You sure? That looks IRIS-T and METEOR to me :P
nah those look more like 1000lb bombs and 2 rockets
Ok, I apologize for my offensive language.
In all seriousness, however, you vastly underestimate the matchmaking time in Air RB. The top rank matchmaking is actually the most popular of all BR; if you rely on your experience with the top battle rating, you will inevitably be wrong.
Secondly, the supposed 10% increase in matchmaking time is the ideal change, and not practically obtainable. The actual increase to waiting time will be much higher You must remember, even in Air RB mode, that matchmaking can take multiple minutes. This is especially apparent if you play on less popular servers (such as the SA server), or on less popular battle ratings (Super prop and early jet BRs come to mind), or on less popular times of day for the servers you play on. The combination of these factors has an exponential, rather than a multiplicative, effect on waiting time.
Players will naturally be frustrated with the long times of waiting and leave the queue. This is directly visible especially in Simulator battle rooms, where often 2 or more times the players required to start a match (which is 2 on both teams) join and leave the room after waiting for multiple minutes. Meanwhile, the match never starts because there were never enough players in the room at the same time. This effect also occurs in Air RB. In reality, the actual time increase from a 0.7 BR would be far in excess of 10%, likely multiple times the total wait time per player, due to this factor.
This is just the mathematical result. Right now, in Air RB, we have BR from 1.0 to 14.0.
If you decreased the BR spread of matches to 0.7, and kept the max BR of 14.0.
That would be the same as decompressing the max BR to 20.0 under the current 1.0 BR spread system.
I don’t think this is a problem. Because the simulation is not generating actual queue times but relative ones. All that is of interest (afaik), is % changes in queue times by changing the BR spread. For that, any abstract rate would do.
I thought this would be the case. It is a problem: You are having the classic survivor bias in your data. You are only measuring people who get matched.
My issues with your strategy are several:
You should create an array of say 10k players. These players are your actual sample. You run the program and enter these 10k players. For each of the 10k players, you record the time of wait. You terminate the run only, when all these 10k players have been matched. So you need to enter more players to keep the program running, but you keep running until the last of your 10k people are matched.
The game has lots of squads, which have to be balanced. So you need not only balance players but groups of players. That is done by the real matchmaker too. So you would need arrays for squads of size 2, 3 and 4. They have the BR of the highest plane in the squad. You have to match those along. You could get estimates for their numbers by counting out scoreboards.
There are groups of planes with uncommon BR. Create one or two such group in the middle and the end the the BR scale. See what they do.
Make sure, any match only contains 0-4 top BR people.
Before you ask such a question, you should define what you mean by fair. I personally do not think that for most BRs, fairness depend on the current ±1 BR spread. Connection, crews, modules, controller, GPU and screen add way more fairness issues than BR.
Also, I wouldn’t want a ±0 BR spread. That would be boring as hell to me in air RB.
Lastly, this is a game, not a field of science. While it may be fun to toy around with data, the revenue for spend time on game research is vastly inferior to that in the real world… ;-)
The important part is that the matchmaker is like a business. Somewhat. In a business, if the rate at which people buy your products is too low, you will go bankrupt. In the matchmaker, if the rate at which people join the matchmaker is too low, they will get frustrated and leave. This effect gets worse the longer waiting times get, so time to start a match actually increases exponentially as the rate at which people join the matchmaker goes down.
I did read the entire post. It is just theoretical proof with little relevance to the reality of the situation.
In reference to BR decompression, I often see people with radical viewpoints, who advocate for massive BR decompression. Their experience is, by all likelihood, on the most popular modes, on the most popular servers, on the most popular battle ratings, etc. To them I bring up the fact that Gaijin has the data on queue time, and that they do not. In principle, it’s incorrect to believe so firmly in an argument, when not only the theoretical foundation is incorrect, but also, there is no data presented in favour of it.
In fact, I have never seen any use of actual queue time data from any proponent of massive decompression.
You haven’t presented queue time data to support your argument either. You’re merely assuming.
The truth is Gaijin’s current model is with a purpose. They’ve seemingly determined that the current state of the BR system brings in the most player engagement and profits, even if it’s at the cost of the user experience.
If the one reason for them not to make the consideration for massive decompression is queue times then why are they so insistent on 16v16? Surely smaller matches would make for lower queue times even in the most unpopulated server at the most unpopulated BR, no?
- Actually, I scaled up/down the player size, but the ratio still didn’t change significantly. ±0.7 is still 10% slower than 1.0. This is really multiplicative (because the algorithmic time complexity of matching a group of games is O(mn)).
- I play props more, more than top tier jets. In fact, I like to play props, and its combat style is more traditional :). The queue time of props is not significantly longer than the popular top tier.
- You said that there are fewer players in some time periods, which is reasonable, so maybe try to open a pilot test of ±0.7 during the time period with more people.
- ASB is a special case with a small number of active players, which is why I didn’t talk about ASB. I also think that ASB should not introduce smaller matchmakers, which does not contradict my main talk about ARB.
In reality, the actual time increase from a 0.7 BR would be far in excess of 10%, likely multiple times the total wait time per player, due to this factor.
In fact, we should not arbitrarily guess the specific multiples of the matching time, because the time complexity of matching a game is O(mn), so in fact it should really be a multiplication relationship. If Gaijin can’t write a matching algorithm with a lower time complexity, I suggest that they recruit some more professional talents. Instead of some embarrassing Game Designers.
6.I understand the example you gave, and I can’t judge its rationality for the time being. But to be honest, even if the maximum BR is expanded to 20.0, it is acceptable to me. Because in addition to the toptier, there is another BR range that needs to be paid attention to, which is 8.0-10.0, and the BR compression in this part is still very serious.
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I don’t disagree with you, it just isn’t the issue. Your initial complaint was the arbitrary choice of time. And it doesn’t matter if he uses 0.01 or 10. It could be 0.01 hours or 10 seconds. Change of relative outcome matters.
Average Max Wait Time for All Battles: 0.93 s
Average Max Wait Time for All Battles: 1.24 s
means an increase of 33%.
In fact, the perfect agreement with 4/3 makes me suspicious that he is basically measuring a relation between his input parameters.
What you want, is to add a new function to my 10k list, namely a chance for “player aborts game”.
The burden of proof is on the person making the claim in the first place, not the person questioning it.
16v16 is better for gameplay in multiple ways. It allows enough players for strategizing, it makes less “meta” aircraft playable, it balances vehicles simply by the higher match size, etc, etc.
It’s sad that you oppose everything you see on the forum.
I’ll keep supporting most of what I see on the forum as most things are great ideas.
@COMBINE
Yes, I am indeed famous for agreeing with most people and supporting them.
Just as you’re arguing against the entirety of the War Thunder playerbase with this topic I’m defending the War Thunder playerbase’s pro-decompression stance from this topic’s pro-compression argument.
War Thunder needs decompression, not the compression you’re arguing for.
And yes, compressing the matchmaker is by definition BR compression, just the other form not as talked about.
OP’s proof is his own experience in which queue times are extremely short. And still even if your queue times are 10 minutes according to his data they’d become 13.5 minutes. Would you rather wait an extra few minute for a more balanced an enjoyable match? Even if you wouldn’t, the vast majority of players would agree to such an exchange.
I can not put into words how much I disagree with you…
I make 13min20s out of his data.
Unless he happens to be located here since the start:
Remaining aircraft in queue: 39
You are still not understanding of the problem in your model. As I have said multiple times, and another player, @Dodo_Dud , has said, you did not consider the fact that players will leave if they are in the queue for too long. They won’t stay forever.
Also, to apply your model in reality at all is laughable.0.0 BR spread is just 3x waiting time of 1.0 BR spread. Would you argue for a 0.0 BR spread then? It’s ridiculous, since effect in reality would be vastly worse.
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Yes, you are correct, I caught the wrong number while skimming through to do the math. Point still stands though.
I don’t use the queue time argument because good lineups fix that for ground, and air doesn’t get impacted because there are no lineups.
Decompression is just objectively better than compression of BRs either compressing the matchmaker, and/or compressing the tech tree BRs.
And in reality, this idea would compress both.
This is why I continually argue against BR compression.
Less than 10% of the air BRs are currently compressed, objectively speaking. [There are 40 air BRs.]
And as people have argued, 13.0 is compressed, 9.0 is compressed… and that’s about it.
“But what about 11.3?” That’s not 11.3 being compressed that’s 13.0 being compressed. You fix 13.0’s compression and it has a knockdown impact to 11.3.
Anecdotal evidence. If you really want to use that, well, I also have some anecdotal evidence for you. I have previously spent more than 10 minutes in an Air RB queue once. Finding no matches, I left. I have also experienced multiple cases where matchmaking took multiple minutes, especially on SA server, and especially around early jet BRs.
See literally any one of my posts on this topic for why this isn’t the case.
The model seems to supply all BRs in about equal abundance. And it obviously does not much else. So no squads, no levels, no bomber limit, no top BR limit. If I omit all that, it will be much easier, sure.
I can easily prove that we need no welfare laws if all are healthy and have jobs. But is that proof relevant?
Could you please quote that definiton? Failing that, could you please explain it very slowly so that we can follow.
And to be on the safe side: You mean with MM compression to switch from 1.0 to 0.7? To avoid misunderstanding your claim.
There are two arguments made on the forums: The correct one and the compression one.
1- Decompression. Decompressing the last holdouts of BRs after an analysis of what those holdouts are. At most a couple hundred vehicles.
2- Compressing the BRs and changing the BRs over over 1000 vehicles for a compressed matchmaker from 4 to 3: 1.0 to 0.7.
This BR compression in the matchmaker would cause more overlapping vehicles, meaning different vehicles like F-104 and Mig-19S would permanently be the same BR despite the Mig-19S being objectively superior.
This would also mean that F-14B and F-15A are permanently the same BR despite them being different.
A 0.7 matchmaker solidifies BR compression into the video game and will never be cured.
This is why 4 is superior to 3, and why we need to oppose this compression in favor of BR decompression in the areas that are still impacted.