If significance testing were a game, it would be dictated by chance and encourage researchers to cheat. A dominant rule would be that once you conduct a study, you go all in: you have one go at your one preregistered hypothesis — one outcome measure, one analysis plan, one sample size or stopping rule etc. — and either you win (significance!) or you lose everything. The game does not allow you to conduct a second study, unless you prespecified that as well, together with the first. Strategies that base future studies on previous results, and then meta-analyze, are not allowed. Honestly reporting the p-value next to your 'I lost everything' result does not help; that is like reporting the margin in a winner takes all game. In a new round you have to start over again. No wonder researchers cheat this game by filedrawering and p-hacking. The best way to solve this might be to change the game. Fortunately, this is possible by preventing researchers from losing everything and allowing them to reinvest their previous earnings in new studies. This new game keeps score in terms of $-values instead of p-values, and tests with Safe Tests.