The reference point argument is as follows: do not compute odds from the vantage point of the winning gambler (or the lucky Casanova, or the endlessly bouncing back New York City, or the invincible Carthage), but from all those who started in the cohort. Consider once again the example of the gambler. If you look at the population of beginning gamblers taken as a whole, you can be close to certain that one of them (but you do not know in advance which one) will show stellar results just by luck. So, from the reference point of the beginning cohort, this is not a big deal. But from the reference point of the winner (and, who does not, and this is key, take the losers into account), a long string of wins will appear to be too extraordinary an occurrence to be explained by luck. Note that a “history” is just a series of numbers through time. The numbers can represent degrees of wealth, fitness, weight, anything.
Taleb, Nassim. The Black Swan (p. 119). Penguin Books Ltd. Kindle Edition.
The way to avoid the survivorship bias is to look at all who started in the cohort. Don't just look at the winners but at he loser as well. So, when you want to evaluate if a particular decision is good, look at all people who made the decision—not just at the ones who made the decision and succeeded. For example, when you wanna decide about whether to go on a keto diet, look for data where they take a large group of people as look at how it went (don't just watch this one keto youtuber). Or another instance, it's more relevant. When you see someone who is successful in an area and want to emulate them, stop. Before you decide to do what he did look at a greater sample of people who followed a similar behavior in that area and look at their outcomes. Maybe he's just one of the lucky ones who succeeded. Don't forget that those who are hidden, those who we don't see. The bigger the sample, the more extravagant the winners will be. This is exactly the way to notice the hidden. Look at the whole sample (the base rates). Ok, so this is another way to fight the survivorship bias (add it there earlier).