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Scatter This! - Your trusty scatter calculator

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Posts: 999 | Subs: 1

Hey Everyone!

Since the community has recently been provided with an immensely useful tool to simulate tank vs tank combat by Hannibal, I've decided to follow his lead and proudly present you Scatter This! - an Excel-based calculator to analyze scatter and AoE-based anti-infantry performance of tanks and indirect fire units.

Now many of you will probably say "Wth is this and what would I ever need this for?", so let's start with a brief explanation what this spreadsheet does and why, before glancing over on how to use it and for what purpose:

1) What does Scatter This! do?

Most of you will probably be familiar with how accuracy (i.e. the product of base accuracy, target size and received accuracy modifiers) determines if a fired round hits its target an deals damage, or misses and scatters off somewhere into the wilderness. And while these scatter shots may still connect with something on their path to deal damage, their contribution to the overall damage output is usually quite small in regular tank vs tank combat, simply due to the fact that tanks already have a pretty low chance to miss each other to begin with.

However, in tank vs infantry fights accuracy plays a much lesser role for damage output, as the target size of an infantry model is much smaller than that of a tank. As a result, most tank guns only have a 1:25 to 1:50 chance to score a direct hit against infantry, making accuracy almost irrelevant for damage calculations.

This is where scatter and AoE profiles come in as an additional layer of RNG in the game - and, unfortunately, one that is much more obscure and less well understood by most players.
Scatter basically determines how far away (horizontally and vertically) a round will impact from its intended target and, luckily, a great and extensive overview of how scatter works can be found here for all of you interested in the detailed mechanics behind this. Hence, we only need to briefly cover the impact of the AoE profile on the damage calculation.

As the name implies, the AoE profile of a weapon determines how much damage is dealt to entities caught within its blast radius and typically declines the farther away the point of impact is from the target. Taking the AoE profiles of the Tiger and 75mm Sherman HE round as an example (see image below), you can clearly see that an infantry model has to stand pretty close to the center of impact to receive lethal damage (which is anything higher than 80 for most infantry models out of heavy cover), but will still receive small amounts of chip damage from impacts much farther away. The actual damage at a given distance is determined by the shape or slope of the curve, and may vary greatly between different tanks.

AoE curves of Tiger and 75mm Sherman with HE rounds

Therefore, knowing how far away a scatter shot lands from a given target and how much, if any, damage is dealt according to this distance is all what is needed to calculate the anti-infantry performance of a weapon.

This is in essence what Scatter This! does.

2) How to use Scatter This!?

2.1) Setup

In order to use the calculator, you'll obviously need to download and unzip it first, after which you should be all set... unless of course you don't have MS Office or some Excel analog installed on your computer, although I doubt anyone can live without this.

2.2) Input

After opening the spreadsheet, quickly navigate to the "Scatter Sim" tab which contains the main calculator and should resemble the image below:

Main window

This is where you can set the parameters of the simulation and view the results from a couple of tables and handy graphs for visualization:

You'll notice that, due to the way Excel handles volatile functions, the sheet will update automatically whenever you change any cell value. This happens quite quickly on my 3yo laptop, but could take significantly longer on older machines due to the unoptimized cell logic (sorry). For those who feel this is slightly annoying there is a button to toggle the calculation mode to manual, which lets you update the sheet only when you want it by pressing F9.

To start a scatter simulation, first select a shooter from the dropdown menu (L2:M2, J2:K2 to select specific categories) and set the parameters for distance to target (D2), max number of shots (A2, must be between 1 and 500) and one-hit kill threshold (E2, should typically be 80 HP, but can be set to lower or higher numbers to simulate cover or damage reduction). If desired, additional modifiers for firing into the FoW (G2) or on the move (H2) can also be enabled or disabled.

Next, the number and formation of the target entities can be selected from the "Formation" menu (N5), with the option of either using one of the 6 formation presets (big thanks for Hannibal for measuring and providing the in-game templates 4-6) or generating your own squad formation using the custom builder or the formation randomizer.

With these set, the targeting mode (N7) can be adjusted to either randomly pick a model to target ("random"), pick the entities with the lowest number first ("fixed") or fire at the center of the template instead (this disables target switching and should be chosen for barrage-type weapons).

Automatic target switching after a model dies can be enabled (N11) or disabled to target specific models only.

Lastly, the "Position" dropdown menu changes how the simulation handles the position of the shooting entity and the target. Choosing "relative" keeps the distance and angle between shooter and every entity targeted constant. As a result, the shooter is 'teleported' each time another model in the formation is targeted.
A more realistic option can be selected by choosing "absolute", which locks the position of the shooting entity in place and only changes the firing angle upon switching targets. However, since in this case the true distance between shooter and each entity in the formation may be greater or smaller than the respective minimum and maximum range of the shooter, the distance set in cell D2 may need to be adjusted accordingly.

Difference between "relative" and "absolute" position mode

2.3) Results

Using the input variables, the calculator will simulate shots fired at the target squad until the last model has received fatal damage. For each shot, an accuracy roll first determines if a natural hit of the targeted model occurs or if the shot scatters to a random point within the scatter cone. Then, the distance between point of impact and each model is calculated to check if and how much AoE damage is dealt. If the targeted model dies, the model with the next-highest priority is selected and targeted for the following shots until the simulation ends.

Detailed results and timestamps can be viewed in the table from columns T:AU and should look something like this:

Main calculation table

Alternatively, the main results are summarized in the leftmost table (A5:H10), showing the number of natural hits, one-hit kills, shots required to kill, and, in case not all models died within the set limit of fired shots, the entities and respective HP left after the simulation finished.

For visualization, the two upmost graphs provide information on the shot distribution (i.e. where each shot landed with respect to the target formation), while the 3rd graph displays the area of the scatter cone and size of the AoE circle. Last but not least, the AoE curve can be seen in the last graph.

Numbered shot distribution display indicating shot sequence

Color-coded shot distribution display indicating targeted entity

AoE and scatter area representation

AoE curve display

2.4) Enumeration, a.k.a. increase sample size

Now being able to see the results of a simulated fight is neat and all, but it still doesn't give any more information on the overall performance than an isolated test in-game would provide.
However, in contrast to in-game testing, firing 50 simulated shots at a target using the spreadsheet is a good deal faster (hopefully) than any in-game test would allow, so we can use this to our advantage to conduct hundreds or thousands of simulated runs in mere minutes as opposed to hours or days.

Still, copying a result and hitting F9 thousands of times in a row to get a statistically relevant result can be quite tedious and unnerving to say the least.
Fortunately, the "Scatter Enum" tab is there to save the day (literally), allowing to repeat a simulated fight for up to 10k iterations and further queue up other simulations to be processed one after another.
All you need to do is to select a range, entity, formation combination in rows 1:3, set the number of iterations of each simulation (BT4), the number of columns to process (BT5), and, most importantly, the desired result to iterate from the dropdown menu (BS3).
With this all set, start the iteration with the "Run calc" and wait (this could take quite long, depending on the number of iterations and the speed of your rig, so proceed with caution) for the macro to finish.

Enumeration calculator interface

Afterwards, you can use the "Analyze" buttons for each dataset on the right side to perform a basic analysis, giving the minimum, maximum, average and standard deviation over all repetitions in the upper panel, as well as the probability distribution for each event in the dataset (i.e. how many times the simulation ended after 10, 11, 12, etc.. fired shots).

Analyzer for Enumeration results

3) Why would I want to use Scatter This!?

Well, I'm glad you asked! While Scatter This! won't offer any answers to mankind's most burning questions, such as "Are we alone in the Universe?", it will surely come in handy if you want to bring some solid numbers to back up your arguments in any scatter- or AoE-damage related balance thread!
To back this up, let's have a look at the following two examples and how Scatter This! can be utilized therein:

3.1) Case study #1: The state of the Tiger

Undoubtedly, the Winter Balance Patch brought a bit of fresh wind into stale heavy tank meta, not least due to nerfs to the AoE damage profile of the Pershing , IS-2 and Tiger. And while all three heavies have been on the receiving end of this, some people feel the Tiger has indeed been hit quite a bit harder by the nerf bat. Justified or not? Well, lets run the numbers to see how much truth there is to this assessment.

To judge the impact of the changes, we'll do a head-to-head comparison of live version of the Tiger, its pre-WBP counterpart, the Vet 2 version of the latter still benefiting from the 20% scatter reduction, and last but not least the Ostheer PzIV to put things into perspective.

Looking at the size of the scatter cone and the AoE area - here in particular the OHK area - in the graph below, you can easily see the extent of the OHK radius reduction between the live and pre-WBP Tiger, as well as the reduced scatter area of the Vet 2 pre-WBP Tiger.

Scatter/AoE area comparison for Tiger, pre WBP Tiger (Vet 0 and Vet 2) and Ostheer PzIV, wide formation

Now the question is of course: How much does that impact the anti infantry performance?

To answer this, let's consider the number of shots required to kill (S2K) a full-health, 6-man squad at a distance of 20 m in a spread-out formation for each tank. Using a sample size of 1,000 iterations we get the following average S2K and T2K (time to kill) values:

Comparison of absolute and relative S2K and T2K values for different tanks versus a full-health, 6-man squad in a wide formation at 20 m distance

While the live Tiger needed 9.5 shots or 45.7 s on average, the pre-WBP version would take about 13% less shots or 15% less time to kill the squad under the same conditions. The the Vet 2 scatter bonus unsurprisingly yielded an even greater performance gain, resulting roughly 25% lower S2K and 28% lower T2K between the old Vet 2 Tiger and its live counterpart.
Still, owing to its superior scatter and despite the much smaller OHK radius the live Tiger remains vastly superior to the PzVI in terms of AI performance, which on average takes more than double the time (~115% more) to wipe all 6 models of the targeted squad.

Considering one objective of the patch was to decrease the OHK potential of heavy tanks, let's crunch the numbers on that one too while we're at it.

Comparison of one-hit kill performance for different tanks versus a full-health, 6-man squad in a wide formation at 20 m distance

As you can see from the graph obtained by again running 1,000 iterations and, this time, recording the number of OHKs per run (i.e. the number of models dropped from 80 to 0 HP in a single shot), the live Tiger did not snipe any model in a single hit in 74% of all cases and OHKed 1 model in the remaining 26%. One-hit wipes of 2 or more models did not happen at all, which of course isn't too surprising given the large maximum AoE and tiny OHK radius of the live 88mm shell in conjunction with the relatively large distance between each squad member.
In contrast, the old Tiger used to wipe at least one entity per hit in more than half the occasions due to the larger OHK radius.

Now of course the recent performance nerfs should be most obvious for clumped-up formations, in which the inter-unit distances get small enough to fit almost the entire squad into the OHK area, so let's see how things change when moving from a spread-out to a much more densely packed formation:

Scatter/AoE area comparison for Tiger, pre WBP Tiger (Vet 0 and Vet 2) and Ostheer PzIV, clumped formation

Since the bunched up model template now conveniently fits into the OHK area of all tanks bar the live Tiger, not only the S2K and T2K values should be considerably smaller than for the wide formation but also one-hit wipes of up to all 6 models should occur much more frequently.
Performance-wise, we find the S2K and T2K of the live Tiger indeed to drop to only 3.9 and 15.4 s, respectively, as seen in the graph below.

Comparison of absolute and relative S2K and T2K values for different tanks versus a full-health, 6-man squad in a clumped formation at 20 m distance

Also in line with our expectation the pre-WBP Tiger performs significantly better than the live Tiger due to the larger AOE near and mid radius together with higher AOE near damage multiplier. As a result, the S2K and T2K are now 19% and 25% lower on average than for the live Tiger, which has to be considered quite significant indeed. Comparing the live Vet 2 Tiger with the pre WBP analog, this performance difference even reaches up to 40% - so it is quite safe to say that complaints about the new Tiger having gotten its fangs pulled are not unjustified in my personal view.

This can also be seen from the OHK performance of the new Tiger, which is now roughly on par with that of the PzIV, albeit without the occasional one-hit squad wipes the PzIV is still capable of due to its relatively large OHK radius.

Comparison of one-hit kill performance for different tanks versus a full-health, 6-man squad in a clumped formation at 20 m distance

In conclusion, I think these results not only show how Scatter This! can serve as a valuable tool to compare the anti-infantry performance of different tanks under different conditions, but also shows that the Tiger tank may indeed suffer a bit more from the recent nerfs to heavy tanks than intended.
Some of you may also remember me posting a similar, yet more condensed analysis a few weeks ago here, which came to a slightly different conclusion. However, somehow i missed the AoE near range reduction from 1.5 to 1 m in back then, which made the Tiger look a bit better than it actually is. Nonetheless, the general conclusion that heavies remained almost as lethal as before the patch still stands, even though the Tiger may be a bit of an outlier here.

3.2) Case study #2: PM-41 vs HM-120 - Duel of the mortars.

In the second example, we're gonna tackle another subject that has come up a couple of times in the recent months: Which of the two soviet mortars is better, the trusty non-doc 81mm or the doctrinal 120mm heavy weight contender?
Of course a comparison of the anti infantry performance can only partially answer this question due to the sheer number of other factors, such as price, availability and utility playing a major role as well. Still, this particular aspect is notoriously hard to quantify and opinions on that remained divided as a result. Luckily, this is where Scatter This! steps in again to bring a bit more light into the dark.

Similar to the Tiger example, a quick look at the S2K and T2K numbers for both mortars can provide a good first impression of which one pulls ahead, so let's find out how the averages over 1,000 iterations for the auto-attack of both mortars against a spread-out or clumped 6-men squad at 80 m distance compare.

S2K and T2K values for the soviet PM-41 and HM-120 mortars at 80 m versus clumped and spread-out squad formations

As visible from the charts above, the autofire of the HM-120 is clearly superior to its smaller 81mm cousin, despite the fact that the heavy mortar has a longer delay between shots than the PM-41. The reason for this is that both mortars have a similarly sized scatter area at 80 m range while the 120mm has far superior AoE damage beyond 1 m distance to impact (see graphs below).

Autofire AoE and scatter area vs distance for the HM-120 and PM-41

However - as most of you will probably interject at this point - in a real in-game scenario no one except players with a ranking having more digits than your zip code will leave a squad in the firing cone of a mortar until death. Also, the only real saving grace for any mortar is its barrage, so let's focus instead on a slightly different approach to gauge the performance of the two mortars.

This time, we'll simulate using the barrage into the FoW against a static clumped or spread-out squad - same distance, same conditions except we now limit the number of shots fired each time (in the main calculator, cell A2) from 1 to the maximum number of shots fired per barrage (4 for the PM-41 and 6 for the HM-120), enable the FoW multiplier (cell G2) and keep the center of the firing cone in the center of the formation template (by selecting "center" in cell N7). Furthermore, we record the HP left after each simulation by switching the category in cell BS3 in the "Scatter Enum" tab to "HP left".

After again running 1,000 iterations for each case (i.e. 1, 2, 3 and 4 shots fired for the 81mm; 1, 2, 3, 4, 5 and 6 shots fired for the 120mm mortar), we get the following results:

Remaining HP of a full-health, 6-man squad in clumped or wide formation after n barrage shells fired by the PM-41 or HM-120 mortar.

Interestingly, the PM-41 now seems to be on par with bigger cousin in terms of HP drained during the first 4 shells dropped on the spread-out squad, and even pulls ahead in case of the tightly clumped squad. Coupled with the longer delay between shells launched for the 120mm mortar, the HM-120's only saving grace is its greater number of shots peer barrage, which allows it to eventually catch up with and overtake the PM-41 in terms of damage dealt.
As you might have guessed already, the reason for this quite unexpected divergence in performance lies again in the size of the respective scatter cones of the two mortars (the AoE profiles remained roughly the same as in the autofire example).

Barrage AoE and scatter area vs distance for the HM-120 and PM-41

As visible from the second panel in the graph above, the scatter area for the PM-41 in barrage mode at 80 m distance is much smaller than that of the HM-120 (thanks to a distance_scatter_max value of only 4 essentially capping horizontal scatter for distances greater 25 m in case of the former). And since we've been firing into the FoW, the true discrepancy between both mortars is even greater than displayed here.

So, the answer to the question to which of the mortar is better is... indeed quite difficult to answer, as it depends quite heavily on the circumstances under which they are used.

For barraging into the FoW, the PM-41 performs equally or better than the HM-120 at max range, but due to the way the scatter area depends on distance, the situation is likely reversed at closer range.
Using autofire, the HM-120 can get the job done in about half the time.

Congratulations if you've made it so far without falling asleep! While these two examples may already serve as a ground for further discussion by themselves, I hope even more that you're now eager to explore Scatter This! on your own and use it to generate some theoretical data yourself for that next balance thread!

4) Where to get Scatter This!?

Easy peasy, you're just one click (well, maybe a couple more than one) away. Download it here, no installation or setup required other than starting Excel and loading it! Be aware though that the spreadsheet contains some macros that are required in order for all functions to run properly.

This project is kind of a work-in-progress, so please feel free to check back on possible updates every now and then. Also, any comments and suggestions are highly welcome, and if you find any errors (likely!) in the data sheet, let me know so I can fix them.

Last but not least, big shout out to Vipper and especially Hannibal for the fruitful discussion and suggestions regarding the scatter model used in the simulation over the last weeks.

Best
-MMX-

UPDATE 5/18/2020 New version of the Spreadsheet is ~~available~~!

Fixed non-functional OHK and natural hit counters in the main result table
Added an info box displaying the chance and damage for a natural hit (accuracy roll), as well as the respective chances to deal highest possible and lowest possible amount of AoE damage vs a single target.
Corrected some errors in the data sheet and added profiles for rocket artillery pieces
Fixed the orientation of the in-game formation templates (preset 4-6) by rotating 90° clockwise. Thanks again to Hannibal for pointing out the error!

UPDATE 2/4/2021 It's been quite a while since I've last revisited the spreadsheet, but a revamped version with tons of new features is now ~~available here~~!

Complete overhaul of the calculator that now not only simulates the damage of main gun projectiles, but also offers a crude approximation of MG damage output. Ever wondered if that pintle MG on top of the PzVI is even worth the munitions? Test out how much of a difference it actually makes with the simulator!
Revamped Simulator tab that now calculates the average damage and kills dealt (total, by MG and by main gun) after each shot for each model in a squad over 100s or 1,000s of repetitions.
Graphical interface that allows quick and easy visualization and comparison of results
New templates for rocket artillery and various off-map arty strikes
A number of bugfixes, especially for the unit stats in the Data tab

UPDATE 2/19/2021 A couple of bugfixes and a new interface with fancy graphs ready to ~~download here~~!

Added a new graphical interface tab that allows comparison of up to 4 datasets and shows damage/kills over time, the contribution of MGs and the main gun to overall damage and model kills, as well as plots comparing the respective AoE and scatter area curves
Included option to export/import datasets to/from .txt
Fixed the damage reduction multiplier not correctly applying to machine gun damage
Fixed an error in the TBS (time between shots) calculation affecting weapons with cooldown

UPDATE 1/12/2022 It's been a while since the last update to the spreadsheet, so I figured it's time to bring back ScatterThis! with updated unit stats reflecting the most-recent patches and a number of new features. Get the newest version here!

Updated MG damage calculation model: While the previous solution allowed a crude approximation of the DPS/KPS the tank-mounted MGs add to the overall AI performance, it wasn't really suited to capture the variance, or "hit-and-miss" nature, usually observed in-game (who doesn't love chasing a retreating squad across the map while constantly missing the last, lethal hit?). The new randomized model does just that by taking the number of fired bullets, targeting delays and accuracy into account when randomizing the damage output in a more realistic fashion
Improved simulation algorithm: A couple of tweaks to the VBA code tremendously increased the speed of the simulation, meaning that results are generated in about 1/10 of the time it took previously.
Up-to-date unit stats (sort of): While some remaining errors are likely, most of the recent balance changes should have made it into the unit stats tab of the spreadsheet by now. Unfortunately, some new abilities (e.g. the 105mm Sherman's and leFH's new barrage abilities) are still missing as there's currently no way of extracting the stats from the game.
New unit templates: A couple of light and ultra-light vehicles are now implemented (including the SdKfz 222 AC; thanks to Klement Pikhtura for the suggestion).
Improved simulator tab: The simulator tab has received some additional functionality and most relevant options (e.g. FoW and moving penalties, % uptime of tank-mounted MGs, etc) can now be set directly in the simulator tab.
Overhauled comparison tab: The graphical interface for plotting and comparison of the simulation results has been revamped to allow more data sets (6) to be displayed at a time. Other plotting options, such as switching between continuous or stepwise graphs and different color schemes have been added as well (again many thanks to Klement Pikhtura for the valuable feedback).
Damage distribution plots: The new damage distribution tab offers a more in-depth way to analyze how much and how reliable a unit delivers its damage over time. The 3D datasets produced in this tab display the probability distribution of how much damage / how many model kills are scored with each successive shot. This can give a pretty good impression of the variance (or reliability) of the DPS/KPS output as well as the alpha-damage capabilities, both of which are otherwise hard to capture using 2D plots.

Posts: 13496 | Subs: 1

Nice work.
Thanks for credits.

Posts: 1273

Wow, very well done! That is a nice neatly complex implementation, big thumbs-up for doing the most difficult part and time-intensive part of the work which is the coding & thoughtful academic design! Well done to you MMX for all of that and to Hannibal for laying the coding ground work - I also really like the clear and distinct examples of how you use the file. Excellent.

edit: giving it a go right now, that is proper good stuff!

Posts: 3114 | Subs: 2

Very great work!
You put plenty of time into this. The text of the post alone... wow!

I think this will be especially useful for balance team to determine scatter and AoE changes on units. But obviously this will clear up a lot of questions and discussions about AI performance. Let's see how forum discussions go from here on onwards, I hope less toxic.

4 May 2020, 12:56 PMJohnSmith

Wow, very well done! That is a nice neatly complex implementation, big thumbs-up for doing the most difficult part and time-intensive part of the work which is the coding & thoughtful academic design! Well done to you MMX for all of that and to Hannibal for laying the coding ground work - I also really like the clear and distinct examples of how you use the file. Excellent.

edit: giving it a go right now, that is proper good stuff!

I want to point out that I have provided nothing other than discussion and some of the spacing presets for this. I had nothing to do with the coding, that is all MMX's work.

Posts: 3114 | Subs: 2

Finally I can look up how long my SU85 needs to take out that damn Volks squad.
What a happy day

Posts: 2358

Great work man! Thank you so much!

Posts: 8154 | Subs: 2

My controls weren't working
And if they were, you were playing dishonorably,
And if you weren't, you were playing without skill,
And if you were, it's not fun to play that way,
And if it is, you only care about winning.

Bible of Scrublord, Psalt 3:16.

Multi Quote

Posts: 999 | Subs: 1

thanks a lot for all the kind words, guys!

4 May 2020, 12:56 PMJohnSmith

edit: giving it a go right now, that is proper good stuff!

great to hear you're giving it a try. let me know if you run into any errors or need some more info on some of the features/settings.

4 May 2020, 15:07 PMHannibal

Finally I can look up how long my SU85 needs to take out that damn Volks squad.
What a happy day

haha, i wonder if the hard-coded 500 max shots the sim can handle will be enough in this case...

Posts: 3114 | Subs: 2

5 May 2020, 03:39 AMMMX

haha, i wonder if the hard-coded 500 max shots the sim can handle will be enough in this case...

I remember that a friggin Jackson once sniped my last Sturmpio model on retreat and thereby wiped the squad. RNG was strong that game.

There seems to be an issue though with some counters in the summary table. At least for me natural hits (and I think the OHKs) were not counted properly and always showed 0, although the shot table registered them.

Posts: 1273

4 May 2020, 15:00 PMHannibal

Very great work!

I want to point out that I have provided nothing other than discussion and some of the spacing presets for this. I had nothing to do with the coding, that is all MMX's work.

Oh, I was mostly referring to your DeCoHde 2.0 project and the detailed Python script you published. I am confident it helped a lot of people to get into creating more adjacent CoH2 content (including this!)

Posts: 999 | Subs: 1

5 May 2020, 08:17 AMHannibal

I remember that a friggin Jackson once sniped my last Sturmpio model on retreat and thereby wiped the squad. RNG was strong that game.

There seems to be an issue though with some counters in the summary table. At least for me natural hits (and I think the OHKs) were not counted properly and always showed 0, although the shot table registered them.

oh, that's strange. worked for me last time i checked. i'll investigate what's going wrong there!

Posts: 3114 | Subs: 2

5 May 2020, 10:29 AMMMX

oh, that's strange. worked for me last time i checked. i'll investigate what's going wrong there!

I mean the counting formula looked fine on first glance, but I did not have a deeper look. Just noticed that although the detailed table reported a natural hit, the summary did not.

Posts: 999 | Subs: 1

5 May 2020, 14:35 PMHannibal

I mean the counting formula looked fine on first glance, but I did not have a deeper look. Just noticed that although the detailed table reported a natural hit, the summary did not.

Just had a quick look and, indeed, you're absolutely correct, thanks a lot for the hint! The array function counting the OHKs seem to work... sometimes, but not consistently for whatever reason. I've switched it out against a non-array version that seems to have no issues.
However, I couldn't reproduce the counting error for natural hits in any way. Do you consistently get this or only once in a while?

Posts: 3114 | Subs: 2

5 May 2020, 15:44 PMMMX

Just had a quick look and, indeed, you're absolutely correct, thanks a lot for the hint! The array function counting the OHKs seem to work... sometimes, but not consistently for whatever reason. I've switched it out against a non-array version that seems to have no issues.
However, I couldn't reproduce the counting error for natural hits in any way. Do you consistently get this or only once in a while?

I think I used the sheet only twice (Excel starts) by now without PC restart, but it did not work on any of these occasions.
I will retry tomorrow and write you. Or maybe someone else can post in the meantime.

Posts: 999 | Subs: 1

5 May 2020, 15:50 PMHannibal

I think I used the sheet only twice (Excel starts) by now without PC restart, but it did not work on any of these occasions.
I will retry tomorrow and write you. Or maybe someone else can post in the meantime.

hmm, no idea what's going on there... at least the naural hit tally should work just fine. anyway, thanks a lot for the troubleshooting, that's very much appreciated!. anyone else that had a shot at it yet experienced the same problem?

Posts: 3114 | Subs: 2

6 May 2020, 08:25 AMMMX

hmm, no idea what's going on there... at least the naural hit tally should work just fine. anyway, thanks a lot for the troubleshooting, that's very much appreciated!. anyone else that had a shot at it yet experienced the same problem?

Tested the sheet yesterday (release version):

Natural hits and OHKs do not work and are not counted, at least not for me.This is a minor issue though since it seems to work for others.
The natural hits are not that important, especially not for AoE calculations. Since you you said you fixed the OHK counter, all the important information is visible.

Posts: 999 | Subs: 1

8 May 2020, 15:37 PMHannibal

Tested the sheet yesterday (release version):

Natural hits and OHKs do not work and are not counted, at least not for me.This is a minor issue though since it seems to work for others.
The natural hits are not that important, especially not for AoE calculations. Since you you said you fixed the OHK counter, all the important information is visible.

thanks a lot for testing again. maybe it's related to the excel version you use? i've tested it with the office 2013 and 2016 version, but maybe some functions got changed in more recent or earlier versions.
anyway, i'll upload an updated version that fixes the OHK bug at least on my side and contains data for rocket artillery as well soon...

Posts: 930

Does movement affects scatter? if so how much?

Posts: 17914 | Subs: 8

10 May 2020, 21:15 PMzerocoh

Does movement affects scatter? if so how much?

Yes, increases it by 50%.

25 Nov 2015, 11:09 AM$nuffy

Maybe it's 'cause the Axis players aren't a bunch of forum crybabies, and they keep their cool and fight the uphill battle, unlike some of their "allied" counterparts.

Good Stuff here

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Posts: 999 | Subs: 1

10 May 2020, 21:15 PMzerocoh

Does movement affects scatter? if so how much?

10 May 2020, 21:21 PMKatitof

Yes, increases it by 50%.

The moving penalty is actually even worse. It's a straight multiplier of 2 to both angular and distance scatter that is not capped by distance_scatter_max.

So as a rule of thumb, shots will scatter double as far in the left/right and up/down direction when moving.

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COH2.ORG » Forums » Parlor Room » COH2 Central » COH2 Gameplay » Scatter This! - Your trusty scatter calculator

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                        1.
Krakenn
1771
443
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+3
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ker_141
518
216
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3.
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2504
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1534
535
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输了变白毛蓝瞳美少女
206
105
.662
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6.
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388
251
.607
+9
7.
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159
60
.726
+4
8.
Marcel
327
144
.694
+1
9.
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517
330
.610
+1
10.
Asuka top soska>3
251
139
.644
-1

                    

                        1.
DIRTY_FINISHER
2169
900
.707
-1
2.
Zirty Zoggy
119
24
.832
+2
3.
Veni
269
88
.754
-1
4.
【Clannad】
263
89
.747
+3
5.
✠Kaiser✠ PERVITIN
446
297
.600
+1
6.
Pioneer
211
103
.672
+2
7.
T.R. Thoton
284
124
.696
+12
8.
Burden
162
58
.736
-1
9.
铁甲小兔
437
294
.598
+4
10.
Hotzenplotz
957
512
.651
+6

                    

                        1.
Thales
1453
737
.663
+5
2.
BBangYa
466
195
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+15
3.
Muhhdock
426
130
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+2
4.
Perun777
357
216
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+2
5.
makke
536
218
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6.
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474
216
.687
+4
7.
Riiiiina
315
136
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+16
8.
Yox
818
467
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-1
9.
Tom
118
52
.694
+2
10.
Restzeit
474
417
.532
+7

                    

                        1.
噗露露特
354
170
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+1
2.
godjaemin
346
157
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+1
3.
Misaki
338
104
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-2
4.
SoE-Sturmpanther
897
246
.785
+5
5.
Jax
587
254
.698
+9
6.
BATTLEDANNY1
698
336
.675
-2
7.
makke
939
429
.686
+1
8.
King of Lee
1509
995
.603
+9
9.
Cn Dg
120
34
.779
+10
10.
Shrimp
270
136
.665
+7

                    

                        1.
渣渣！反了他！欧布艹了你爸!气死偶嘞
2840
1025
.735
+2
2.
Stupid cat
506
159
.761
+17
3.
vonLewinski
546
194
.738
+27
4.
Bober
933
376
.713
+3
5.
zieja.pl
1715
873
.663
-1
6.
hoijimmy890.ttv
1360
445
.753
+14
7.
Basset
917
379
.708
+4
8.
铁证如山
631
379
.625
-1
9.
Imbbe
533
310
.632
+22
10.
红色卫兵
132
27
.830
+8

                    

                        1.
DIRTY_FINISHER
3043
1503
.669
+14
2.
[SVO] ✠Kaiser✠ tushkan
338
175
.659
+3
3.
TheMeowGamer
248
122
.670
+5
4.
ttv  HSRometh
529
386
.578
+4
5.
Burden
222
73
.753
+5
6.
André
356
169
.678
+5
7.
KIROV | BIH/QC |
855
493
.634
+6
8.
Pioneer
177
101
.637
+5
9.
gardening lelic
1307
788
.624
+2
10.
F[Lex]
448
333
.574
+2

                    

                        1.
Thales
780
375
.675
+9
2.
Yox
467
279
.626
-1
3.
Peppa
165
55
.750
+4
4.
White8===D
357
265
.574
-1
5.
Tom
105
30
.778
+5
6.
makke
480
243
.664
+1
7.
Q
643
391
.622
+6
8.
Zsirbacsi
244
150
.619
+6
9.
[NS]Hell March
414
165
.715
+6
10.
[Dengue]™Alexandro
248
87
.740
+3

                    

                        1.
Bulbasaur
721
379
.655
+4
2.
Komuccap
346
135
.719
+1
3.
Misaki
320
176
.645
-5
4.
makke
936
700
.572
+3
5.
(MTRQ) ForsakenHunt  ( ^ _^)b
656
488
.573
-1
6.
[Dengue]™Alexandro
1246
740
.627
+2
7.
BATTLEDANNY1
460
320
.590
+2
8.
PunkBusterr
71
47
.602
+1
9.
噗露露特
152
111
.578
-3
10.
昂撒猪猪拳
437
350
.555
+3

                    

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7368
2731
.730
+4
2.
Bober
1832
774
.703
+8
3.
ker_141
469
220
.681
+7
4.
hoijimmy890.ttv
1383
535
.721
+2
5.
Stupid cat
394
121
.765
+2
6.
Krakenn
4138
928
.817
+2
7.
输了变白毛蓝瞳美少女
575
283
.670
+7
8.
vonLewinski
651
206
.760
+6
9.
Asuka top soska>3
583
324
.643
+1
10.
红色卫兵
149
62
.706
+10

                    

                        1.
DIRTY_FINISHER
1475
638
.698
+2
2.
Alastor
203
49
.806
+6
3.
✠ Kaiser Friedrich ✠
1612
1158
.582
+2
4.
[SVO] ✠Kaiser✠ tushkan
695
436
.615
+1
5.
Falko_nero22
663
345
.658
+9
6.
Flap
526
285
.649
+3
7.
✠Kaiser✠ PERVITIN
378
206
.647
+3
8.
|^ Saltman™
1899
1281
.597
+3
9.
★Osas
174
67
.722
+4
10.
FIelA
1308
808
.618
+11

                    

                        1.
Vertsu
477
173
.734
+1
2.
Oorah!
506
212
.705
+8
3.
★Osas
646
294
.687
+4
4.
Richmond
254
114
.690
-1
5.
Kilder
838
377
.690
+7
6.
Artyom
245
69
.780
-1
7.
Thales
693
306
.694
+9
8.
Cow
235
86
.732
+1
9.
.OneTwo
1178
847
.582
+3
10.
Restzeit
576
402
.589
+1

                    

                        1.
噗露露特
338
155
.686
+1
2.
Cn Dg
151
40
.791
+3
3.
Shrimp
671
312
.683
+2
4.
SpacePig
379
184
.673
+10
5.
Obesity
236
221
.516
-1
6.
钱难挣，屎真香
400
172
.699
-1
7.
Hey girl go back to the kitchen
243
215
.531
+3
8.
BATTLEDANNY1
970
475
.671
+3
9.
黎霏洺
737
304
.708
-3
10.
昂撒猪猪拳
1699
827
.673
+1

                    

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3508
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+9
2.
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1077
406
.726
+2
3.
TRI1091
258
79
.766
+9
4.
SKELETRON
2022
686
.747
+26
5.
GiantDwarf
602
164
.786
+3
6.
vonLewinski
393
150
.724
+24
7.
Bober
694
282
.711
+3
8.
输了变白毛蓝瞳美少女
188
88
.681
+11
9.
Pioneer
179
102
.637
-1
10.
GiantDwarf2
199
30
.869
+8

                    

                        1.
DIRTY_FINISHER
2642
1441
.647
+5
2.
靈魂收割者十分簡單對
276
165
.626
+3
3.
☞ ps3YES ☜
733
323
.694
+9
4.
TRI1091
460
190
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+3
5.
Pioneer
183
93
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-1
6.
앙드레 조선어 ㅆㅅㅌㅊ
285
128
.690
+8
7.
William H. Harrison
479
202
.703
+3
8.
Zirty Zoggy
74
21
.779
+2
9.
shadics ARG.
398
175
.695
+7
10.
BatON
1137
770
.596
+2

                    

                        1.
SFC. LEE ッ
3086
1001
.755
-1
2.
Restzeit
642
336
.656
+8
3.
Tom
92
16
.852
+15
4.
遇到狗就输
695
400
.635
+5
5.
Peppa
255
100
.718
-1
6.
Oorah!
346
148
.700
+5
7.
Riiiiina
446
162
.734
+6
8.
JOE
1156
703
.622
-2
9.
Remder
687
234
.746
-1
10.
쿨게이
205
112
.647
+5

                    

                        1.
lol
403
313
.563
+2
2.
godjaemin
330
243
.576
-1
3.
玛丽猫猫
846
720
.540
+2
4.
噗露露特
138
87
.613
+3
5.
Jax
157
65
.707
+4
6.
BATTLEDANNY1
482
333
.591
-1
7.
Bulbasaur
463
299
.608
+2
8.
King of Lee
679
536
.559
+2
9.
フンッ！逃げるつもりかい！！
422
316
.572
+2
10.
Cn Dg
59
12
.831
+10

                    

                        1.
Krakenn
830
222
.789
+36
2.
MoronPark_Cat YE
349
57
.860
+14
3.
渣渣！反了他！欧布艹了你爸!气死偶嘞
571
211
.730
-3
4.
Krakenn
1097
613
.642
+1
5.
Bober
916
404
.694
-1
6.
micmillan2
280
162
.633
+8
7.
vonLewinski
305
114
.728
+1
8.
阿萨塔
721
440
.621
+3
9.
PanMuGwan
147
58
.717
+1
10.
ker_141
266
108
.711
+17

                    

                        1.
☞ ps3YES ☜
2012
1083
.650
+7
2.
IncaUna
569
354
.616
-1
3.
DIRTY_FINISHER
1675
921
.645
-2
4.
HazardousMoose
426
271
.611
+1
5.
TheMeowGamer
101
36
.737
+4
6.
✠Kaiser✠ PERVITIN
189
101
.652
+1
7.
Flap
432
208
.675
+1
8.
[虎贲] Leng Mo
116
49
.703
+7
9.
【Clannad】
209
68
.755
+7
10.
André
286
120
.704
+3

                    

                        1.
Thales
753
286
.725
+1
2.
Tom
169
48
.779
-1
3.
Peppa
214
90
.704
+17
4.
Remder
600
178
.771
-1
5.
André
981
427
.697
+3
6.
Ovidiu
1424
712
.667
+1
7.
Riiiiina
324
127
.718
+12
8.
★Osas
359
155
.698
-1
9.
SoE-Sturmpanther
360
59
.859
+2
10.
Shifty
179
105
.630
+2

                    

                        1.
玛丽猫猫
568
415
.578
+2
2.
Tharrats
775
618
.556
+5
3.
Shrimp
232
122
.655
+2
4.
BATTLEDANNY1
398
285
.583
+1
5.
黎霏洺
311
206
.602
+2
6.
ukill
194
157
.553
+10
7.
一个坏人
133
47
.739
+3
8.
King of Lee
239
169
.586
+5
9.
bilibili24511298丶无赖哥
1469
1198
.551
+3
10.
Kamooos
379
285
.571
+1

                    

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