Rather, we should take real data...

Not quite. The idea is to see if the theory can convincingly explain fake data. If it can, it doesn't mean the theory is wrong, it just means your capacity to infer things from it is limited. Natural selection is interesting and useful, but it is not a reliable predictor in many cases. You routinely see people say, "The market must do X because of Y." If they could say basically the exact same thing about ~X, then it's a fake explanation; their theory really doesn't tell them what the market will do. If a theory can convincingly explain false data, you've got to be very cautious in using it to make predictions or claims about the world.

Conversely, theories with extremely high predictive power will consistently pass the test. If you used facts centered in physics or chemistry, a competent test-taker should always spot the false data, because our theories in physics and chemistry mostly have extremely precise predictive power.