TennisFlow AI Model Performance & Release Notes

TennisFlow publishes its AI performance data transparently. Instead of vague claims like “AI-powered,” we show measurable results for our models on a validated dataset.

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AI Model Performance

Structured results of the current TennisFlow models on the internal validation dataset.

TennisFlow AI results on the internal validation dataset.
Task Metric Result
Stroke Detection Precision 97.66 %
Stroke Detection Recall 97.73 %
Stroke Detection F1 Score 97.70 %
Stroke Type Classification Accuracy 99.9 %
Stroke Detail Classification Accuracy 95.9 %

The results are measured on TennisFlow’s internal validation dataset using manually annotated ground-truth data.

Why do we publish our AI metrics?

Many apps promote “AI” without making its quality measurable. At TennisFlow, we want to be transparent. That is why we regularly publish the performance data of our AI models and document their progress with every release.

Release Notes

Chronological overview of app versions – newest first.

Version 1.2.3

  • Multiple player profiles per account – ideal for families and coaches
  • Improved racket detection (+2 %)
  • Better stroke recognition

Version 1.2.2

  • Stability and performance improvements
  • Finer filtering and sorting of video clips

Version 1.2.1

  • Bug fixes and UI improvements
  • Improved analysis overview