Should "win limits" or "prize targets" become a part of responsible gambling

Should “Win Limits” Become a Part of Responsible Gambling?

Presented by Doug WalkerCollege of Charleston

New Horizons in Responsible Gambling ConferenceFebruary 1-3, 2016

Vancouver, B.C., Canada

Win Limits - New Horizons 3

“Responsible gambling”• Strategies to prevent gambling disorders– Akin to limits for low-risk alcohol consumption

(Currie et al. 2008)• A focus on self-imposed gambling limits…– Setting a monetary loss or deposit limit– Limiting time spent gambling

• Time per session• Frequency of sessions



“Responsible gambling”• “Win limits” haven’t been

mentioned in academic literature until recently– The Everything Casino Gambling

Book: Feel Confident, Have Fun, and Win Big! (2004)

– Yet, “stop when you’re ahead” seems like obvious advice

American Gaming Assoc. (2003)• Four key characteristics of responsible

gaming– Responsible gamers understand that

gambling by its nature entails risk and that the odds of winning are with the house

– Responsible gaming is done socially, with family, friends or colleagues

– Responsible gaming is done for limited amounts of time, both in frequency and duration

– Responsible gaming always has predetermined acceptable limits for losses


A typical casino visit• Consider a “responsible gambler”– Player starts with $200 chips and loss limit– Player plans to stop gambling after 2 hours, or

until they’ve lost budgeted $200– Responsible gambler may be likely to lose all

budgeted money at the casino• Former title: “How do casinos make

money?”


Intro to win limits• Commitment to stopping gambling after winning a

certain amount– “Prize target” or “prize cash-out point” may be better

names• Decreases expected loss from gambling

– effectively reduces time spent gambling• Use of win limit would result in higher % of people

leaving casino as winners– Relative to other betting limits used alone– And when used with other betting limits


Probability distribution, roulette (house advantage 5.26%)

Source: Hannum & Cabot (2005, p. 22)


Players’ loss and win limits

loss limit

win limit

-5%


Simulated slot machine• Slot machine– $1 per play, single line– 6 seconds per play– Random number generator,

0.000-1.000– Player’s expected value

is -0.05

Random Number NetPayoffMinimum Maximum

0.00000 0.75000 $ (1)0.75001 0.90000 $00.90001 0.97000 $10.97001 0.99897 $200.99898 0.99997 $450.99998 1.00000 $160

Overall expected value: $ (0.05)


Simulated betting rules– Simulated player details

• Each run includes 900 players• Each player can do 5,000 spins, if no limits set• Always adhere to betting limits

– Simulated self-imposed betting limits[1] No win limit or loss limit (5,000 spins; 8.33 hrs of play)[2] Time limit of 1 hour (at 6 seconds per play = 600 plays)[3] $100 loss limit[4] $100 loss limit; $100 win limit[5] $100 loss limit; $100 win limit, “going down”[6] $100 loss limit; $200 win limit[7] $100 win limit


Simulation

# Winners(% Chance of Winning)

Average$ Result

Minimum $ Result

Maximum$ Result

Average Time Played

(# Plays a)

Maximum Time Played

(# Plays a)

Minimum Time

Played(# Plays a)

1 No win or loss limits (5,000 spins; 8.33 hrs. of play )

159 (17.6%) $ (251) $ (843) $ 419 8.33 hrs. (5,000)

8.33 hrs. (5,000)

8.33 hrs. (5,000)

2 Time limit of 1 hr. (6 sec./play)

315 (35.0%) $ (30) $ (220) $ 233 1.0 hr. (600) 1.0 hr. (600) 1.0 hr. (600)

3 $100 loss limit

66 (7.3%) $ (76) $ (100) $ 382 2.38 hrs. (1,429)

8.33 hrs. (5,000)

0.25 hr. (147)

4 $100 loss limit; $100 win limit

275 (30.6%) $ (35) $ (100) $ 162 1.13 hrs. (677)

4.33 hrs. (2,595)

0.13 hr. (78)

5 $100 loss limit; $100 win “down”

286 (31.8%) $ (35) $ (100) $666 1.22 hrs. (730)

8.33 hrs. (5,000)

0.07 hr. (41)


135 (15.0%) $ (53) $ (100) $ 254 1.81 hrs. (1,084)

7.46 hrs. (4,478)

0.26 hr. (156)

7 $100 win limit

435 (48.3%) $ (153) $ (858) $ 186 5.23 hrs. (3,135)

8.33 hrs. (5,000)

0.14 hr. (81)

Simulation results summary 900 players, up to 5,000 spins each,

6 sec./play


Simulation


Average$ Result

Minimum $ Result

Maximum$ Result

Average Time Played

(# Plays a)

Maximum Time Played

(# Plays a)

Minimum Time

Played(# Plays a)


159 (17.6%) $ (251) $ (843) $ 419 8.33 hrs. (5,000)

8.33 hrs. (5,000)

8.33 hrs. (5,000)


315 (35.0%) $ (30) $ (220) $ 233 1.0 hr. (600) 1.0 hr. (600) 1.0 hr. (600)

3 $100 loss limit

66 (7.3%) $ (76) $ (100) $ 382 2.38 hrs. (1,429)

8.33 hrs. (5,000)

0.25 hr. (147)


275 (30.6%) $ (35) $ (100) $ 162 1.13 hrs. (677)

4.33 hrs. (2,595)

0.13 hr. (78)


286 (31.8%) $ (35) $ (100) $666 1.22 hrs. (730)

8.33 hrs. (5,000)

0.07 hr. (41)


135 (15.0%) $ (53) $ (100) $ 254 1.81 hrs. (1,084)

7.46 hrs. (4,478)

0.26 hr. (156)

7 $100 win limit

435 (48.3%) $ (153) $ (858) $ 186 5.23 hrs. (3,135)

8.33 hrs. (5,000)

0.14 hr. (81)


6 sec./play


$100 loss limit simulation• If everyone adheres, only 7% of

players leave casino as winner• Average loss using this strategy is

$76


Simulation


Average$ Result

Minimum $ Result

Maximum$ Result

Average Time Played

(# Plays a)

Maximum Time Played

(# Plays a)

Minimum Time

Played(# Plays a)


159 (17.6%) $ (251) $ (843) $ 419 8.33 hrs. (5,000)

8.33 hrs. (5,000)

8.33 hrs. (5,000)


315 (35.0%) $ (30) $ (220) $ 233 1.0 hr. (600) 1.0 hr. (600) 1.0 hr. (600)

3 $100 loss limit

66 (7.3%) $ (76) $ (100) $ 382 2.38 hrs. (1,429)

8.33 hrs. (5,000)

0.25 hr. (147)


275 (30.6%) $ (35) $ (100) $ 162 1.13 hrs. (677)

4.33 hrs. (2,595)

0.13 hr. (78)


286 (31.8%) $ (35) $ (100) $666 1.22 hrs. (730)

8.33 hrs. (5,000)

0.07 hr. (41)


135 (15.0%) $ (53) $ (100) $ 254 1.81 hrs. (1,084)

7.46 hrs. (4,478)

0.26 hr. (156)

7 $100 win limit

435 (48.3%) $ (153) $ (858) $ 186 5.23 hrs. (3,135)

8.33 hrs. (5,000)

0.14 hr. (81)


6 sec./play


$100 loss, $100 win limit simulation

• If everyone adheres, 30% of players leave casino as winner– 4x as many as with loss limit alone

• Average loss using this strategy is $35– ½ as much as with loss limit alone


Simulation


Average$ Result

Minimum $ Result

Maximum$ Result

Average Time Played

(# Plays a)

Maximum Time Played

(# Plays a)

Minimum Time

Played(# Plays a)


159 (17.6%) $ (251) $ (843) $ 419 8.33 hrs. (5,000)

8.33 hrs. (5,000)

8.33 hrs. (5,000)


315 (35.0%) $ (30) $ (220) $ 233 1.0 hr. (600) 1.0 hr. (600) 1.0 hr. (600)

3 $100 loss limit

66 (7.3%) $ (76) $ (100) $ 382 2.38 hrs. (1,429)

8.33 hrs. (5,000)

0.25 hr. (147)


275 (30.6%) $ (35) $ (100) $ 162 1.13 hrs. (677)

4.33 hrs. (2,595)

0.13 hr. (78)


286 (31.8%) $ (35) $ (100) $666 1.22 hrs. (730)

8.33 hrs. (5,000)

0.07 hr. (41)


135 (15.0%) $ (53) $ (100) $ 254 1.81 hrs. (1,084)

7.46 hrs. (4,478)

0.26 hr. (156)

7 $100 win limit

435 (48.3%) $ (153) $ (858) $ 186 5.23 hrs. (3,135)

8.33 hrs. (5,000)

0.14 hr. (81)


6 sec./play


$100 win limit simulation• If everyone adheres, almost 50% of

players leave casino as winner– 7x as many as with loss limit alone

• However, average loss using this strategy is $153– 2x as much as with loss limit alone

• Maximum loss is greatest of any, $850


Cumulative distribution functions (CDFs) for different betting rules

-$1,

199

-$1,

149

-$1,

099

-$1,

049

-$99

9-$

949

-$89

9-$

849

-$79

9-$

749

-$69

9-$

649

-$59

9-$

549

-$49

9-$

449

-$39

9-$

349

-$29

9-$

249

-$19

9-$

149

-$99

-$49 $1 $5

1$1

01$1

51$2

01$2

51$3

01$3

51$4

01$4

51$5

01$5

51$6

01$6

51$7

01$7

51$8

01$8

51$9

01$9

51$1

,001

$1,0

51$1

,101

$1,1

51

0%

20%

40%

60%

80%

100%

5000 spins 1 hr time $100 loss $100 loss, $100 win

Player's Monetary Result

Cum

ulati

ve %

of P

laye

rs (w

ith th

at re

sult

or le

ss)

Vertical distance between 100% line and curve is the probability a player has a bet -ter monetary result than the amount indicated on the hor-izontal axis (greater distance is better) Vertical distance (height

under curve) is probability a player has that monetary result or less (lower height is better)


Massachusetts gamblers’ survey• Nelson et al. (2013) summarize results

from a 2012 survey of Bay State residents– Currently working with group on analyzing

survey data• 273 of 511 respondents were past-year

gamblers– These respondents were asked about their bet-

limiting behavior, etc.


Who sets betting limits?• 83% usually set a loss limit– 80% of those adhere or never reach limit

• 25% usually set a win limit– 60% of those adhere or never reach limit


Survey question categories• Demographics (sex, race, age, marital status, education employment,

household size & income)• Leisure activities enjoyed over last 12 months• Types/amount of advertising seen for gambling• Gambling attitudes and beliefs• Gambling frequency, types of gambling, past year• Wager size, loss size over past year• Where you’ve gambled during past year• DSM disordered gambling criteria• Betting limit setting, adherence• When you started gambling, have you sought help, etc.• Familiarity with help for gambling problems• Drinking habits, drug use, other psychological problems• Saving for retirement, non-retirement savings


Data, model• 247 survey respondents gambled in past 12 months

– 264 of 511 did not, and are excluded– Lottery-only players also excluded

• First looked at correlations between variables• Four logistic regression models

– Set, win/loss– Adhere, win/loss

• Preliminary results are shown– Adherence seems to be most interesting


Set loss limit?• Females 2.2 x more likely to set

loss limit, when controlling for other variables (e.g., age, household income, max. time spent gambling, etc.)


Adhere to loss limit?• Individuals reporting income of $50-

100K are 70% less likely to adhere to loss limits than those reporting higher income (i.e., >$100K)

• People who don’t go to the ATM while gambling are 11 x more likely to adhere to loss limits


Set win limits?• Females 90% more likely to set win limits• For each year older when first bet placed,

5% more likely to set win limit• Individuals reporting income of $20-50K

are 2.4 x more likely to set win limit than highest income category (i.e., >$100K)


Adhere to win limits?• Greater beliefs about “luck” in gambling

positively related to adherence to win limits– One-unit increase on this subscale, 17% more

likely to adhere (p=0.064)• Greater self-reported gambling problems

negatively related to adherence to win limits– One-unit increase on DSM criterion, then 70%

less likely to adhere


Omitted variables• Drinking and drug use omitted– comorbidity rate >70% with disordered

gambling• Anxiety and depression questions (4)

omitted– Some potential overlap with DSM criteria


Behavioral economics• “House money” effect– Difficult to adhere to win limits– Chasing losses

• Prospect theory– Impact of loss > impact of symmetric win

• Betting limits and breaks in play– Mental accounting– “Decision exercise”


Future research• Finish research using Mass. survey data• Experimental/lab research is needed– Real players

• Adherence to limits?– Real betting rules– Variable bets– Various slot machines types

Contact Information

Doug WalkerProfessor of EconomicsCollege of Charleston66 George StreetCharleston, SC 29424

[email protected]+1 (843) 953-8192

Papers on Win Limits simulationWalker, Litvin, Sobel, & St-Pierre (2015)

Setting win limits: An alternative approach to “responsible gambling”? Journal of Gambling Studies 31(3): 965-986.

Stopping when you’re ahead: Win limits and responsible gambling, Responsible Gambling Review 1(2): 1-9.

Survey dataNelson, Kleschinsky, LaPLante, Gray, Shaffer (2013)

A benchmark study for monitoring exposure to new gambling opportunities: Final report scientific content. Cambridge, MA: Division on Addiction.

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Should "win limits" or "prize targets" become a part of responsible gambling