🚀Awpy 2 is here!. A revamped Python library to parse, analyze and visualize Counter-Strike 2 demos. Faster and with more features than ever, such as. - a revamped, Polars-based api + cli.- new stats + plotting modules.- fast visibility checks. 👉pip install awpy. More below 👇

RT @ekta_prashnani: It’s @CVPR week!! 🥳🤩 Come join us tomorrow morning for the Second Workshop on Computer Vision for Videogames at Room 21….

📣 We’d love your feedback, we’d love to see what interesting analysis you have, and we want to work together to push the boundaries of esports analytics. Our Discord is found at -- see you there!.

🛠️ Finally, we’ve expanded Awpy's backend infra, including hosting map data/images/meshes for different game patches. All are hosted on our shiny new domain:

🌐 Awpy 2 realizes exciting and novel analysis capabilities! Now, you can parse nav meshes and world geometry files directly for deeper insights into game strategies and player performance. We can calculate point-to-point visibility in *microseconds*.

📈 The visualization module has been expanded to better display and summarize game state, such as through animated round gifs. You can also now visualize heatmaps and navigation meshes.

📊 Awpy puts your favorite stats at your fingertips—ADR/KAST/Rating are simply a function call away. Advanced stats like win probability added (WPA) and map control are in the works!

If you prefer a CLI or want to use Awpy in an automated flow, we've got you covered. With only one command, you can parse a demo and automatically compress the output into a zip file.

Awpy is all about democratizing esports analytics through demos🫵. With minimal Python code, you can extract tick-level insights on key game events—from player positions to shots and grenades. Grab a demo from @HLTVorg or @FACEITcs, then run this snippet to see Awpy in action

Counter-Strike is more popular than ever – CS2 already achieved a peak of close to 2 million concurrent players in 2025. Demo files, which are effectively recordings of Counter-Strike matches, have been a unique aspect of the game for over a decade.

If you believe you're a good fit, please email your resume + a brief intro to [first initial][last name] at

Our team at NVIDIA Research is hiring a PhD intern (in-person, US) to work on gaming/vision/multi-modal agents. Ideal candidate has strong quantitative and technical abilities + a track record of impactful research. Must be able to obtain a US work permit! Details below 👇.

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