DataCoach vs Freezetime
DataCoach
datacoach.ggFreezetime
benginn.github.ioSide by side
| Figure | DataCoach | Freezetime |
|---|---|---|
| Price from | $11/mo | €4.99/mo |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | Yes |
| Web | Yes | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | — | Yes |
| Self-hosted | — | Yes |
| Plans published | 6 | 4 |
| Spec score · Game Replay Analyzers | 8.8 (#4) | 9.1 (#2) |
| Data retention | The policy says school data is anonymized or deleted within 30 days after a contract ends, depending on the school's request. | Archived matches are kept indefinitely, while older seasons receive less weight in tendencies and predictions using a 90-day half-life. |
| Support | The contact page lists [email protected] for customer support and says the team responds to organization inquiries within 24 hours. | The project directs questions and setup help to GitHub Discussions and bugs or feature requests to GitHub Issues. |
| What it does | DataCoach converts Rocket League replay files into esports performance analytics, coaching insights and training plans. | Freezetime analyzes Counter-Strike 2 professional and personal demo files for replay and tactical reporting. |
Plans
DataCoach
- Player BasicFree
- Player - Platinum$11 a month
- Player - Diamond$18 a month
- Collegiate TeamPriced on request
- High School TeamsPriced on request
- Pro TeamsPriced on request
In their own words
Freezetime
Freezetime is a free, self-hosted analysis platform for Counter-Strike 2 demos. Its public archive is a read-only site with more than 2,600 professional matches, searchable and grouped by series, and needs no installation or account. For a personal demo, the Analyze page parses one file in the browser using WebAssembly, so the file stays on the user's machine. Processing produces 16 Hz player positions along with kills, grenades, and economy data. Synchronized 2D replays show player health, economy, kill feed, grenade trajectories, smoke, and flash effects. Analysis tools include opponent reports, predictions, ML Lab, leaderboards, match comparison, heatmaps, ghost rounds, Moments, and Pattern Finder. My DB can process private demos without the server keeping a copy. Self-hosting unlocks features marked self-host only, but users must supply their own demos because the repository contains no match data or database dumps. The project says smart features use deterministic methods and locally trained models rather than external AI services. Freezetime is MIT licensed, with no warranty.