This is an example of short term variance versus long term variance taken from Arnold Snyder. If you watch someone flip a coin ten times and it comes up heads seven times, that is a frequent occurrence within the realm of short term statistical probability.
But if you watch someone flip a coin 10,000 times and it comes up heads 7,000 times then either the coin or the coin tosser is crooked. The theoretical frequency of that occurrence is so infinitesimally small that it is a mathematical impossibility.
I keep stats on everything I play, put them on a spread sheet and use running totals. I always back up the theoretical with empirical results. I have one new progressive play that I've only found 53 playable numbers on. The theoretical for achieving my objective is 800 games. You can call 800 games the short term. You can call the 41,340 games total that I've played on the 53 plays the long term. I've averaged taking the jackpot off every 780 games. My shortest play was 6 games. My longest play was 5564 games. I took a beating on the play that went 5564 games. Out of the 53 plays I've had only 4 losing plays.
Should I pay attention to the one play where I got beat up? Or pay attention to the healthy profit I've averaged over the 53 plays. The short term beating is insignificant to me. It's the long term stats that I pay attention to.
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