what does the f in f(M) = 10M(B+Is) stand for?
what does the f in f(M) = 10M(B+Is) stand for?
I think you guys must also take into account the battles themselves.
If I where to battle 100scavangers with 40HP dam 15-30 hit 60%
I would need >150 recruits to kill them all on the first shot
If I use 50 recruits and 60 bowmen, I prolly lose only my recruits and kill them in one shot without having as large as an army that we would need with only recruits.
Atleast this is what I have been using and I never lose my bowmen and only replace my recruits.
yes good points.. but I know too little to actually do that right now. I dont even know what accuracy stands for.. I mean if a unit has 60% acc does it mean that only 60% of the damage goes through every round?
and you can juggle your amount of recruits/archers in the battle sim to find a sweet spot where you minimize your casualties, just like you already figured out. for recruits there seems to be no drop off point where an additional recruit wont reduce casualties, but... after some point it becomes so small you dont have to care
I mean look at this. 100 recruits vs 50 scavengers
24 losses
200 recrutis vs 50 scavengers
23 losses
I have wondered about that. It makes no sense...
How come that it says 21 avg losses when I put 150 recruits vs 50 scavengers?
A note on accuracy: If I understand this correctly and if it is appliable to TSO (so far the simulations have been correct...), accuracy is the chance the the troop does max damage, otherwise it does min damage.
Could someone please verify that accuracy indeed means the chance for max dmg.
In shot, not reading all stuff - they do a lot! Especcialy if there are non first-strike enemys. They got best dmg done.
The use of all troop types is situational. In many cases, especially early on, there is no benefit to using better troops. If 200 recruits can kill the enemy in one round then replacing some of them with bowmen or militia will have no added benefit. However if 200 recruits take the battle into 2 rounds then replacing half of them with bowmen could do enough damage to end the fight in one round or leave fewer enemies to fight in round 2, hence reducing your own losses as long as you are sure to take along enough recruits to protect the bowmen. Replacing a few with cavalry could allow you to kill their archers before they hurt your troops, but if they have dogs could prove too expensive in losses to your own.
Metal Tooth (sector 8) is the first time you really need to consider whether it's worth sacrificing expensive troops to beat an enemy. If the simulators are right (they reset his hit points to max after each wave) then its completely impossible to win the battle with recruits since he is the first enemy to be attacked and his troops kill off 200 recruits before you can reduce him to 0 hit points. If they are wrong and his health does not reset to full after each attack it's only extremely slow to kill him with recruits. If the latter is true you have to decide whether all the horses needed for the cavalry you will lose are more important to you than the time it's going to take to grow and train the hundreds of extra settlers to send in recruit waves and the cost of three generals - assuming you have enough housing to build a full 3 waves of recruits. I'll have the cavalry before I have the population limit to build 600 recruits and I'd rather save the 500 gold needed for a 3rd general too. You might kill metal tooth with 2 recruit waves, but it's not guaranteed even if he heals nothing between attacks.
Only you can decide what your priorities are. If you set up your town so it produces horses quickly it'll be a lot less painful to lose some than if you have to wait an age for a single stable to produce the same number. How you use your precious building licences and which buildings you choose to upgrade will make these decisions unique for you. People can make suggestions but they may have a quite different setup to yours.
That seems to be the assumption used by the simulator at http://castleempiresim.com/
Since it appears to predict results accurately, it seems fair to assume that it is correct.