Jan 22, 2024

How Mais Esports uses PandaScore data

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Ever wondered what the secret is behind Mais Esports’ data excellence? PandaScore is proud to be powering the largest esports news portal in Brazil, contributing to Mais Esports' prominence in the competitive gaming landscape 🐼. Committed to keeping their audience up-to-date on all things esports, Mais, with the aid of PandaScore data, delivers the latest updates in the competitive scene, comprehensive match schedules, and in-depth post-game analyses.

Their dedication to the competitive scene has brought them a staggering reach, with over 3.2 million monthly page views and over 500k unique users each month. These impressive figures highlight the platform as a go-to destination for fans seeking an informative and engaging esports experience.

Mais Esports utilises PandaScore’s statistical data from the Historical plan for three popular esports titles: League of Legends, Counter-Strike, and Valorant.

“PandaScore was a very important tool for the digital transformation carried out at Mais Esports in recent years.” Rafael Augusto, CTO Mais Esports.

The platform’s first PandaScore subscription dates back to September 2021, marking an impressive two years of collaboration. As we raise a virtual toast (🥂 clink) to this milestone, it’s a great time to reflect on how Mais Esports uses PandaScore data to enhance the user experience on their platforms.

How Mais Esports uses PandaScore data

Mais Esports delivers a deep insight into a match before and after it begins, empowering users to be more informed of the win potential of a team. Let’s explore how Mais leverages PandaScore’s wealth of data to curate an immersive experience for esports enthusiasts.

Pre-game data

Employing PandaScore's dedicated team stats endpoints, Mais Esports has crafted detailed head-to-head opponent comparisons for upcoming League of Legends matches. These head-to-head stats showcase in-game team performance, detailing the percentage of games in which each team secured a first Tower, Dragon, and Baron, the average number of champion kills, structures destroyed, and monsters slain.

These statistics are an interactive element on the platform, allowing users to compare team performance by the number of games and by blue/red sides in-game. With these dynamic statistics, users can gain insights into each team’s unique playstyle based on their recent performance in Summoner’s Rift.

League of Legends pre-game team statistics.

As well as head-to-head team statistics, Mais Esports highlights the key performance metrics of the rosters expected to play for their respective teams. The head-to-head player statistics provide users with a means to compare player performance for opposing lanes. The players’ performance is represented by their average KDA, creep score, and vision across the map, serving as valuable indicators of player gameplay dynamics.

League of Legends pre-game player head-to-head statistics.

Collaborating with Mais Esports, PandaScore happily embraced the opportunity to enhance the existing player and team statistics. We prioritise customer feedback, and this collaboration allowed us to deliver innovative data tailored to meet customer needs.

“PandaScore has good tools to help developers consume the product, our teams frequently communicate to suggest improvements and new features in the data and documents.” Rafael Augusto, CTO MaisEsports.

Inspired by Mais Esport's feedback, our dedicated stats endpoints have evolved. Now, users can filter team and player statistics by a given number of games or by team side (blue or red for LoL and radiant or dire for DotA2). These newly introduced filters allow users to gain a granular understanding of player and team performance and transform raw data into statistical insights.

Post-game data

Once a game has finished, Mais Esports presents users with a comprehensive post-game breakdown of team and player performance. This encompasses the team's overall scores, objectives secured, picks, bans, KDAs, and gold earned, as well as player champion level, summoner spells, KDAs, damage dealt, creep score, warding score, and items purchased. Mais employs tags to spotlight standout contributors in-game, revealing the player that secured first blood and which players dominated in categories such as damage dealt, gold earned, and creep score throughout the game.

Post-game League of Legends statistics.

Across four Historical plan videogames, PandaScore provides over 170 unique statistics and dedicated stats endpoints for player and team performance. The wealth of available data opens endless possibilities for development, paving the way for continued innovation in esports. Curious about what PandaScore data could do for you? Schedule a free call today.

Useful Links

Mais Esports

Esports portal | Twitter


Documentation | Statistics overview | Pricing

If you have any questions, you are welcome to join our (p)awesome customer and developer slack.