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2. Boosting (video games) - Wikipedia

   en.wikipedia.org/wiki/Boosting_(video_games)

   Duo queue boosting can also occur in the form of a highly ranked gamer losing to a low-ranked competitor intentionally to boost their rank due to the way the MMR (matchmaking rating) system works. [21] Placement matches boosting. This Elo boosting category entails hiring a professional gamer to give a new gaming account a positive head start.

3. Glicko rating system - Wikipedia

   en.wikipedia.org/wiki/Glicko_rating_system

   Mark Glickman created the Glicko rating system in 1995 as an improvement on the Elo rating system. [1]Both the Glicko and Glicko-2 rating systems are under public domain and have been implemented on game servers online like Counter-Strike: Global Offensive, Team Fortress 2, [2] Dota 2, [3] Guild Wars 2, [4] Splatoon 2, [5] Online-go.com, [6] Lichess and Chess.com.

4. Elo hell - Wikipedia

   en.wikipedia.org/wiki/Elo_hell

   Elo hell (also known as MMR hell) is a video gaming term used in MOBAs and other multiplayer online games with competitive modes. [1] It refers to portions of the matchmaking ranking spectrum where individual matches are of poor quality, and are often determined by factors such as poor team coordination which are perceived to be outside the individual player's control.

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   mail.aol.com

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6. Elo rating system - Wikipedia

   en.wikipedia.org/wiki/Elo_rating_system

   Few video games use the original Elo rating system. According to Lichess, an online chess server, the Elo system is outdated, with Glicko-2 now being used by many chess organizations. [71] PlayerUnknown’s Battlegrounds is one of the few video games that utilizes the very first Elo system.

7. CatBoost - Wikipedia

   en.wikipedia.org/wiki/Catboost

   It works on Linux, Windows, macOS, and is available in Python, [8] R, [9] and models built using CatBoost can be used for predictions in C++, Java, [10] C#, Rust, Core ML, ONNX, and PMML. The source code is licensed under Apache License and available on GitHub. [6] InfoWorld magazine awarded the library "The best machine learning tools" in 2017.