Unofficial implementation of "TTNet: Real-time temporal and spatial video analysis of table tennis" (CVPR 2020)

Computer Vision app designed to analyze basketball shots from video footage using YOLOv11 finetuned with a custom dataset.

🏅 AI-спорттех — SportTechCup 2024

A collection of literature on the use of computational intelligence methods in sports

"Predicting Ball Location From Optical Tracking Data" - contains data analysis, model development and testing

A minimalistic toolbox for extracting features from sports activity files written in Python

This project was developed in Java, using the Java Swing library to create an intuitive and friendly user interface. Its main purpose is to assist in the management of statistics on volleyball matches and players, simplifying the process of collecting, analyzing and visualizing essential data for the performance of teams and athletes.

Metrics to analyze table tennis games

The app enables booking football fields, organizing challenges, and connecting with gyms, trainers, and sports services. It also offers reservations for swimming pools, photoshoot locations, and sports gear purchases, with order tracking and delivery. A version for venue owners and trainers

🏓 30th Place Solution for AI CUP 2025 | An machine learning project for the AI CUP 2025 (Top 3% finish). Features robust player-centric validation and domain-driven feature engineering to achieve strong generalization on private data.

A simple fitness tracker app with material you design support.

In this project, we created an 'expected goals' metric to help us assess a team's performance rather than the actual number of goals scored. We merged this metric with the calculation of a team's offensive and defensive ratings, which are updated after every game, to create a classification model that predicts the outcome of future matches, as w…

Various machine learning approaches for soccer prediction focusing on Ensemble learning algorithms as a method to obtain the optimal prediction

Bachelor Thesis application backend

Statistical analysis of elite chess ahead of the 2020/21 FIDE Candidates

Implementation of the VAEP framework including a new version: Hybrid-VAEP.

ERA-5 climate data pipeline for WBGT index calculations (extract ZIP-.nc, merge, DataFrame export)

A tool designed to help users uncover trends, activity distribution, and valuable insights from anything happening on Kuyy, a platform where people can discover and join various sports activities like tennis, padel, and more. Perfect for anyone who wants quick, data-driven understanding of what’s popular and where the action is.