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Editado por GhostDog:
7/1/2020 1:47:58 PM
4
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It's not the 1% that are the problem. Most average players can't compete with a top 25-30 % player. The truth is 2 really good players can wreck a lobby. Stop listening to guys like Mtash and True Vanguard tell this won't affect most of the player base. Once you pass the top 50%, the player skill begins to increase exponentially. And this argument about "Oh boy! Now I can try new and fun load outs!" is BS. They're all still running sweaty load outs.
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There's one on the enemy team almost every time, and it takes only one to make your life miserable.
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Unless they live in my matchmaking pool, in which case it's every damn game. You ARE aware that some regions have more pro gamers than others, yeah? Like, entire west coast is toast.
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If you look at it from the perspective of percenatage, yes, finding a person in the top 1% of anything is rare. But in this case, I fell like this is flawed.. hear me out. What makes that player top 1%? Obviously, superior reflexes and eye to hand coordination. But also, time. No one jumps in and is just better than 99% of other players. They play a lot. A lot more than the majority of players. If someone plays PvP say, 4 hours a day, you’re way more likely to match them, than against a person that is just in for the weekly bounties, right? You can get those done in what? An hour or two at most? In a week? Anyway.. seems like your far more likely to come up against people who spend the majority of their time in PVP, who intrinsically should be more skilled than someone who jumps in and out casually. Just my two cents. Thanks:).
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There is a flaw in your calculations - distribution of a population playing at any given moment of time is the same, narrow normal.
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Agree to disagree:). No worries. Seems like your way more likely to run up against people who spend the most time in the playlist.. but I could be wrong too, happens all the time, and I’m okay with it:). Have fun, and stay safe Guardian:).
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Not even remotely true. If it were there'd be an even distribution of employment by wage and industry across any 1 hr sample, and the extreme opposite is true.
