In GS , all combats may have many result possibility . Many players reload the game to get better combat results . Since sometimes player reload as many as possible to get some extrem result & benefit from it , It has made it unfair for their opponent . It also made their opponent lose the interest in this great game . But until now It seems we still did not find a way to solve this problem .
After our team’s researching on this , we find an easy way to solve this by changing a game set up file as follows :
In “general.txt” file , there is a data named “ NUMBER_OF_BATTLE_ROLLS” . (We will brief it as“NOBR” ) . It is the rolls of each combat sothat to get an average combat result . At present this data is set as 3 & maxium 4.
To research about the result of increase the NOBR to 4 , we make a data test . The test object is three combats between Sub vs DD ; sub vs BB ; Luftwaffe FTRvs RAF FTR in turn 2( Sept 21st 1939). & the results are the loss from both side.
At first : We collect 30 times data when we set NOBR at 3 , then we get 180 original data . We calculate the data’s Average , Maxium, Minium , Range & Standard Deviation .

To compare with the above data , we increase the NOBR to 4 . Without any other change , we test it in the same above situation & collect another 180 original data .

To be clear to compare the data from the above two tests , we put them into one sheet as follows :

The statistic result shows that : when we increase the NOBR , the combat result’s range was quite reduced . & the possibility of the extrem result become rather rare .




Finally , we draw a conclusion that to increase the NOBR will effectively reduce the possibility of extrem combat result . This does work well not only in 3.2 but also in 3.1. So we suggest to increase the NOBR’s maxium to 9 in 3.2 . It will thoroughly solve the problem of reloading ! It will make players concentrate on the skill & strategy , not wasting time on reloading for extrem better combat result .
Then we can enjoy this great game in coming years .
CEAW-GS China team
Nov 8th 2015