daily Change Log → Identify changed entities → Refresh relevant feeds

Relevant Feeds

The following feeds are commonly used when monitoring MLB data changes:

High-Level Workflow

A typical data monitoring integration follows this flow:

1. Call the Daily Change Log for a specific date
2. Review which entity types have changed
3. Capture the affected entity IDs
4. Refresh only the feeds related to those entities
5. Update cached or displayed data accordingly

⏱️

Daily Change Log Time Window

Each day in the Daily Change Log represents a 24-hour UTC window:

• Start: 10:00:00 UTC
• End: 09:59:59 UTC (the following day)

When requesting the log for a given date, the response includes all changes that occurred within this time range, not strictly from midnight to midnight.

Integration Steps

1. Call the Daily Change Log

Start by calling the Daily Change Log for the date you want to monitor.

The response includes:

• A start_time and end_time window

• Lists of changed entities such as:

  • players
  • schedule
  • results
  • standings

• A last_modified timestamp for each entity

The change log only indicates what changed, not what the new values are.

2. Identify Changed Entity Types

Review which sections are present in the response. Only entity types that have changed during the time window are included. If a section is not present, no changes occurred for that entity type during the requested window.

{
  "start_time": "2025-08-28T09:00:00+00:00",
  "end_time": "2025-08-29T08:59:58+00:00",
  "players": [
    {
      "id": "1b2d6c3b-5c96-45fd-bce6-2a31a28cfe48",
      "first_name": "Shawn",
      "last_name": "Dubin",
      "last_modified": "2025-08-28T14:07:45+00:00"
    }
  ]
}

{
  "schedule": [
    {
      "id": "deaf25b5-54ae-4bbc-acf9-25d791b14db5",
      "title": "Tigers(DET)@Royals(KC)",
      "last_modified": "2025-08-28T12:18:53+00:00"
    }
  ]
}

{
  "standings": [
    {
      "id": "93941372-eb4c-4c40-aced-fe3267174393",
      "name": "Red Sox",
      "abbr": "BOS",
      "last_modified": "2025-08-28T19:33:01+00:00"
    }
  ]
}

For example:

• A game appearing under schedule may indicate:

  • A status update (scheduled → in-progress → final)
  • A time change
  • A postponement or correction

• Entries under players often reflect:

  • Roster updates
  • Biographical corrections
  • Name or profile adjustments

• Standings updates typically occur:

  • After games complete
  • Following statistical validation or corrections

Your application should treat each section independently and only react to the data types it cares about.

3. Refresh Affected Feeds

Use the returned IDs to selectively call the appropriate MLB feeds.

Examples:

• Game ID → refresh Schedule feeds, Game feeds, Statistics feeds (If updates impact aggregated statistics)
• Player ID → refresh Player Profile
• Standings changes → refresh Standings (and optionally Rankings)

This targeted approach avoids unnecessary full-season refreshes.

💡

Refresh Game-Related Feeds on Schedule or Result Changes

When the Daily Change Log reports a change for a game ID (under schedule or results), refresh all relevant game endpoints, including:

• Game Summary / Game Extended Summary
• Game Boxscore
• Game Play-by-Play
• Game Pitch Metrics

A single game update may impact scoring, statistics, and standings calculations. Refreshing all related game feeds ensures consistency across your application.

4. Handle Timing and Frequency

The Daily Change Log is designed to be polled at regular intervals based on your platform’s freshness requirements.

Best practice is to:

• Poll once per day for general synchronization
• Increase frequency during high-activity periods (trade deadlines, postseason, heavy game days)
• Use the last_modified timestamps to determine recency
• Combine with update frequency guidance from individual feeds
• For more details, see the Update Frequencies page

Common Use Cases

Monitoring data changes supports many platform features, including:

• Keeping cached standings in sync
• Updating results immediately after games conclude
• Detecting late schedule changes or postponements
• Refreshing player updates and transactions
• Powering backend data ingestion pipelines

Best Practices

• Use the Daily Change Log as a trigger, not a data source
• Only refresh feeds related to changed entities
• Do not poll game or standings feeds unnecessarily
• Expect standings updates after games complete
• Combine change detection with documented update frequencies
• Treat downstream feeds as the source of truth for full datasets