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math behind TO Reward


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thank you AbsoluteZero for your confirm :-)

 

now, like you say, we try how to calculate the amount of crystal rewards for each player. Of course, it's not based only on score, the reward doesn't follow the score: I didn't found all the formulas (yet ! ... I hope :-)  ) but in some way the formulas must have something to do with the number of players (on the same team), and may be ... something to do with the gap from a player to another (but I am not sure at all, it's only an idea)

 

stay tuned ,

 

Andrea

Edited by andreaNEW

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thank you AbsoluteZero for your confirm :-)

 

now, like you say, we try how to calculate the amount of crystal rewards for each player. Of course, it's not based only on score, the reward doesn't follow the score: I didn't found all the formulas (yet ! ... I hope :-)  ) but in some way the formulas must have something to do with the number of players (on the same team), and may be ... something to do with the gap from a player to another (but I am not sure at all, it's only an idea)

 

stay tuned ,

 

Andrea

An observation I made early on was that those players who had a score above the Score Mean, also had a reward above the Reward Mean. Vice versa for those below the mean.

I had a tinker with gaps and standard deviation but nothing was obvious.

 

Logarithms seem to be involved somewhere.

If you get the scores then change them to a log (doesn't matter what base), then do the same for the rewards for each player, plot them on a scatter, you will always get a straight line!

Similarly, if you just get the raw scores and raw rewards and plot them, they give you a near perfect power curve.

How the gradient is worked out or how the battlefund gets integrated is beyond me.

So wish I paid attention now in Math class.

 

uFCbovo.png

 

Edit:

Woke up this morning and thought we're looking for y=mx+c, dy / dx would give you the gradient (m) of the straight line, ie. the difference in y divided by the difference in x. Do the sums and the gradient and I get 1.501192 in excel which is not far off the actual gradient as given by the scatter diagram 1.5008. Need to figure how to get to that point when we don't have the y values in the first place.

Edited by AbsoluteZero

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unfortunately I don't have any conclusion, but we can see something : the total score is 1836, the total reward are 1408. 

the first player 

score 289 (15.74% of 1836 total score)

reward 273 (19.39% of 1408 total reward)

 

the last player

score 110 (5.99% of total score)

reward 62 (4.40% of total reward)

 

then .. it's not a simple percentage, but there is something else ...

Like you, I take print screen when a game ended, and I have some example. 

 

 

 

The fund isn't entirly oven to the team, a small part is left in the server

 

It's a nice challenge :-)

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Its simple, here is the formula of battle reward calculation.

 

Battlefund -> HeroPlayer

 

:P

 

All other players should live from the golds and crystal boxes.

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An observation I made early on was that those players who had a score above the Score Mean, also had a reward above the Reward Mean. Vice versa for those below the mean.

I had a tinker with gaps and standard deviation but nothing was obvious.

 

Logarithms seem to be involved somewhere.

If you get the scores then change them to a log (doesn't matter what base), then do the same for the rewards for each player, plot them on a scatter, you will always get a straight line!

Similarly, if you just get the raw scores and raw rewards and plot them, they give you a near perfect power curve.

How the gradient is worked out or how the battlefund gets integrated is beyond me.

So wish I paid attention now in Math class.

 

 

uFCbovo.png

 

 

Edit:

Woke up this morning and thought we're looking for y=mx+c, dy / dx would give you the gradient (m) of the straight line, ie. the difference in y divided by the difference in x. Do the sums and the gradient and I get 1.501192 in excel which is not far off the actual gradient as given by the scatter diagram 1.5008. Need to figure how to get to that point when we don't have the y values in the first place.

Are you actually a professor or what  :blink:

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Success

 

The formula to distribute the battlefund to players, as it turned out, was not too complicated.

 

Video of values being inputted.

 

Regards, @AbsoluteZero B)

 

 

Thanks to @andreaNEW for working out the battlefund split for the teams.

 

 

you did it ! great job @AbsoluteZero , more faster than me :-)

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Just listen the latest video blog by developers (by non English language).

 

A huge change is planned - the formula to distribute the battlefund to players will be changed (inside 1 team, the division between blue/red teams will remain the same).

They will start to use a linear distribution, so there will be reason not to leave the battle if you are far away in the bottom, but not such a big reason to use supplies if you are on the top. :)

Edited by r_Venividi0

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Just listen the latest video blog by developers (by non English language).

 

A huge change is planned - the formula to distribute the battlefund to players will be changed (inside 1 team, the division between blue/red teams will remain the same).

They will start to use a linear distribution, so there will be reason not to leave the battle if you are far away in the bottom, but not such a big reason to use supplies if you are on the top. :)

Interesting. I would have thought they would want to encourage supply use. Let's hope this planned change is fairer and better. If not, they should leave it alone or plan something else.

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All very interesting. Wish i could check it myself to understand it properly. And changing the battle fund distribution? Well well. It could be interesting.

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