3. asgsafd

asgsafd

TL;DR It’s kind of a wash, almost everyone has blue advantages

Hello once again it’s me, EsportsDS back with another professional LoL stats analysis post. This is a contuation of my last post on the blue side advantage. If you enjoy my posts feel free to check out my earlier ones on ELO, Adjusted ELO, and Peak ELO

Alright this post is mainly about champion blue and red winrates but I gotta do one thing first. As some users pointed out, as I do have “science” in y name maybe I should do a significance test on the data. I decided to do a Chi squared test which helps determine the likelihood of an event happening under a certain assumption. In this case it’s the likelihood of 55% of matches being won by blue if the sides are balanced. To do this you do the sum of ((observed - expected)2)/(expected) for each variable. In this case the equation is: chi2 = ((4599-4188)2)/(4188) +((3777-4188)2)/(4188) = 80.66

Then you check a chart to see where it falls. Since there are two variables, we have one degree of freedom and 80 is wayyy off the right end meaning there is a p-value lower than 0.005 translating to less than 0.5% chance of that happening if the sides were perfectly balanced.

Alright now for the fun part. The most popular question and in my opinion the most interesting was if certain champions benefited from being on blue side more than others. Many people came up with interesting theories as to which might benefit from a specific side and why. So I decided to try to create a table with overall win rate, blue win rate, red win rate and games played. I thought it would be pretty straightforward but I ended up having a lot of trouble with champions entered under multiple name like MF, MissFortune, Miss Fortune, Miss fortune, miss fortune etc. So I had to individually label everything that was ever used and then make a lookup table and lookup function. I also had to teach myself a lot more about overloading operators in python which will probably also help me in later posts. Anyways here’s the list!

I’ve also included some for explanation. Feel free to leave your own explanations and I might put them on the list!

number champion overall win% blue win% red win% games comments
1 Aatrox 0.588 0.653 0.538 114 .
2 Ahri 0.516 0.573 0.458 1103 .
3 Akali 0.474 0.5 0.455 38
4 Alistar 0.495 0.554 0.441 2281
5 Amumu 0.435 0.531 0.356 108
6 Anivia 0.469 0.554 0.398 162
7 Annie 0.499 0.551 0.452 893
8 Ashe 0.544 0.629 0.47 342 Big gap...
9 Aurelion Sol 0.0 0.0 0.0 4 0-4 GG well it’s equal red/blue winrate
10 Azir 0.533 0.583 0.472 1146
11 Bard 0.537 0.586 0.486 516 A lot of people though he would be higher red because of botlane escape route.
12 Blitzcrank 0.503 0.567 0.456 157
13 Brand 0.308 0.462 0.154 26
14 Braum 0.474 0.515 0.431 1823
15 Caitlyn 0.479 0.535 0.417 1068
16 Cassiopeia 0.501 0.571 0.442 383
17 Cho'Gath 0.471 0.53 0.413 204
18 Corki 0.486 0.528 0.447 2401
19 Darius 0.525 0.545 0.509 101
20 Diana 0.502 0.568 0.436 325
21 Dr. Mundo 0.445 0.488 0.408 530
22 Draven 0.529 0.595 0.464 221
23 Ekko 0.515 0.58 0.445 678
24 Elise 0.513 0.55 0.473 2318
25 Evelynn 0.503 0.557 0.449 648
26 Ezreal 0.471 0.502 0.44 1791
27 Fiddlesticks 0.455 0.508 0.392 112
28 Fiora 0.493 0.534 0.451 536
29 Fizz 0.542 0.603 0.486 605
30 Galio 0.4 0.4 0.4 35 the only other champ with equal win rates
31 Gangplank 0.488 0.525 0.436 408
32 Garen 0.2 0.25 0.0 5
33 Gnar 0.507 0.538 0.475 1157
34 Gragas 0.515 0.562 0.469 2430
35 Graves 0.498 0.549 0.444 1565
36 Hecarim 0.494 0.563 0.425 735
37 Heimerdinger 0.429 1.0 0.0 7
38 Illaoi 0.5 0.333 1.0 4 higher red but only 4 games
39 Irelia 0.487 0.533 0.442 705
40 Janna 0.518 0.573 0.464 1759
41 Jarvan IV 0.481 0.52 0.441 1403
42 Jax 0.474 0.519 0.421 390
43 Jayce 0.462 0.496 0.426 439 pretty close for how many games
44 Jhin 0.446 0.477 0.422 148
45 Jinx 0.498 0.558 0.438 725
46 Kalista 0.563 0.596 0.525 1661 Kalista is pretty busted
47 Karma 0.459 0.528 0.382 333
48 Karthus 0.478 0.536 0.422 314
49 Kassadin 0.521 0.567 0.473 755
50 Katarina 0.43 0.41 0.447 86 Higher red, highish games
51 Kayle 0.467 0.526 0.416 287
52 Kennen 0.496 0.549 0.44 413
53 Kha'Zix 0.475 0.537 0.413 642
54 Kindred 0.48 0.534 0.424 588
55 Kog'Maw 0.502 0.545 0.452 931
56 LeBlanc 0.508 0.529 0.487 1161
57 Lee Sin 0.497 0.535 0.462 1928
58 Leona 0.481 0.52 0.441 749
59 Lissandra 0.522 0.563 0.48 1106
60 Lucian 0.486 0.532 0.445 2763
61 Lulu 0.465 0.511 0.413 2048
62 Lux 0.412 0.527 0.321 291 20% gap
63 Malphite 0.489 0.514 0.464 476
64 Malzahar 0.484 0.533 0.438 31
65 Maokai 0.509 0.578 0.451 2013
66 Master Yi 0.476 0.5 0.455 21
67 Miss Fortune 0.561 0.599 0.521 337 Wtf MFi has high winrate
68 Mordekaiser 0.692 0.857 0.5 26 super high blue, not many games though
69 Morgana 0.523 0.565 0.475 1418
70 Nami 0.463 0.506 0.411 745
71 Nasus 0.534 0.586 0.493 251
72 Nautilus 0.464 0.51 0.418 1376
73 Nidalee 0.538 0.577 0.494 1209
74 Nocturne 0.433 0.521 0.361 215 decent gap
75 Nunu 0.525 0.594 0.464 556
76 Olaf 0.503 0.564 0.443 330
77 Orianna 0.466 0.523 0.411 1175
78 Pantheon 0.491 0.541 0.437 214
79 Poppy 0.535 0.594 0.469 964
80 Quinn 0.494 0.493 0.495 174 slightly higher red
81 Rammus 0.484 0.5 0.466 128
82 Rek'Sai 0.517 0.572 0.459 2304
83 Renekton 0.507 0.557 0.46 768
84 Rengar 0.477 0.509 0.443 426
85 Riven 0.53 0.571 0.504 198 >50 red
86 Rumble 0.478 0.545 0.406 1122
87 Ryze 0.518 0.58 0.437 821
88 Sejuani 0.479 0.505 0.452 560
89 Shaco 0.375 0.5 0.25 8
90 Shen 0.495 0.545 0.438 1000
91 Shyvana 0.494 0.519 0.47 640
92 Singed 0.578 0.711 0.444 90
93 Sion 0.525 0.548 0.5 261
94 Sivir 0.526 0.575 0.479 2142
95 Skarner 0.481 0.656 0.362 79
96 Sona 0.521 0.573 0.466 695
97 Soraka 0.517 0.53 0.5 143
98 Swain 0.467 0.568 0.375 92
99 Syndra 0.457 0.493 0.424 282
100 Tahm Kench 0.493 0.564 0.413 294
101 Talon 0.367 0.444 0.333 30
102 Taric 0.441 0.509 0.392 127
103 Teemo 0.667 0.6 0.75 9 Highest winrate champ in Pro LoL, Rofl
104 Thresh 0.52 0.584 0.461 3076
105 Tristana 0.471 0.531 0.411 1006
106 Trundle 0.526 0.56 0.494 1041
107 Tryndamere 0.5 0.533 0.478 38
108 Twisted Fate 0.561 0.605 0.516 756
109 Twitch 0.501 0.557 0.445 527
110 Udyr 0.404 0.467 0.318 104
111 Urgot 0.5 0.568 0.44 204
112 Varus 0.478 0.544 0.419 680
113 Vayne 0.487 0.543 0.428 854
114 Vel'Koz 0.486 0.588 0.389 35
115 Vi 0.499 0.578 0.431 457
116 Viegar 0.472 0.563 0.4 72
117 Viktor 0.459 0.523 0.395 1258
118 Vladimir 0.477 0.539 0.42 373
119 Volibear 0.46 0.481 0.443 113
120 Warwick 0.5 0.684 0.348 42
121 Wukong 0.372 0.436 0.327 94
122 Xerath 0.449 0.502 0.402 448
123 Xin Zhao 0.472 0.548 0.387 159
124 Yasuo 0.503 0.497 0.509 330
125 Yorick 0.426 0.531 0.333 68
126 Zac 0.527 0.584 0.465 330
127 Zed 0.578 0.628 0.521 739 Really high winrate and playrate
128 Ziggs 0.477 0.495 0.46 390
129 Zilean 0.524 0.604 0.455 229
130 Zyra 0.52 0.563 0.474 431

Please tell me what you think. My eyes and brain hurt from staring at these numbers. As always thank you for reading and I’m open to more post suggestions. If you like this post and want to see more like it feel free to follow my twitter for updates. Also shout out to whoever gave me gold on my last one.

Finally I am taking requests for stats from journalists and team analysts. I have data on matches, game length, teams, tournaments, champions, players, kills, deaths, assists, dragons, barons, towers, cs, gold, summoner spells, items. Inquire at [email protected]

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