That’s not how a gaussian works and they are talking about percentiles anyways. An 80% player is within 1 sigma as the ± 1 sigma band contains approximately 68% of the population (0 sigma would be the median player, i.e. a 50% player). So a player at exactly +1 sigma would be an 84% player. Top 0.1% is about 4.5 sigma.
Updated the post since you guys were asking:
UPDATE: Okay, some people have brought up what percentage of people we’re talking about in each of the categories above. We can crunch the sample we have (N=208) through a standard deviation calculator, assuming the distribution is normal for these purposes and the sample representative, and see what percent of players are better or worse than a given average relative position on their service record. The standard deviation on the sample is 12.502, on a mean of 51.827, if you want to follow along at home. What it comes to is:
50% player (by average relative position) in the sample: Better than 44.2% of all players.
67% player: Better than 88.8% of all players
75% player: Better than 96.8% of all players
80% player: Better than 98.8% of all players.
You can run the same math in reverse, too. Assuming all the many many assumptions above, for an average score of 1500 in ground RB, which is equivalent to the 61% percentile of game results, you can infer that 76.7% of ground RB players will not be able to achieve that score.
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For future reference, here’s a breakdown of average relative position values (%ARP) and population of active gamers who can equal or beat them (%POP), assuming representative sample, normal distribution, and sigma and mean as given above:
| %ARP | %POP |
|---|---|
| 50 | 55.81 |
| 55 | 39.98 |
| 60 | 25.66 |
| 65 | 14.60 |
| 70 | 7.30 |
| 75 | 3.19 |
| 80 | 1.21 |
| 85 | 0.40 |
| 90 | 0.11 |
| %POP | %ARP |
|---|---|
| 50 | 51.8 |
| 45 | 53.4 |
| 40 | 55.0 |
| 35 | 56.6 |
| 30 | 58.4 |
| 25 | 60.3 |
| 20 | 62.3 |
| 15 | 64.8 |
| 10 | 67.8 |
| 5 | 72.4 |
| 1 | 80.9 |
| 0.1 | 90.5 |
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This is a very good post but it cannot be, i cannot possibly be better than 98.8% of all players in ground arcade battles. I can do 40k mission score in 2.30h MAXIMUM if i play rankVII, even less if i play something broken like the italian sherman lineup at rank3 (7k avg.mission score per battle, 6 battles per hour).
Going of your stats, yes ,yes you are XD
May i ask what your average team placement is for arcade ground?
Here’s one thing the OP did not consider:
- Rank bonus.
OP considers only 1.0 rank bonus and only mode based multipliers.
Dunno ground multipliers, but IIRC for air we had…
Rank 1-4: 0.9
Rank V: 1.0
Rank VI: 1.1
Rank VII. 1.2
Rank VIII: Can’t remember.
The new profile cards have made it much harder than it was to check other players stats, sadly. I could never have scraped this same data today. But I think the math holds up, it’s certainly never been challenged.
But IF your ground AB average score was 7k per game, another way to look at it is these numbers suggest a standard 16 player side has about 20k score on average to split between them in an average AB game. If you’re taking a third of it on average, that leaves 2/3 for the other 15 players, so to be on a team with you they’d only be making on average about 4-500 score per game. Do the math on how long it will take them to do this event under those conditions… It’s not pretty. I don’t think the players on either team would much enjoy that kind of results differential.
There, I’ve proved mathematically that seal clubbing is bad. :)
No way to consider it, starting from the initial data set. But given that it’s likely offset in many modes by smaller match sizes and more ODLing at higher tiers (reducing total available score) I suspect the impact isn’t much. If anything it might not offset those factors enough. The bigger effect will be if you slide yourself up or down that score-per-game line in the original graphs by playing at a level either too easy or too hard for your skill level.
Sorry for the late response, my average team placement is 80% in 13674 battles, but take in consideration that i also play navalAB in which i’m really bad so i rarely place top3…
Oh yeah, you’re absolutely better than almost all players. Are you familiar with a normal distribution bell curve?
If you are, then imagine a player with an average placement of 50% and think of how their curve will look, and now imagine how yours at 80% will look.
To have an average of 80% half your games will fall above that and half will fall below (on average). BUT Since you cannot get better than first (100%) then if you get one game lower than 60% you have to compensate for that by getting more than one game above 80%. So say you get 40% in one game you have to get two games at 100% to compensate for the change in average. So the amount of games you have above 80% placement has to be drastically more than the number of games below to achieve the average of 80%.
Just one game where you are last (0%) has to be compensated with 4 games att 100% to get an average of 80% (400/5=80). So you can imagine how often you have to get first or second in the team to maintain an average of 80% :)
I hope I explained it well enough :)
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