My comment was not about how the game works, but rather how people "break the code" on how things work.
To take a non-game related example:
Scientists will use correlation as proof of causation and label things as "carcinogens". It is possible that (for example) lacking specific nutrients caused mice in a group to be more cancer prone, and that the foods tested were causing malnutrition. This would cause a correlation between eating huge amounts of the food and getting cancer, even if the food itself was not cancer causing.
Bringing this back to the game:
Attacking troops usually causes a loss of troops. If I track the losses and troops killed, they tend to be very close numbers. If I don't have access to the code, I could attribute the reward system to be either driven by my losses, or by the troops I've killed off, and the data might support either argument in 99% of my battles.
People need to be careful about concluding data proves a particular position. Often the data will support many different possible conclusions.
The best approach, barring asking the devs and getting inside information, is to gather data on as many factors as possible, then see which possibilities are ruled out. When someone insists that X causes Y, and the data doesn't support that conclusion, you can go back and check for causes of error in the data. Until you can resolve such a conflict though, you are compelled to conclude that the data doesn't support their position.
With respect to battling locations, there are numerous factors you can consider:
Information provided in the field manual.
Information provided in the forums by those with inside understanding. (Usually in the form of a negative. eg - This doesn't affect that.)
Cost of troops used.
Cost of troops lost on both sides of the battle.
Ratio of losses in each battle.
Food upkeep of forces in the battle / lost / ratio
Power of the forces
Active boosts and their sources
etc
Until you can rule something out as being irrelevant: track it. Track it well enough, and then test it.
My experience has been that it is exceedingly difficult to isolate a single factor, but with enough battles: the data should disclose the secrets.
You just need to be able to tell the difference between correlation and causation, and sometimes you can sift that out with testing.