"I ain't reading all that!" sure, but you'll miss out. Go straight to the Wojak map below to understand what the quadrants of the heatmaps correspond to.

I'm not sure if anyone has tried this approach to studying Martingale tendencies before, so I hope a few of you at least will understand my gibberish (lol). This section was made possible by the new heatmap chart type from Flipside, so shout out to them for that.

Below you'll find 6 heatmaps, 2 for each gambler profile. The ones on the left are ROI heatmaps (the values they contain are the average ROIs for each square or (x,y) bin), and the ones on the right are gambler concentration heatmaps (the values are the number of gamblers for each (x,y) bin).

Why is there a need for 2 heatmaps for each profile? To gauge the significance of the average ROI values in the left heatmap, and also for the sake of curiosity. An average ROI from a sample of 5 gamblers will be much less significant than an average ROI from a sample of 300 gamblers. That way, we know which parts of the ROI heatmap we must take with a grain of salt, ya dig?

Now onto the x and y axes, what do they represent?

The x axis is the correlation between a gambler's PnL and the size of their bets, when the PnL goes up.
The y axis is also the correlation between a gambler's PnL and the size of their bets, but when the PnL goes down.

So why split the data series that way? Because remember, a gambler shows Martingale tendencies when they increase their bet size (as a % of their portfolio) when they win, and don't cut it or even increase it more when they lose. So we need to isolate the cases where they win and lose, and study them separately.

Here are a few examples:

x = 1 and y = 1: the gambler bets more when they win and less when they lose, every time.
x = 1 and y = 0: the gambler bets more when they win every time, and keeps betting the same when they lose.
x = 1 and y = -1: the gambler bets more when they win and more they lose, every time (the absolute degen).
x = -0.4 and y = 0.3: the gambler tends to bet less when they win, and also less when they lose: a more conservative and wise gambler.

So the takeaway is that 1 and -1 are extreme values showing a systematic behaviour. Between the two, it's more of a tendency to behave like so (not every time).

chainrunner_