Stratadrake wrote:
At a rated accuracy of 75%, Mantis and Python took damage 100% of the time (a.k.a. 100% of misses), again no difference between them.
That tells me how the rouding error affect my chart... However I still need the same test with tiger to confirm that since it is 2px smaller than mantis, the accuracy stay at 75%.
I believe you are overevaluating a little the effect "miss behing" that should gives ~1/4 of the miss as hit. It would mean 62.5% when 50% of accuracy. And 82% when announcing 75%. Otherwise your experiment exactly confirm the source code .
I believe you are overevaluating a little the effect "miss behing" that should gives ~1/4 of the miss as hit. It would mean 62.5% when 50% of accuracy. And 82% when announcing 75%. Otherwise your experiment exactly confirm the source code
It was noted that missing behind the target has little to no effect on artillery or VTOL weapons, only ground-based direct-fire ones.
Okay, I've tweaked my testing method and achieved the following results:
About six squares or so. But doesn't that have zero effect on shot scatter? Range determines when you can attack; scatter is calculated when said attack is actually executed.
It is impossible to tell whether a "false miss" was targetted "inside" or "behind" the target hitbox because the projectile explodes the moment the game detects a hitbox collision - zero projectiles ever make it to the behind of the target.
It's mathematically possible to identify how many of these misses landed behind the target's hitbox (based on known size, scatter, and range to target), but the steps get a little complicated....
I know, what I say it's that it's impossible to explain the data you got only by the miss behind bug. There is another undocumented bug of the accuracy system yet to find...
No, I don't think so. If I take the figures you gave in previous posts for hitbox and scatter radius determination, then let's break down the results:
1 - Python took 88% of hits from a 50% base accuracy weapon. So 38% of all shots fired (a.k.a. 76% of misses) were false hits.
2 - If Python has a hit radius of 54 and the weapon has a scatter radius of 100, then (because actual scatter is determined by a radius/angle offset from target position) we can expect 54% of misses to land inside the hitbox radius (regardless of angle) and score a false hit.
3 - Misses targetted "behind" the hitbox will impact the target en route and also score a false hit.
4 - If only 54% of misses should have hit, but 76% actually did, this is a +22% difference and it represents the number of misses that were aimed behind the hitbox.
So in total, of 400 shots fired at the Python:
- 200 (50%) were expected to hit the target (and did)
- 108 (27%) were expected to miss the target, but landed inside the hitbox and scored a hit
- 44 (11%) were expected to miss the target, but landed behind the hitbox and scored a hit en-route
- 48 (12%) actually did miss the target.
PS: Here's some trig for you to crunch on. Given a range-to-target (x), hitbox radius (r) and maximum scatter radius (s), then:
- Target radius expressed as an angle in the attacker's FOV: = arcsin(r/x) (total target diameter relative to attacker's FOV is twice this)
- Angular radius that represents an area always "behind" the target, regardless of scatter distance: = (90 - arccos(r/s) - arcsin(r/x) )
- Any scatter angle that exceeds (90 + arcsin(r/x)) is either aside or in front of the target, regardless of scatter distance
- Any scatter angle between the above two values may or may not land behind the target, depending on scatter distance