The competitive environment of video games can take on new forms of participation. In addition to traditional esports tournaments, platforms are beginning to use performance data to allow regular players to compete without needing to join professional teams.
One such concept is Game Skill Monetization (GSM), a model that converts statistics gathered during matches into points that determine the winners of competitions.
A representative from Gamers Brawl, a platform using this system, explained how the technology works and the challenges of ensuring result fairness in an interview with Olhar Digital during the Brasil Game Show (BGS).
Unlike classic confrontations, participants do not necessarily have to play against each other. Each user plays their matches in a standard mode, while the platform tracks metrics such as kills, assists, accumulated gold, and captured objectives.
Using League of Legends as an example, the system takes into account different character roles. For instance, a support player is evaluated by different criteria than an ADC, as each position contributes to the team in a unique way. Ultimately, the statistics are converted into points used to determine the competition winner.
This approach allows players to participate in contests without abandoning familiar game modes. However, the use of individual statistics also involves difficulties, particularly concerning result manipulation.
Among the problems highlighted are the use of secondary accounts, profile sharing, and cheating software. To detect potential violations, anti-fraud systems can analyze performance history and look for unusual changes in player behavior. In this case, the technology employs machine learning and examines over 100 attributes to detect suspicious situations. A sudden and significant change in statistics, for example, could lead to the suspension of the competition for analysis.
Nevertheless, such monitoring does not completely eliminate the possibility of fraud and depends on adequate criteria to avoid unjustified penalties. The model also raises the issue of access to video game competitions. While the professional scene usually requires training, team participation, and constant dedication, performance-based competitions allow casual players to experience competitive dynamics using their own matches.
The concept still faces issues related to point balancing, fraud prevention, and comparing different playstyles. Nevertheless, applying statistics to create individual competitions demonstrates how data generated by video games can be used to develop new competitive formats beyond traditional championships.
