RESEARCH QUESTION
Can setting a ‘win limit’ be an effective method for responsible gambling?
PURPOSE
Pre-commitment strategies, such as setting and adhering to monetary loss or time limits on gambling, have gained attention as an important responsible gambling initiative. However, no studies had previous investigated the notion of ‘‘win limits’’ as a component of responsible gambling. The purpose of the present study was to provide a simulation to illustrate the potential benefits of win limits, in combination with and in contrast to loss limits and time limits, for the advancement of responsible gambling practices.
HYPOTHESIS
A self-imposed win limit would reduce the average loss.
PARTICIPANTS
None.
PROCEDURE
A slot machine simulation was developed with a random number generator used to determine the results of the slot machine spin. The simulated slot machine required a $1 bet, and allowed only one play per spin. The overall expected payout from the slot machine was 95% (i.e., an average loss of $5 for every $100 bet). Each run of the simulation had 60 individuals playing slot machines over each of 15 rounds for each of seven scenarios. The simulation allowed each player to make up to 5,000 slot machine spins (i.e., about 8.33 h of play if each spin takes 6 s) if there was no limit set to stop the player sooner. The simulations varied based on the limits imposed (i.e., combinations of time limits, loss limits and/or win limits).
MAIN OUTCOME MEASURES
Time spent gambling, gambling losses, and gambling winnings were recorded.
KEY RESULTS
In the 1st scenario (i.e., no limits), 18% won money, the average result was a loss of $251. The best result was a win of $419 and the worst was a loss of $843. In the 2nd scenario (i.e., time limit of 1 h), 35 won, the average result was a loss of only $30, and both minimum and maximum results were smaller than in scenario 1. Among all the simulations, this one yielded the smallest average loss because it limited the number of plays the most of any simulation. For scenario 3 (i.e., $100 loss limit), no player could lose more than $100. There were only 7% winners, the average loss was $76, and the average time spent gambling was 2.4 h. In scenario 4 ($100 win limit and $100 loss limit), players stopped gambling when they were up or down by $100. In this scenario, 31% won, the average loss was $35, the maximum gain was $162, and the average length of play was 68 minutes. For scenario 5 (i.e., $100 loss limit and $100 win ‘down’), players stopped when winnings increased to $100 or if the limit is reached on the way down. For example, if a player had $80 and won a $45 jackpot, the balance would be $125. Under this simulation, the player kept playing until the balance fell to $100. The scenario resulted in a 32% win rate, higher average winnings than scenario 4, and an average 0f 73 minutes of play. For scenario 6 (i.e., $100 loss limit and $200 win limit), 15% won, the average loss was greater than scenario 4, and the average play time was 1.8 h. For scenario 7 (i.e., $100 win limit), 48% won, the average loss was $153, and the average playing time was 5.2 h.
LIMITATIONS
Simulations were only run for slot machine gambling and results may not generalize to other types of gambling. Additional research with human participants is needed.
CONCLUSIONS
The results suggest the win limit results in improved player performance and reduced casino profits. Additional research is needed to determine whether win limits could be a useful component of a responsible gambling strategy.
