Big Data? Accessing and working with data collected through online gambling platforms

Transcription

1 Big Data? 7 th April 2016 Accessing and working with data collected through online gambling platforms Dr Tilman Lesch Tilman.Lesch@psych.ubc.ca

2 Agenda Motivation to work with online data Previous player tracking research The PlayNow.com dataset Bet-by-bet analysis Identifying at-risk play Challenges & Benefits 2

3 Agenda Motivation to work with online data Previous player tracking research The PlayNow.com dataset Trial-by-trial analysis Identifying at-risk play Challenges & Benefits 3

4 Motivation to study online gambling Rapid growth since early 2000s Ubiquitous 24/7 availability Different types of players Much easier and quicker feedback to changes in regulation Easier access to playing data Easy Implementation of additional measures such as questionnaires, etc. possible 3

5 Areas of online gambling research 1. Descriptive analysis of online gambling Prevalence study Player segmentation Comparative analysis within individuals, e.g. daily, monthly, seasonal, yearly playing patterns 2. Identification of at risk players (e.g. Harvard s Transparency Project) Personalized interventions Timely interventions Predictive Analytics Determine likelihood of problem gambling event, e.g money upload, self exclusion, loss chasing Confirmation of theory and laboratory findings in naturalistic data 4

6 DSM-5 Diagnostic Criteria for Gambling Disorder Development of Tolerance Symptoms of withdrawal Unsuccessful control of play Preoccupation with gambling Gambling when feeling distressed Loss Chasing Concealment of play Jeopardize significant relationship, job, or educational or career opportunity Bailout through others 5

7 Agenda Motivation to work with online data Previous player tracking research The PlayNow.com dataset Trial-by-trial analysis Identifying at-risk play Challenges & Benefits 7

8 The Transparency Project (Cambridge Health Alliance) Data Set Daily aggregates from bwin based in Austria, website world wide available ( ) Games Types: sports betting (most), internet poker, casino Measures Daily aggregates of number of bets, bets per day, Euros per bet, total wagered, net loss, percent lost Number of active days before the first deposit was made Duration of play, days active Monetary deposits to, and withdrawals from player s account Trajectory of first month wagers Reason for account closure 7

9 The Transparency Project Assessing the Playing Field: A Prospective Longitudinal Study of Internet Sports Gambling Behavior (LaBrie et al. 2007) Summarize first 8 months of play for new subscribers Comparison of fixed odds and live-action betting behaviour Analyses: (1) cohort characteristics; (2) cohort gambling behaviour; and (3) the behaviour of heavily involved bettors (Top 1%)

10 The Transparency Project Population trends in Internet sports gambling (LaPlante et al. 2008) Gambling behaviour of new subscribers playing either fixed-odds or live-action sports betting over 18 month. Sum of bets (18 months) Sum of bets (first 90 days) 9

11 The Transparency Project Population trends in Internet sports gambling (LaPlante et al. 2008) Most Involved Bettors (Top 1%) Sum of stakes (8 months) Sum of stakes (first 90 days) 10

12 The Transparency Project How do gamblers start gambling: identifying behavioural markers for high-risk internet gambling (Braverman & Shaffer, 2010) n=15 n=22 n=115 n=378 11

13 The Transparency Project Using Cross-Game Behavioral Markers for Early Identification of High- Risk Internet Gamblers (Braverman et al. 2013, similar: Gray et al. 2012) 12

14 Agenda Motivation to work with online data Previous player tracking research The PlayNow.com dataset Trial-by-trial analysis Identifying at-risk play Challenges & Benefits 14

15 The PlayNow Platform The online gambling platform from BCLC for British Columbia and Manitoba 6 categories of gambling: Lottery KENO Casino Sport Poker Bingo 14

16 The data measures and metrics xxx

17 The data measures and metrics xxx

18 The data measures and metrics Date &Timing Customer ID xxx Net Loss Bet Amount

19 Percentage of Players in each Category Number of Bets placed in each Category Social Bingo Sports Casino Lotto June 2015 only 18

20 Top 5% of day users - Ecasino Median Values Ecasino Top 5% Other 95% # Players # Days gambled per month 27 4 # Bets placed Total amount wagered Amount per bet Net Loss # Different games 24 5 The Top 5% of day users show on average at least 10 fold the gambling engagement than the remaining 95% of users Despite this, their median amount per bet is slightly lower 19

21 Ecasino total wagered by Product Type Ecasino number of bets placed by Product Type Table Probability Virtual Poker Slots 20

22 Intermediate Summary I Majority of people access PlayNow to play Lotto Large majority of bets and wagers placed in the Ecasino Heavy ecasino users (Top 5% of day users): play almost every day and 5x more different games place more than 25x the number of bets with 15x the wagers accumulate 10x the loss. Slot machines are the most popular casino games The bet sizes on the tables games are considerably higher compared to the rest 21

23 Agenda Motivation to work with online data Previous player tracking research The PlayNow.com dataset Bet-by-bet analysis Identifying at-risk play Challenges & Benefits 23

24 # of Bets placed # Bets placed by Hour of Day (Not) At-Work plateau end of work effect after-breakfast effect Hour of day 23

25 Behavioural markers of online gambling I Betting Speed or the PRP ( Post-Reinforcement-Pause ) for online gambling: Original definition of PRP : Fixed schedules produce "post-reinforcement pauses" (PRP), where responses will briefly cease immediately following reinforcement, though the pause is a function of the upcoming response requirement rather than the prior reinforcement. Translation for online gambling: Time between one bet and the next bet within the same session. 24

26 Mean overall Betting Speed by individual 25

27 Mean Betting Speed difference between winning and losing by individual Zero Line (No Bias) Slower after Losses Slower After Wins >0: Slots: ~75% Tables: ~65% 26

28 Behavioural markers of online gambling II Loss Chasing: Definition of Loss chasing : increased bet sizes or prolonged betting after a series of losses in an attempt to win back funds (Lesieur, 1984; American Psychiatric Association, 2013). Translation for online gambling: 1. Increase of amount wagered throughout a gambling session (escalation) 2. Considerable deviation from average session length due to losses experienced during that particular session (persistence) 27

29 Distribution of amount wagered during session using correlation Decrease of wager Increase of wager Table Games only 28

30 Distribution of amount wagered during session using correlation Decrease of wager Increase of wager Slot Machines only 29

31 Intermediate Summary II Bet-by-bet analysis: Daily betting pattern: o After-Breakfast, After-Work effects and (Not) at-work plateau Betting Speed o Play on table games slower than slots machines o Difference in speed between winning and losing larger for slot machine play Loss Chasing o Almost uniform distribution of correlation for table games with negative skew suggests that loss chasing for some but not all o Tri-modal distribution of correlation for slot machine play 30

32 Agenda Motivation to work with online data Previous player tracking research The PlayNow.com dataset Trial-by-trial analysis Identifying at-risk play Challenges & Benefits 32

33 DSM-5 Diagnostic Criteria for Gambling Disorder Development of Tolerance Symptoms of withdrawal Unsuccessful control of play Preoccupation with gambling Gambling when feeling distressed Loss Chasing Concealment of play Jeopardize significant relationship, job, or educational or career opportunity Bailout through others 32

34 Identifying at risk player Loss Chasing Within one session via wager increases Across multiple session via average session length Development of Tolerance Progression of play over time Sudden changes in behaviour 33

35 Agenda Motivation to work with online data Previous player tracking research The PlayNow.com dataset Trial-by-trial analysis Identifying at-risk play Benefits & Challenges 35

36 Benefits Naturalistic data Confirm theory and lab findings Personalisation Real-time analysis Enrichment with more data (e.g. demographics, facebook) Only using data already/anyways collected Data only to get larger and richer 36

37 Challenges Translation of measures and interpretation Messy data, e.g. different categories, games, etc. Environmental/circumstantial factors of diagnosis Red flags likely going to differ between game types Privacy concerns Access to data Skill to analyse data Infrastructure to analyse data 35

38 Future Directions Personalisation, e.g. personal limits Real-time analysis Predictive analytics Take analysis offline (e.g. with loyalty cards) Combine online recording with questionnaires Analyse chats/ correspondence with patrons (NLP) 37

39 Questions? Thank you for your attention Dr Tilman Lesch Acknowledgements CGR Professor Luke Clark BCLC Dr Kahlil Philander Bradley Bodenhamer Michaela Becker 39

40 Open discussion Behavioural patters to look at: Big Wins Tolerance Streak effects?? Other areas: Credit card spending? Trading Banking 40

41 Thank you for your attention

42 Top 5% of day users - Overall Medium Values Overall Top 5% Other 95% # Players # Days gambled per month 24 7 # Bets placed Total amount wagered Amount per bet # Different categories 2 1 The Top 5% of day users show on average at least 10 fold the gambling engagement than the remaining 95% of users Despite this, their median amount per bet is lower

43 Betting Amount by Hour of Day Total amount wagered in Million CAD after-breakfast effect (Not) At-Work plateau end of work effect Hour of day

44 Cognitive Biases in Gambling A cognitive bias is a pattern of deviation in judgment and decision-making, whereby inferences about situations and other people may be drawn in an illogical fashion. Hot Hand Fallacy: fallacious belief that a person who has experienced success with a random event has a greater chance of further success in additional attempts. Illusion of Control: tendency for people to overestimate their ability to control events. Sequential/ Streak Effects: ( Gambler s Fallacy : mistaken belief that, if something happens more (less) frequently than normal during some period, it will happen less (more) frequently in the future - balancing). Cognitive distortions play an important role in the development and maintenance of pathological gambling.

45 A Public Health Approach to Gambling Harm Near-misses Impulsivity Gambler s Fallacy Illusory Control GAME GAMBLER Dopamine Brain structure GAMBLING ENVIRONMENT Korn & Shaffer 1999 Murch & Clark 2015 Gambling Venue Legislation

46 Goals for acquiring the PlayNow dataset Detect behavioural and cognitive biases in naturalistic dataset Describe the BC online gambling population Replicate the findings of the Transparency Project at Harvard Be the first research group looking at trial-by-trial online behaviour Identify individuals with symptoms of problem gambling based on their online gambling behavior

47 DSM-5 Diagnostic Criteria for Gambling Disorder A. Persistent and recurrent problematic gambling behavior leading to clinically significant impairment or distress Needs to gamble with increasing amounts of money in order to achieve the desired excitement. Is restless or irritable when attempting to cut down or stop gambling. Has made repeated unsuccessful efforts to control, cut back, or stop gambling. Is often preoccupied with gambling (e.g., having persistent thoughts of reliving past gambling experiences, handicapping or planning the next venture, thinking of ways to get money with which to gamble). Often gambles when feeling distressed (e.g., helpless, guilty, anxious, depressed). After losing money gambling, often returns another day to get even ( chasing one s losses). Lies to conceal the extent of involvement with gambling Has jeopardized or lost a significant relationship, job, or educational or career opportunity because of gambling Relies on others to provide money to relieve desperate financial situations caused by gambling. B. The gambling behavior is not better explained by a manic episode.

48 Big Wins: Case Study Overall: More than bets in June 2015 on 15 days and 52 different games Accumulated bets worth more than CAD Lost about about CAD over the course of June Big Win Session: 5h play on 9 different games Start: 9:40 pm; End: 2:40 am 2209 bets, every 8 seconds Accumulated bet amount: CAD Net win: CAD Big Win Big Win: At 00:27:10 bet 50$ and won CAD the next bet at 00:27:19 again 50$ 48