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Coachless

Coachless offers an advanced analytics platform for League of Legends players, using Win Probability Added (WPA) to objectively measure item and build performance. Our proprietary model isolates item impact on win probability, helping players discover meta-breaking combinations and identify key gameplay moments that influence victory.

Updated 2 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Traditional methods for evaluating item effectiveness in competitive gaming often rely on win rates, which are inherently biased by player skill and situational context. This lack of objective data makes it difficult for players to identify truly impactful item builds and understand their precise contribution to in-game success.

Solution

Coachless provides an advanced analytics platform that leverages Win Probability Added (WPA) to objectively measure item and build performance in League of Legends. By analyzing millions of matches, our proprietary model isolates the impact of specific item purchases on a team's win probability, filtering out confounding variables like player skill and game state. This allows players to discover meta-breaking item combinations and understand which choices genuinely enhance their chances of victory. Furthermore, our match analysis tool identifies critical "Points of Interest" within replays, highlighting gameplay moments where a player significantly influenced the win probability, thereby accelerating skill development.

Target Audience

The primary users are competitive League of Legends players, ranging from aspiring amateurs to professional esports teams, seeking data-driven insights to optimize itemization and improve in-game decision-making.

Features

  • Win Probability Added (WPA) metric for objective item and build performance evaluation, debiased against player skill and game context.
  • Proprietary win probability model trained on extensive League of Legends match data, achieving state-of-the-art accuracy.
  • Item analytics interface displaying WPA alongside occurrence data, filterable by champion, matchup, role, patch, and region.
  • Build analytics module that identifies high-impact item sequences and synergies based on WPA and occurrence.
  • Match analysis tool that pinpoints "Points of Interest" (POIs) in replays, correlating player actions with win probability shifts.
  • Support for Ranked Solo/Duo, Flex, and Normal Draft game modes.
  • Integration with Riot Games API for direct account linking and data import.
  • Data segmentation by patch, allowing for analysis of meta shifts and item viability over time.
This profile is AI-generated and may contain inaccuracies.