American-Hungarian Physicist Key in Answering This 150-Year-Old Game of Skill

Relationship with the public: A system devised by an American-Hungarian physicist may offer a solution to a controversial question that has been the subject of fierce legal battles over how to distinguish between games of skill versus games of chance.

New Delhi: A system devised by an American-Hungarian physicist may offer a solution to the contentious question that has been the subject of a fierce legal battle over how to differentiate between games of skill versus games of chance.

In a recently released report, Delhi-based policy think tank Evam Law & Policy has come up with a system of skill rating based on the ELO system for chess developed by American-Hungarian physicist Arpad Elo.

Since games of skill were exempted by the Public Gambling Act in 1867, several legal battles have been fought in India over defining games of skill. In 1957 the Supreme Court ruled that crosswords were a game of skill. As the popularity of online gaming has increased over the years, it has become the subject of serious legal battles. Some states like Karnataka, Tamil Nadu and Kerala brought laws to ban online skill games for money, but their state high courts struck them down.

Evam has come up with a new framework called Skill-Based Matchmaking (SBMM), which enables a clear distinction between games of skill and games of chance. This method pairs players based on their skill level to ensure balanced and competitive matches.

The SBMM is inspired by the ELO system devised by Arpad Elo for rating chess players. The ELO system, adopted in 1970, removed subjective and arbitrary elements from chess and introduced a statistical model that operated solely on the results of games played.

For example, if there was an ELO system in the 1920s, the Indian chess prodigy Mir Sultan Khan, who fell into obscurity despite winning the British Chess Championship three times, would have found his rightful place in the chess world. SBMM also incorporates elements of newer models such as Glico and TrueSkill to provide enhanced accuracy and versatility.

Shashank Reddy, founder of Evam Law & Policy, explains, “Implementing the SBMM requires a well-designed skill-rating model that combines relative calculations, average value representation, and quick access to ensure fair and engaging gameplay. Considers factors such as convergence. The balance between accuracy and simplicity is important in selecting a skill-rating model that is both effective and user-friendly.

He further added, “In the context of the Indian RMG sector, from a legal perspective, implementing the SBMM helps separate the game of skill from the game of chance. Secondly, from a policy perspective, the SBMM is essential to promote fair and responsible gaming practices in online RMGs.