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Table 2 Gambling behavior in users who did and did not exceed deposit limits

From: Virtual harm reduction efforts for Internet gambling: effects of deposit limits on actual Internet sports gambling behavior

   Fixed-odds (n = 46267)   Live-action (n = 32277)  
Gambling behavior
measure
Users who
did exceed limits (n = 159)
Users who
did not exceed limits (n = 46108)
Difference
test
Users who
did exceed limits (n = 149)
Users who
did not exceed limits (n = 32128)
Difference
test
Percentage of active
betting days
Mean (SD) 21 (20) 25 (29)   26 (28) 31 (37)  
  Median 14 13   16 11  
  Log Mean (SD) -- -- t = -1.90 -- -- t = -1.71
Average number of
bets per active
betting day
Mean (SD) 7 (13) 4 (7)   8 (14) 4 (5)  
  Median 3 2   4 3  
  Log Mean (SD) 0.60 (0.40) 0.44 (0.32) t = 6.12* 0.68 (0.42) 0.46 (0.34) t = 7.98*
Average size of bet
in Euro
Mean (SD) 25 (55) 11 (30)   27 (41) 11 (25)  
  Median 8 4   12 4  
  Log Mean (SD) 0.96 (0.60) 0.67 (0.51) t = 7.14* 1.07 (0.58) 0.65 (0.53) t = 9.59*
Categorized percentage of losses        
   Overall winners n (%) 26 (16.4) 6755 (14.7)   25 (16.8) 6924 (21.6)  
   Lowest percentage of losses n (%) 59 (37.1) 12367 (28.8)   73 (49.0) 10548 (32.8)  
   Intermediate percentage of losses n (%) 56 (35.2) 19338 (41.9)   40 (26.8) 9533 (29.7)  
   Highest percentage of losses n (%) 18 (11.3) 7648 (16.6) Chi2 = 10.91* 11 (7.4) 5123 (15.9) Chi2 = 20.58*
  1. * p < .05.