Release version of DeCoHde - Snake Edition.
Download Python version of DeCoHde here: DeCoHde Python version
Download executable version of DeCohde here (currently slightly bugged, fixes will be released when I find the time): DeCoHde executable version
Download the Visualizer tool here (only Python version available): Visualizer Python version
For more information on the release version, please read this post.
UPDATED POST AND SHEET. Hit Boxes are now correct!
This project could use a little help by other interested members of the community. If you are interested in helping, please check the spoiler below and drop me a PM.
DeCoHde 2.0 - Snake edition
In my never ending quest to finally shut down all discussions on this forum, I moved on to a new tool: Tank fight simulations for predicting the outcomes of a fight if it comes to raw AT performance. The little piece of code runs on Python since Excel quickly reaches its point of practicability. While it is not quite ready for a "real" simulation yet, I am finally on a level that is able to showcase a little bit of data.
What can this little tool do?
- simulate one tank shooting at another at a set distance (with correct accuracy and penetration calculation)
- angle the targeted tank (to simulate flanking)
- simulate scatter shots and scatter hits
- report the data as summary for each fight as well as the for each single shot done in the simulation (currently reported are: shooter, target, simulation #, # of shots, total hits, natural hits, scatter shots, scatter hits, misses, # of pens, # of bounces, # of frontal hits, # of rear hits.
As a model, I have chosen the T34/76 and OST PanzerIV and let the P4 shoot the T34 from 40 meters until the T34 is dead.
In a simulation of 10.000 iterations, I got the following data:
(read as 'how many simulation ended with x amounts of shots/misses/bounces?', e.g. at 0° angle, 885 simulations ended after the P4 took 4 shots)
shot number graph
If we have a short look at the the graph, we see that the number of needed shots decreases if the target is angled, since rear hits become more prevalent. At large angles (that is higher chance to hit rear armor) angle, high shot counts comes mostly from misses, while at small angles they come from both bounces and misses.
In the dataset we can see that at 180° angle, the P4 is unable to even hit the frontal armor. Since the P4 always pens the rear armor, there are also no bounces. Also, in no dataset occur more than 4 rear armor hits, after which the T34 is dead and the simulation ends.
All in all, the simulation seems to come decently close to what we really know about the game. However I had to make a few assumptions, and the most important one is the scatter model:
Nobody except for Relic knows how it really works. The current simulation calculates an area where the shot can land and picks a random point inside that area. All points are equally likely to be picked.
We don't know if this really is the case though, it might be that scatter shots have a higher probability to land closer to the originally targeted area than further away. MMX has done small scale tests and suggested this, but we need proper testing on that. Please see the bottom spoiler if you can help on that one.
Second, which might be an easy task for people knowing the game files a bit better:
I do not know the actual hit boxes. For the above simulation, I took the size of a real T34 from Wikipedia and hoped it would somehow fit what is in the game. The real hit box sizes would be great though for accurate simulations.
After ironing out some minor issues, further plans are to simulate an actual fight of two tanks shooting at each other until the winner is determined. This would then include more knowledge about the time between two shots.