Table 1.

A matrix showing the OR of heavy play between each week preregulation and postregulation using dataset 1

	0	1	2	3	4	5	6	7	8	9	10
−1	0.96	0.94	0.95	0.91	0.99	0.95	1.03	1.01	1.15	1.22	1.56
−2	0.89	0.88	0.88	0.84	0.92	0.89	0.96	0.94	1.07	1.13	1.46
−3	1.03	1.01	1.02	0.97	1.06	1.02	1.10	1.09	1.24	1.31	1.68
−4	0.78	0.77	0.77	0.74	0.80	0.77	0.84	0.82	0.94	0.99	1.27
−5	0.71	0.70	0.70	0.67	0.73	0.71	0.76	0.75	0.86	0.90	1.16
−6	1.00	0.99	0.99	0.95	1.03	1.00	1.08	1.06	1.21	1.27	1.64
−7	0.77	0.75	0.76	0.72	0.79	0.76	0.82	0.81	0.92	0.97	1.25
−8	0.79	0.78	0.78	0.75	0.82	0.79	0.85	0.84	0.96	1.01	1.29
−9	0.76	0.74	0.75	0.72	0.78	0.75	0.81	0.80	0.91	0.96	1.23
−10	0.68	0.67	0.67	0.64	0.70	0.67	0.73	0.71	0.81	0.86	1.10
−11	0.65	0.64	0.64	0.61	0.67	0.64	0.69	0.68	0.78	0.82	1.05

Each column represents a different week postregulation; each row a different week preregulation. For example, the cell located at (−1,0) compares the odds of heavy play 0 weeks postregulation (that is the week spanning 1–6 November 2019) against the odds of heavy play 1 week preregulation (that is the week spanning 25–31 October 2019): its value (0.96) represents a situation in which individuals are 0.96 times as likely to engage in heavy play in week 0 when compared with week −1. All comparisons are significant at the P < 0.001 level using Fisher’s exact test (two-sided).