function a = LoLstat(n)
C=randperm(9, 4);
C=2*sort(C)+[14 28 42 56];
T=zeros(1, C(1,1));
J=zeros(1, C(1,2)-C(1,1));
M=zeros(1, C(1,3)-C(1,2));
B=zeros(1, C(1,4)-C(1,3));
S=zeros(1, 100-C(1,4));
LT = length(T);
LJ = length(J);
LM = length(M);
LB = length(B);
LS = length(S);
Tw=zeros(1, LT);
Jw=zeros(1, LJ);
Mw=zeros(1, LM);
Bw=zeros(1, LB);
Sw=zeros(1, LS);
Tp=zeros(1, LT);
Jp=zeros(1, LJ);
Mp=zeros(1, LM);
Bp=zeros(1, LB);
Sp=zeros(1, LS);
T=0.9*ones(1,LT)+0.1*rand(1, LT);
J=0.9*ones(1,LJ)+0.1*rand(1, LJ);
M=0.9*ones(1,LM)+0.1*rand(1, LM);
B=0.9*ones(1,LB)+0.1*rand(1, LB);
S=0.9*ones(1,LS)+0.1*rand(1, LS);
k=0;
while k<=n
Tx = randperm(LT, 2);
Jx = randperm(LJ, 2);
Mx = randperm(LM, 2);
Bx = randperm(LB, 2);
Sx = randperm(LS, 2);
x1 = Tx(1,1);
Tp(1, x1)=Tp(1, x1)+1;
x2 = Jx(1,1);
Jp(1, x2)=Jp(1, x2)+1;
x3 = Mx(1,1);
Mp(1, x3)=Mp(1, x3)+1;
x4 = Bx(1,1);
Bp(1, x4)=Bp(1, x4)+1;
x5 = Sx(1,1);
Sp(1, x5)=Sp(1, x5)+1;
y1 = Tx(1,2);
Tp(1, y1)=Tp(1, y1)+1;
y2 = Jx(1,2);
Jp(1, y2)=Jp(1, y2)+1;
y3 = Mx(1,2);
Mp(1, y3)=Mp(1, y3)+1;
y4 = Bx(1,2);
Bp(1, y4)=Bp(1, y4)+1;
y5 = Sx(1,2);
Sp(1, y5)=Sp(1, y5)+1;
Red=(0.9+0.2*rand(1))*T(1, x1)+(0.9+0.2*rand(1))*J(1, x2)+(0.9+0.2*rand(1))*M(1, x3)+(0.9+0.2*rand(1))*B(1, x4)+(0.9+0.2*rand(1))*S(1, x5);
Blue=(0.9+0.2*rand(1))*T(1, y1)+(0.9+0.2*rand(1))*J(1, y2)+(0.9+0.2*rand(1))*M(1, y3)+(0.9+0.2*rand(1))*B(1, y4)+(0.9+0.2*rand(1))*S(1, y5);
if Red>Blue
Tw(1, x1)=Tw(1, x1)+1;
Jw(1, x2)=Jw(1, x2)+1;
Mw(1, x3)=Mw(1, x3)+1;
Bw(1, x4)=Bw(1, x4)+1;
Sw(1, x5)=Sw(1, x5)+1;
else
Tw(1, y1)=Tw(1, y1)+1;
Jw(1, y2)=Jw(1, y2)+1;
Mw(1, y3)=Mw(1, y3)+1;
Bw(1, y4)=Bw(1, y4)+1;
Sw(1, y5)=Sw(1, y5)+1;
end
k=k+1;
end
Twr=Tw./Tp;
Jwr=Jw./Jp;
Mwr=Mw./Mp;
Bwr=Bw./Bp;
Swr=Sw./Sp;
Tpr=(1/n)*Tp;
Jpr=(1/n)*Jp;
Mpr=(1/n)*Mp;
Bpr=(1/n)*Bp;
Spr=(1/n)*Sp;
[T; Tpr; Twr]
[J; Jpr; Jwr]
[M; Mpr; Mwr]
[B; Bpr; Bwr]
[S; Spr; Swr]
sum(Tpr)
sum(Jpr)
sum(Mpr)
sum(Bpr)
sum(Spr)
sum(Tpr.*Twr./2)
sum(Jpr.*Jwr./2)
sum(Mpr.*Mwr./2)
sum(Bpr.*Bwr./2)
sum(Spr.*Swr./2)
TwrT=Twr./T
JwrJ=Jwr./J
MwrM=Mwr./M
BwrB=Bwr./B
SwrS=Swr./S
length([T J M B S])
plot(T, Twr, 'red')
hold on
plot(J, Jwr, 'cyan')
hold on
plot(M, Mwr, 'green')
hold on
plot(B, Bwr, 'blue')
hold on
plot(S, Swr, 'magenta')
이대로 복사하셔서 n에 원하는 숫자를 넣어소 매틀랩에서 돌리시면 자동으로 결과값이 나옵니다. 실행할 때마다 조금씩 달라집니다.
이 밑은 영상에서 보여드린 시행에서의 결과값입니다. 200만 게임을 돌렸네요.
위에서 5번째까지의 행렬은 1행 - 캐릭터 성능, 2행 - 캐릭터 픽률, 3행 - 캐릭터 승률 순이며,
그 아래 2.0 5개는 각 라인 별 픽률 총 합이며,
그 아래 0.5 5개는 ( (각 캐릭터 픽률)*(각 캐릭터 승률) 의 총합) / 2 입니다. (2로 나누는 건 한 게임마다 각 라인 별 2개 캐릭터가 출전하므로 두 배로 계산되기 때문.)
그 아래 XwrX (X = T, J, M, B, S) 는 각 캐릭터 별로 승률 / 성능 값입니다. 같은 승률을 내기 위해 필요했던 성능 값이 작을 수록 커집니다.
그 아래 100은 총 캐릭터 수 100을 뜻합니다.
여기부터는 실제로 출력된 결과.
>> LoLstat(2000000)
ans =
0.9857 0.9482 0.9044 0.9069 0.9426 0.9523 0.9343 0.9228 0.9518 0.9469 0.9790 0.9145 0.9233 0.9962 0.9353 0.9129
0.1253 0.1244 0.1251 0.1253 0.1249 0.1255 0.1251 0.1252 0.1247 0.1250 0.1245 0.1247 0.1253 0.1250 0.1247 0.1252
0.5956 0.5163 0.4217 0.4253 0.5040 0.5237 0.4848 0.4610 0.5244 0.5129 0.5825 0.4430 0.4613 0.6189 0.4872 0.4379
ans =
0.9682 0.9306 0.9669 0.9604 0.9983 0.9487 0.9834 0.9951 0.9517 0.9059 0.9409 0.9121 0.9453 0.9456 0.9753 0.9001
0.1252 0.1252 0.1249 0.1250 0.1250 0.1253 0.1251 0.1252 0.1247 0.1250 0.1244 0.1251 0.1251 0.1250 0.1247 0.1251
0.5352 0.4544 0.5344 0.5199 0.6014 0.4904 0.5701 0.5946 0.5007 0.3988 0.4773 0.4143 0.4837 0.4870 0.5500 0.3876
ans =
0.9282 0.9212 0.9022 0.9367 0.9971 0.9826 0.9661 0.9638 0.9716 0.9486 0.9426 0.9352 0.9839 0.9812 0.9957 0.9745
0.1251 0.1254 0.1247 0.1249 0.1247 0.1251 0.1252 0.1256 0.1247 0.1249 0.1246 0.1250 0.1251 0.1251 0.1248 0.1250
0.4351 0.4188 0.3799 0.4541 0.5848 0.5529 0.5181 0.5124 0.5297 0.4792 0.4662 0.4475 0.5562 0.5492 0.5810 0.5349
ans =
0.9161 0.9346 0.9879 0.9867 0.9448 0.9644 0.9791 0.9921 0.9455 0.9477 0.9342 0.9356 0.9396 0.9877 0.9996 0.9277 0.9687 0.9185
0.1115 0.1110 0.1110 0.1112 0.1112 0.1111 0.1105 0.1110 0.1111 0.1114 0.1111 0.1113 0.1109 0.1113 0.1113 0.1111 0.1110 0.1109
0.4143 0.4530 0.5691 0.5655 0.4740 0.5163 0.5506 0.5780 0.4777 0.4836 0.4538 0.4552 0.4642 0.5679 0.5935 0.4370 0.5269 0.4197
ans =
1 ~ 20번 열
0.9808 0.9285 0.9294 0.9692 0.9388 0.9556 0.9705 0.9193 0.9973 0.9038 0.9811 0.9138 0.9223 0.9728 0.9324 0.9371 0.9546 0.9448 0.9449 0.9327
0.0588 0.0588 0.0588 0.0586 0.0586 0.0592 0.0591 0.0586 0.0587 0.0589 0.0590 0.0589 0.0588 0.0588 0.0588 0.0592 0.0588 0.0588 0.0586 0.0586
0.5628 0.4513 0.4537 0.5366 0.4727 0.5091 0.5398 0.4314 0.5967 0.4032 0.5638 0.4204 0.4384 0.5463 0.4569 0.4704 0.5094 0.4859 0.4888 0.4616
21 ~ 34번 열
0.9099 0.9961 0.9604 0.9438 0.9921 0.9411 0.9432 0.9428 0.9145 0.9955 0.9554 0.9789 0.9553 0.9848
0.0585 0.0586 0.0588 0.0588 0.0587 0.0589 0.0592 0.0588 0.0586 0.0591 0.0588 0.0590 0.0589 0.0589
0.4159 0.5910 0.5177 0.4850 0.5865 0.4807 0.4839 0.4819 0.4233 0.5902 0.5062 0.5569 0.5087 0.5722
ans =
2.0000
ans =
2.0000
ans =
2.0000
ans =
2.0000
ans =
2.0000
ans =
0.5000
ans =
0.5000
ans =
0.5000
ans =
0.5000
ans =
0.5000
TwrT =
0.6042 0.5445 0.4662 0.4690 0.5348 0.5499 0.5189 0.4996 0.5510 0.5417 0.5951 0.4844 0.4997 0.6212 0.5209 0.4797
JwrJ =
0.5528 0.4883 0.5527 0.5414 0.6024 0.5169 0.5798 0.5975 0.5261 0.4403 0.5073 0.4542 0.5117 0.5151 0.5639 0.4306
MwrM =
0.4688 0.4546 0.4211 0.4847 0.5864 0.5627 0.5363 0.5316 0.5452 0.5051 0.4946 0.4785 0.5653 0.5598 0.5835 0.5489
BwrB =
0.4523 0.4847 0.5760 0.5731 0.5017 0.5353 0.5624 0.5826 0.5053 0.5103 0.4858 0.4866 0.4940 0.5749 0.5938 0.4711 0.5439 0.4569
SwrS =
1 ~ 20번 열
0.5738 0.4860 0.4882 0.5536 0.5035 0.5327 0.5562 0.4692 0.5983 0.4461 0.5746 0.4600 0.4753 0.5616 0.4900 0.5020 0.5336 0.5143 0.5173 0.4948
21 ~ 34번 열
0.4571 0.5933 0.5390 0.5138 0.5912 0.5109 0.5131 0.5111 0.4629 0.5929 0.5298 0.5690 0.5325 0.5810
ans =
100
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