Assuming the percentage spread is determined linearly, i.e. there is an equal chance of 9%, 10%, ....18% then I realise that in the majority of cases the winner will inflict more casualties than it receives. However, there still is a good spread of occurrences where the loser can outscore the winner, i.e. all the combinations where the winner is in the range 9-14% and the loser is in the similar range.TheGrayMouser wrote:Ah then a shorter answer would have been more effcient
Yeah the loser can inflict more "casualties", the loser as being defined by the BG that rolled less hits The combat charts show it well but the winner might , for example be the one that got say 3 hits and thus will inflict 9-18% causalties, the loser who got 2 hits 5-14%. A 5% differential, worst case scenario
Surely a system that allows, using the example above, a winning side to inflict 9% casualties on the opponent and the losing side to inflict 14% casualties on the winner is flawed and needs a rethink.
Once the "winner" has been determined then constraints must be put on the loser to ensure that the casualties they inflict is less than the casualties inflicted by the winners.
At present it seems that too many random factors are being used in determining the result. A random dice to determine who wins and a random determination of casualties, which could, at least in my mind, override the decision of who won. This may be why there is some adverse feedback that the results are too random.
I certainly believe that that random elements are required to determine results, but some constraints need to be applied too. Constraining the losers maximum percentage to less than the winners percentage roll, is one way to ensure that strange results are minimised.
Obviously, there are a number of assumptions in what I've written, e.g. linear spread, no current constraints, etc. so I'd welcome feedback from the technical community that know how it works behind the scenes as well as thoughts from all others.