The simulated, skilled player does not claim to provide and is not intended to provide optimal play – that challenge remains to be pursued by the millions of players out there. It is intended to provide a measureable contrast against the unskilled players.
Testing a game in this way can potentially generate one of two conclusions:
- The skilled player outperforms the unskilled players, earning more points or winning more match-ups, and the degree of out-performance is measurable and demonstrable to be statistically significant. This clearly indicates that the outcomes of the game reflect the knowledge and skill of the participants.
- The skilled player either does not outperform the unskilled players or does not outperform the unskilled players by a large enough degree that statistical significance can be established. This conclusion admits three possible interpretations – either the game does not have a measurable skill element, the employed algorithm is not sufficiently skilled, or the amount of data is insufficient to demonstrate a clear difference in skill.
Summarizes the results
When testing concludes, the client receives an official GLI report, summarizing the rules of the game format, the testing conducted, and the testing results. It is important to understand that GLI certifications do not contain legal opinions or issue any statements regarding the legality of fantasy sports. However, the GLI report is a critical component of any legal analysis that may subsequently be conducted by private sector lawyers, regulators or other government officials. Certifications also provide valuable information to consumers to create transparency for a fantasy sports service or certify that games meet appointed technical standards. Moreover, GLI's findings provide a clear summary of the technical testing results, which are intended to examine the role of knowledge and skill.
Before analysis can begin, the client should be prepared to list exactly how the athlete statistics are used to determine the final outcome of the fantasy game and provide official historical data of all statistics used. The amount of data needs to be sufficient so that a skill algorithm will have enough data to make good decisions.
Noah B. Dean, PhD, is Director of Mathematics at Gaming Laboratories International, LLC (GLI®). His expertise lies in the fields of discrete probability and stochastic processes. Before joining GLI®, he taught at the University of Maine at Machias, developing curriculum and teaching several courses in math and statistics. For more information, visit www.gaminglabs.com.