IMHO

OIC, yes my buildings are pretty wide. I assume building vs. vehicle may affect targeting logic as well.

And what were the targets for RPG? I have two different setups where a seven men veteran/crack RUS infantry squad inside a building fire at another building at 289m. I haven't calculated exact hit ratio but my feeling is they are on target with the correct floor with a 30-40% probability. It's a daytime, dry weather and gentle dead wind.

@Vanir Ausf B, I'll try to remember 2011 I meant variance in the each function node results. Let's assume 2D map, a soldier has a sector of so many degrees and he spends so much time scanning this sector. "Scanning" outcome could be no spotting, full spotting or semi-spotting and the latter two are grouped as "positive". If I remember correctly the probability of EITHER of the two positive outcomes for this sector scanning timeslot was quite stable. You get a large variance in the end time to spot finally and reliably because if one sector scan does not result in spotting (and it's randomized) then you'll need to wait for the next sector scanning or even the one after that etc. "Sector", "timeslot" etc. are certainly terms related to exact implementation so that's a kind of speculation for the sake of explanation The actual implementation method may well be far away. What I haven't researched much was full-spotting vs. semi-spotting and I never digged deep on how an angle to the target affects the probability. I had a crude proxy for the latter and I say crude as you have many soldiers in the squad so this smoothes out the effect of where exactly this particular guy is looking at this very moment. And the former one seemed to be a more complex function but luckily it was not so important for the task of a building assault optimization. You'll never be wrong with blasting with all force the moment you get a semi-spot on an OPFOR infantry lurking in the building. I never tried it with vehicles.

Stop tanks from instantly detecting ATGM launch direction if ATGM targets the tank, may be? Ok, in CMBS the tanks don't immediately acquire the targets as was the case in CMSF but they still rotate the hull and target acquisition time is enormously reduced... ATGM teams are still half-kamikazes

@Sgt.Squarehead, e.g. for CMBS I have a load-out model for the Russian seven-team infantry squad Number of enemy teams vs. total building size facing the probable route to clear up a town vs. the total length of the open terrain to run vs. distance distribution to the buildings you need to suppress (affects GL and RPG grenades flight time - they have different velocities so it affects the practical rate of fire and ammo use) -> gives you suppression time with "Target light" vs. "Target" with heavy weapons when you detect an enemy and you switch into full-blast, then the strategy you use - two full team suppression plus one-team attack vs. three scout teams split vs. three assault teams split Actually the only discernible unpredictability is TacAI now sometimes makes soldiers in suppression team run from a window to window so it affects the time each soldier spends firing so affects the optimal load-out

Combat Mission Six-dimensional (w)Formhole to the enemy occupied building? PS @Sgt.Squarehead, Combat Mission Statisticians-style Fighting Like in Wu-Shu

CMSF=Combat Mission Science Fiction?

Well don't throw me just yet Because when doing off the cuff sampling for discrete sets you needn't look at the total sample size but at the share of EACH of the discrete values in the sample size. So if you say that you want to understand the probability for a vehicle to bog, you ran 200 tests and the vehicle was immobilized just once - I'd say keep trying But if you ran 20 test and had 10 immobilizations I'd say may be it's discussable. But that's off the cuff - for important cases you don't stop even there. You have to understand how "the system works" and isolate the significant factors to build a robust sample relative to these factors. Because when you run test after test in CM you make one implicit assumption - that this set is random. And in real life there may well be some unknown factor that introduces bias so that even millions of events do not give you a representative sample Like when you say that for spotting you need to run the test at the same distance, weather, crew experience level etc. you actually make an assumption that this list of factors is exhaustive. And in real life it may well not be so and the next thing - you read an article about someone who lost hundreds of millions of dollars on careless approach to statistics No. From what I've seen it's multi-step calculation though each step is an obvious function with randomization. It's not a straightforward: "Take experience, weather, distance etc. feed it into one function, here you go - spotting or no spotting..." You can crudely compare it to a neural network with very simple function nodes. As in any neural network the end result taken per se is hard to interpret - here come these heated discussions But as the nodes are simple functions - if you take a case apart it becomes cristal clear. Disclaimer: I tested what I tested - see above... Indulge me with CMSF circa 2011 Just joking. Actually my feeling is the whole approach hasn't changed (luckily because it's quite logical ). I did some limited testing on CMBS - I see what looked to me like behaviour patterns similar to CMSF 2011 just at a well more refined and complex level. I've never done an exhaustive testing on CMBS similar to CMSF 2011. The objective of that old one was to understand how much and what kind of suppression I need to throw before I rush a team against a building in a urban terrain. So in the end I had a model where you can simply input your teams, target building parameters and the distance to it, nearby building parameters, probable enemy teams and probability of their presence in buildings and it would give you a distribution of loss probabilities for the attacking team depending on the amount of fire time for each suppressing team. But that's kind of killed the fun Spotting back then was quite simple and logical. Perceived complexity in spotting comes from the fact that many nodes generate binary results - so when you look from outside the end result seems incomprehensible. It's not - it's just not a straightforward single function calculation and you have a certain in-node randomization. So what you might see are several peaks/plateaus in the end results depending on how these binary nodes perform.

@Rinaldi, well if you make few steps away from textbook Gauss into the probability distribution one has to work with in real life I had a real life case when 50 mln values were not enough to acceptably approximate the probability function You believe 200 would have been any more convincing than 20? Correction: 3.5mln * 2 * 12=84 mln results and about 1'500 factor values for each result.

@c3k, Believe me 200 is no more convincing than 20 or 2000 from a statistical point of view Multiplying ten Gaussian distributions and one say log-normal makes the end result barely different from a simple Gaussian one. If I remember correctly the factors for spotting were: number of eyes, experience / suppression / bla-bla-bla, angle to the target, distance / weather / etc., probability to achieve SOME level of spotting for a given time slot (I guess it works through assigning sectors for a period of time but exact implementation is not so important for predicting the result), probability of "full-spot" vs. "semi-spot". Each individual function was quite simple - the end result, certainly, complex but only if you do not isolate. If you do - it's pretty easy to calculate. Outliers are not due to the complexity of each individual function - they are because the spotting is binary.

@IanL, try such a setup: an RPG team, the smallest building in front of it, an OPFOR team/squad inside the building, OPFOR is facing RPG team and is ordered not to return fire. Now RPG team makes one shot at the building, you write down the number of KIAs and WIAs should an RPG hits the building then you relaunch the battle. The idea is basically to isolate damage calculation logic. If I remember correctly the sum of soldiers turned into KIAs and WIAs status is ALWAYS a constant. I run the test something like 50 times though ten were enough PS Inside the sum of KIAs and WIAs the number of KIAs might be preset as well but I'm not so certain about it - it was six years ago. It makes battles a bit "gamey" since you can more or less accurately estimate the number of OPFOR guys left in the building after multiple RPG hits - due to this constant outliers will be quite rare. Having tested spotting / probability to hit / suppression capability of a team in the building one can predict the damage to one's soldiers should you desire to storm the building. To minimize outliers you do need to carefully isolate the factors. Should you try to estimate the end result of a rush to the building per se - you'd need many tests for sure. But if you isolate then summing up the factors and calculating mathematical expectation is straightforward.

@IanL, I dare to disagree There are rules of statistics on how to determine the number of tests. My impression from old CMSF tests were that the engine is mostly logic-driven rather than randomized. That's huge respect to BFC guys - I imagine how much time and effort were invested. But logic driven engines inherently limit the pool of outcomes so you don't need so many experiments to isolate a factor in simple processes. I can tell you there were some cases (albeight basic ones) that one could think are random at first. But in reality you could have EVEN A DISTRIBUTION within ten tests. Again because the pool of outcomes is limited and "streaks of (un)luck" is coomon for randomness it's really quite possible someone can be unlucky for 4-5-6 times in a row and get a bad taste in the mouth PS Actually this limited pool was the reason why I decided not to publish the results of the tests. It would have killed the joy of acquiring "the feel" of the game

@c3k, Why 200 tests and not 20 or 2000? I mean you know the variance and distribution rule? Actually some years ago I ran hundreds of tests of one of the old versions of CMSF engine. I was interested in spotting/accuracy/fire effects for infantry. The variance is actually quite low - the set of outcomes is predefined and quite limited. Certainly many things could have changed since then. I'd guess "bad seed" is irrelevant. If the save predefines the spotting then we will not have different spotting results loading from the same save. And we do. It may somehow skew the distribution depending on the logic but how it does it if it does at all - we don't know. Again from CMSF tests - there's a limited pool of outcomes and the result will be a random selection inside the set. I don't mean that the set is somehow "wired-in" (I don't know, actually) looks like it's the result of the engine algorithms. I have not tested extensively if there's a difference between saves and launching a new battle. I did mostly new battles with very limited saves - back then the pool of outcomes was the same for both cases, distribution - I don't know. Test with 200 tanks is dangerous, IMHO. Since we know that "collective scanning" does improve the results we cannot use single test with 200 tanks as a proxy for 200 tests with single tank. 200 tanks setup will test more of a rule on how units coordinate spotting between themselves rather than single unit spotting abilities. For RUS you dismiss an "ol' and good" radio link. Using linear multiplication for Abrams vs. no multiplication for T-90 you make an implicit assumption that a T-90 crew locates the target then keeps very private about the fact Just friendly corrections... PS Actually such a heated argument about spotting may be caused by this limited set of outcomes. Since the spotting is binary - see or no see - it's just some of you may be unlucky more often while others are simply fortunate

Sorry, one more thing I forgot to say, RPO effects are estimated for only one room of limited footage. 50m2 room with high ceilings will make an RPO explosion a "somewhat unenclosed" one.

As far as I remember it's 122mm. 152 is way too much for 2.4 litres of fuel-air mixture in RPO. One important qualification for the HE - FA comparison. When KBP provides this marketing slogan they use a little trick here. They compare the INDOOR effects of an RPO explosion INSIDE the enclosed shelter vs. HE nearby explosions OUTSIDE the shelter. You can make rough comparison by pulling the Joules of RPO mixture burning vs. the Joules of HE shell TNT contents. And certainly there's no hope for RPO to attain effects similar to 122mm HE if RPO explosion is unconfined. The trick in itself is not that absurd as firing RPO from 150m one can hope to be more accurate than calling a fire support from many kilometres away.

Guys, it might well be a tempest in a teapot. You don't know how saturated development pipeline is. It might be fully planned say for the next two years so these long discussions and exhaustive testing will have no impact in real life. Just because development/testing capacity is not infinite I guess it won't hurt to articulate that the game balance and how accurately the game reflects the real-life may well be mutually exclusive tasks So firstly you may want to come to an agreement whether you discuss how to make the game more enjoyable or how closely the game follows the latest battlefield data. Changes in fundamental aspects like spotting capability will have profound effects on the whole gameplay not just tank duels. It will be a different game and that means a lot of retesting so here comes the first point When speaking of the balance it seems to me you somehow assume that the force structures and their application tactics should be the same. Like how many T-90s we need to kill one Abrams. May be RUS and US battlefield tactics are very different so such a comparison is not 100% relevant? May be what should be discussed is how many Msta's shells are required to kill an Abrams because leveraging fire support is exactly the RUS tactics?

Object 477 Molot 152mm Scrapped due to dissolution of the Soviet Union. Certainly the cost would have been astronomical but the project never went beyond the early prototype stage so in reality nobody knows. Though feasibility might have been a bigger issue for the end of 80s - beginning of 90s. Armata is basically started as an Ural's revival of all 477 ideas. Plus some things that appeared since the end of 80s. PS The tone of the article is actually a pun on Ural's vs. Kharkiv's tank aficionados. Both side are pretty aggressive in peddling superiority of their camps. Especially Ural's

You are right - I used an incorrect wording. What I mean is the technological gap was one of the main driving forces that resulted in imbalances in Soviet Union force structures. I didn't mean precedence in time but rather a cause and effect relationship. Starting with tank armadas as a result of WWII mindset then the Soviet Union was left with tanks as the only way to counter US nuclear superiority (especially in delivery vehicles) and still effect an unacceptable damage to the European allies. Then the technological race began and the numerical superiority was considered as the only way to counter the gap. The tank overproduction was actually driven by extremely high estimated attrition rates. So in the end it was a kind of track that the Soviet Union was not able to turn away. With dire economic consequences A similar situation was in AAD - inability to achieve a balance in fighter force capabilities led to over-reliance on SAMs. Though here it had positive technological effect rather than churning out "dumb iron" Choosing cheap but less technological advanced T-72 over T-64 had negative effect on Soviet technology in tanks, IMO.

@John Kettler, Very interesting information! If I may add something from this side of then an Iron Curtain... USSR was capable of producing reliable millimeter-wave radars but not a longer range one especially if tank radio signature constraints were imposed. Plus an inability to guarantee accurate counter-warhead targeting with short reaction time and multiple threat processing. Given these limitations Soviet designers were bound to follow this particular route of Drozd improvement that failed in the end. Certainly as with any R&D they had not known in advance that it would not come to fruition. The initial results for HEAT/Heavy ATGMs were quite promising but it turned out the performance could not be pushed much further. It's funny that to a certain extent the concept of tank armadas was born not as an entry into ATGMs/tank race but as a RESPONSE to the long range capabilities of the Western equipment. We could not hit from afar, attrition rates were high and we could not close the technological gap so the end result was the creation of an unbalanced force structure where the predominance of one component was meant to mitigate the inability to create a capable combined force on par with Western armies. The same factor was instrumental in skewed force structures of Soviet Air Force and the Navy - though to different degrees. It's very interesting how higher echelons of Soviet leadership had very sober assessment of its technological and economical weaknesses. And it's a pity how irrational mutual distrust learnt at mother's knees led to so much time and effort of almost two generations wasted on building and maintaining such an expensively unbalanced overwhelming force And it seems like the history may repeat itself now at least in terms of distrust and misunderstanding of decision making factors "I am convinced that whenever we exaggerate or demonize, oversimplify or overstate our case, we lose" - Barack Obama. From an orgbehaviour point of view it's also remarkable how the interests of the Soviet military-industrial complex and inefficiency of talent management inherent to the Soviet system of 70s pushed back the Soviet Union from the 50s-60s' position of leadership in some areas of weapon design to a looser's approach of trying to replicate almost ALL and EVERY Western weapon system later on. An approach with no chance of success since a steam engine can never win a race against starship even if moving in the same direction An accurate rational assessment of Soviet limitations did not result in obvious decisions - cold-headed understanding but not an emotional acceptance

Mistake, pls, remove this post

They all have asphalt-going tracks, have they not? Very helpful over the sandy terrain?

On-topic: A user proposes but the Product Owner disposes Certainly the change in the behaviour in this area could have have far reaching repercussions across the gameplay so the developers' views are what matters, @Battlefront.com Off-topic: The question that is hardly be ever answered is what kind of and how much of an internal explosion this partition can handle. My guess would be it's designed to handle powder charges ignition and, alas, an HEAT ammo initiation(s) would make the tank a toast Residual effects of an HEAT hit is quite capable of initiating an ammo HEAT warhead should they reach one though probability of such an event may well be put in question

Guys, What's the current status on this? Is a change in plans? I remember in CMSF the tanks would instantaneously acquire targets, turn, aim and start shooting if still alive at this moment. As far as I understand in CMBS tanks immediately learn the direction (and position themselves relative to the threat) but do not acquire the targets per se. Will a fix make tanks unplayable easy preys?

@c3k, do you look for last season models? VAT refund required?

https://www.theguardian.com/world/2016/jul/27/weapons-flowing-eastern-europe-middle-east-revealed-arms-trade-syria If I remember correctly Bulgarian arms production tripled over the years of the Syrian conflict.