Clash Beta data analysis

  1. 1. Introduction
  2. 2. Context
    1. 2.1. League of Legends.
    2. 2.2. Clash
  3. 3. Game
  4. 4. Ranks
  5. 5. Champions
  6. 6. Conclusion
  7. 7. Annexes

Clash banner

Review of Clash by the numbers, from analyzing impact of scouting system on champion picks and bans to rank-wise fairness inside brackets.

Introduction

Clash is one of the biggest project in League of Legends, and aims to enhance the competitive environment of the game. First announced more than 2 years ago, it has known lots of technical and scalibility issues which postponed its release for years. After more or less successful betas, it is finally ready for official release.

Having multiple questions about Clash, about the competitive difference with SoloQ, the impact on the playerbase, or the competitive fairness, I decided to do a data analysis targeting Clash games. I gathered over 4 millions League of Legends games data on the EUW Clash week-end of the 5th and 6th October 2019, including more than 85.000 Clash games, and the previous week-end, using the Riot Games API. I focused the analysis over three main points : the games, the player ranks, and the champions.

Context

A little summary of what is League of Legends and Clash. Skip it if you already know.

League of Legends.

League of Legends (LoL) is a competitive video game, especially a MOBA (Multiplayer Online Battle Arena), lauched in 2009 by Riot Games and in constant development until now, and derived from the Warcraft III mod DotA. A game lasts around 20-40 minutes and confronts 10 players in two teams of 5, the goal is to take over the enemy base. Each player control a champion, an entity with its own stats, unique abilities, and customizable with items, themselves with specific caracterisics and particularities.

Clash

While Riot Games mostly handled the team aspect of the competition only at the professional level and leaving “low level” tournament to third party structures, they finally decided to organize tournament events opened to all League of Legends ranked players while maintaining the competitive integrity : Clash.
Clash takes place the week-end, one tournament on Saturday, and another one and Sunday. The week prior to Clash, all players can assemble in teams. When the tournament begins, teams are gathered in groups of 8 based on their ranking in the competitive game modes. They will then play in a bracket format (quarter finale, semi finale, finale) with a loser bracket. Before each game each team will be able to consult stats on the other team, in order to find their strengths and weaknesses and play accordingly, during the draft, the moment before the game where players can pick or ban champions, and during the game itself.
Clash FAQ for more details.

Game

One of my first question was how much Clash games are played and was this the reason behind the multiples crashes during previous betas, so I gathered all the games played during Clash week-end, and the ones from the previous week-end as control. Figure 1 are histograms of games creation by slices of 10 minutes. On the bottom one, on orange are represented the Clash games. It clearly shows abnormal spikes and a far higher load, while there is barely 9k games per 10 minutes in normal situation, it reaches almost 13k in 10 minutes on the Sunday. It’s important to note that in this version, players were free to launch their first game any time between 7pm and 9pm depending on their rank, while in the first events, teams of the same rank all had to begin at the same time, putting a lot more strain on the servers. This delayed game launches is a way to spread the effort and avoid crashes.

![Games creation graphs](https://hextechlab.com/img/clash/games_creation.png data-zoomable)

Figure 1 : Histograms for games creation

Player-wise, if a little more than a half (52%) of the players played Clash only one day of the week-end, it is still designed to make them play more than one game. In this Clash session, the losing bracket ensures teams to play at least twice (and at least three times in the new system). Figure 2 represents the number of Clash games by players. We can see that 15 players played 7 games over the week-end. While I can’t be sure exactly why, my best bet is it comes from broken brackets where there were too much teams not able to play after registering, and after one game in a first bracket, a team would be relocated in a second bracket where they would have to to a “first” game once again.

Games by player

Figure 2 : Number of games by player

I did not dig up more on that side, but we can say that Clash has a big impact on the number of games played and gathers a lot of players without draining too much from the other modes, showing what could be interpreted as a good way to attract new or returning players.

Ranks

One of the most important part of the analysis, about one of the key element of Clash, is the competitive fairness of the tournament. And measuring that is very tricky and full of arbitrary and contestable decisions. Despite that, I still tried to create some metrics to represent the competitive fairness of each Clash bracket.

Note that Clash system ranks teams in 4 different tiers, based on players SoloQ/Flex rank, and I don’t have access to these Clash tiers, only to the SoloQ/Flex rank.

First of all a little review on rank distribution. Figure 3 allows us to see this distribution and compare it to Clash players. It also show the percentage of player in each division which participated in Clash, and the clear trend that the higher in the rank a player is, the higher is the chance for this player to participate in Clash. Two explainations I see, and that can be combined quite well, are Clash targeting competition and competitive players tends to be higher in the rank, and that some low rank players just don’t play enough to get higher, hence not playing for Clash.

Games by player

Figure 3 : Rank distribution of all ranked players and Clash only players

Time for definition for the metrics.

  • Level : Translation in number of LoL tier (Challenger, Iron…), starting with Iron = 1 up to Challenger = 9.
  • (Team) Level : Each player in the team having a level, the team level is the mean of these value.
  • Disparity : Same as team level, except we take the variance instead of the mean. It serves to spot inconsistency in a players in a same team, e.g. 1 Diamond player and 4 Bronze players.
  • Level Variance : Inside a bracket, the variance of teams Level.
  • Disparity Variance : Inside a bracket, the variance of teams Disparity.
  • Level Amplitude : Difference between the highest and lowest Team Levels in a same bracket.

So, why so much metrics? First, we are dealing with two different entities : teams and brackets, and they each need their own metrics. Then, just dealing with the mean level of a team hides the dimension of the composition of the team, and it’s where the Disparity metric comes in. I personally think that teams should be matched considering the team composition instead of only a mean value of all the players level.
Here is an example of how the metrics work. Take a team of 3 Diamonds (level=6), 1 Platinum (level=5) and 1 Gold (level=4). The Team Level is 5.4 and as each player are around the same level (even if the Gold - Diamond gap is still big), the Disparity is 0.8. Compare it with a team composed of 1 Challenger (level=9), 1 Grandmaster, 1 Diamond, and 2 Bronze, you’ll get a Team Level of 5.4 too. However, the Disparity here is 10.8 and reveals the big difference between the top level player (Challenger, Grandmaster and arguably Diamond) and the Bronze players. To have fair games, I do not think these two teams should be matched against each other.

In this perspective, I computed these metrics over more than 4.200 brackets.

Figure 4 shows the distribution for Disparity Variance by bracket and is quite skewed on the good side. Most of the brackets don’t have a team really sticking out of the group, but as a large part (more than 25%) still have quite high disparity, I think there is still a lot a room to improvement.

Games by player

Figure 4 : Disparity Variance inside brackets

Figure 5 shows the distribution for Level Variance by bracket and the results are quite good giving that almost three quarters of the brackets have less than 0.1 Level Variance. However, the outliers, where the Level Variance is more than 0.5, are mostly because of some teams with Platinum or Diamond players that were matched with others teams with Grandmaster and even Challenger players. Maybe at this level, it is hard to find enough teams to match together with a close enough level.

Games by player

Figure 5 : Level Variance inside brackets

Figure 6 shows the Level Amplitude inside brackets and tells another story. More than one quarter of the brackets have a Level Amplitude of 1 or more. Put into perspective, it means than more than at 1000 teams were matched in a bracket with another team at one full tier higher (e.g 5 Gold vs 5 Platinum) which is very concerning.

Games by player

Figure 6 : Level Amplitude inside brackets

This concern made me ask another question, which is about the chances to win once the bracket is created, even before a game started.
The team with the unique lowest Level in the bracket won 3 games (i.e. reached and won the finale) only in 8% of the brackets while the team with the unique highest Level in 20%, for a base probability at 12.5% (1/8).
On the side of Disparity, we also have a clear trend. The team with a lowest unique Disparity wins in 17% of brackets, while the one with the highest Disparity wins in only 9% of brackets.
While these effects were foreseeable and can be considered as normal, I don’t think it’s OK in an environment based on fair competition. Having more than twice the chances of winning of another team in your bracket only because you were put in this bracket does not feel fair.

This wraps up the analysis on ranks. The system to create fair brackets works well but still presents some critical flaws that should be worked on.

Champions

Last part but not least, I wanted to measure how much of a different game LoL is between SoloQ/Flex and Clash. And of course, it goes by comparing champion statistics.

First of all, the banrates. Considering one of the biggest change with SoloQ is the scouting phase, I was expecting a lot of changes in banrates.

Figure 7 is a visual representation of the champion banrates, more precisely the number of champions by banrate for SoloQ, Flex and Clash. The format might be unusal, but it allows to show some interesting points.

First, SoloQ and Flex banrates distributions are very alike and can be summarize in two parts : a lot of champions are mostly unconcerned by bans (the big bars on the left) and some champions have a far higher banrates (the little points toward the right). For Clash, these two parts are far less dominant : there are far less champions that are almost never banned, and also far less champions with very high banrates.

Games by player

Figure 7 : Number of champion by banrate

Particular differences in bans between SoloQ and Clash :

  • Champions that are far less banned in Clash:
    • Pyke : 52% ↘ 22%
    • Blitzcrank : 40% ↘ 15%
    • Zed : 50% ↘ 24%
    • Evelynn : 29% ↘ 8%
    • Master Yi : 34% ↘ 13%
  • Champions that are far more banned in Clash:
    • Kai’Sa : 10% ↗ 24%
    • Thresh : 7% ↗ 20%
    • Xayah : 6% ↗ 18%
    • Vayne : 10% ↗ 21%
    • Jinx : 6% ↗ 17%

Honorable mention for Yasuo who has a high banrate in SoloQ and also in Clash.

It is also worth noting that 6 out of the top 10 increase banrate in Clash are for AD Carry (Marksman). In organized teams, that role seems far more dreadful, but is it justified? A simple way to measure the effectiveness of a ban is to calculate the winrate of a team banning a certain champion, or in another way, what are your chance of winning if you ban this champion. If we look at the SoloQ, the “default” bans, or banning a champion that is usualy banned, have little effect as the winrate in such case is very close to 50%. Even more flagrant on how much usefull is a ban in SoloQ, not banning a champion also has a very limited impact with a winrate of 49.72%. In Clash, a no ban drops the winrate to 35.93%, and “default” bans tend to have a negative effect and to lower the winrate. Banning ADC seems not to be efficient as aside from Jinx, a default ban on an ADC results mostly in a lesser winrate. Bans against tanks and supports are generally more effective.

On the pickrate side, we also have differences, yet less spectacular than with the banrates :

  • Champions that are far less picked in Clash:
    • Yasuo : 20% ↘ 11%
    • Teemo : 10% ↘ 2%
    • Master Yi : 11% ↘ 4%
    • Lux : 20% ↘ 13%
    • Lee Sin : 15% ↘ 9%
  • Champions that are far more picked in Clash:
    • Xayah : 12% ↗ 27%
    • Rakan : 9% ↗ 20%
    • Morgana : 16% ↗ 26%
    • Sejuani : 12% ↗ 22%
    • Nautilus : 12% ↗ 22%

Quite interesting, picks and bans trends seems very correlated as Xayah is far more picked AND banned, at the opposite of Master Yi which is far less picked and banned. This can be a good way to indicate champion feared or useful in a SoloQ environment and those better fit to orgainzed team play, and looking more like what we can see on the LoLesports scene. On this side, this is a clear success.

Fun facts about masteries, 60% of the bans target a champion with Mastery rank 7 in the other team. And if you are an One Trick Pony of this champion (under my definition, having more than half of the total mastery points on this champion), this champion will be banned in 69% of the cases, but when will the OTP will play his champion, the winrate is only of 48%.

Conclusion

All in all, Clash is a tournament mode that a a positive impact and the League of Legends player base. While the fairness of each bracket is something that can and should be improved, the will of Riot Games to create a mode that allows player to experience a glimpse of what pro players live every day is a success on many other points.

I made this analysis fur fun and shared it in to give others the information and insight about Clash they were looking for (or not). If you have any feedback to give, I’ll be glad to hear them, and if you are curious about how I did this analysis, the code is on Github :

https://github.com/HextechLab/Clash

Annexes

Click on titles to open the tables, click on table headers to sort.

Champion banrates differences
Champion Clash Ranked Difference
Pyke 22.19% 52.12% -30
Blitzcrank 14.58% 40.11% -26
Zed 24.96% 49.94% -25
Evelynn 8.14% 28.66% -21
Master Yi 13.37% 33.86% -20
Darius 20.18% 39.76% -20
Morgana 29.03% 47.60% -19
Draven 15.31% 30.06% -15
Yasuo 41.02% 55.44% -14
Akali 13.57% 24.90% -11
Jax 20.60% 30.97% -10
no ban 4.24% 14.44% -10
Malphite 15.21% 24.03% -8.8
Teemo 4.02% 12.84% -8.8
Illaoi 6.58% 14.90% -8.3
Mordekaiser 11.04% 19.24% -8.2
Brand 4.17% 11.28% -7.1
Yuumi 8.84% 15.30% -6.5
Tryndamere 6.05% 11.39% -5.3
Fiora 9.91% 15.10% -5.2
Pantheon 10.38% 15.08% -4.7
Qiyana 4.94% 9.62% -4.7
Kha’Zix 12.10% 16.38% -4.3
Fizz 10.73% 14.94% -4.2
Dr. Mundo 4.19% 7.36% -3.2
Aatrox 4.22% 7.22% -3
Nasus 7.71% 9.98% -2.3
Diana 6.37% 8.01% -1.6
Nautilus 11.21% 12.79% -1.6
Kassadin 6.05% 7.04% -0.99
Sylas 8.62% 9.45% -0.84
Garen 6.38% 7.09% -0.7
Rammus 4.50% 4.91% -0.4
Zyra 3.77% 4.05% -0.28
Fiddlesticks 1.28% 1.40% -0.12
Rengar 7.80% 7.85% -0.049
Renekton 9.79% 9.80% -0.0095
Malzahar 8.45% 8.45% 0.0056
Quinn 0.97% 0.82% 0.15
Annie 1.68% 1.45% 0.22
Heimerdinger 2.16% 1.92% 0.24
Karthus 1.77% 1.50% 0.27
Tahm Kench 1.04% 0.76% 0.27
Kalista 0.44% 0.16% 0.28
Kog’Maw 0.51% 0.14% 0.37
Maokai 0.61% 0.13% 0.49
Nidalee 0.73% 0.24% 0.49
Jayce 0.96% 0.39% 0.57
Graves 0.87% 0.28% 0.59
Aurelion Sol 0.92% 0.31% 0.61
Trundle 0.78% 0.17% 0.61
Ziggs 0.87% 0.21% 0.66
Skarner 0.82% 0.14% 0.68
Varus 0.98% 0.28% 0.7
Singed 0.93% 0.23% 0.7
Ivern 1.00% 0.21% 0.79
Talon 4.01% 3.21% 0.79
Taliyah 0.94% 0.07% 0.87
Nocturne 3.77% 2.90% 0.87
Alistar 1.75% 0.86% 0.9
Bard 1.34% 0.40% 0.95
Kindred 1.52% 0.57% 0.95
Corki 1.27% 0.30% 0.97
Udyr 2.99% 1.99% 1
Twisted Fate 1.21% 0.21% 1
Rumble 1.35% 0.29% 1.1
Viktor 1.19% 0.12% 1.1
Cho’Gath 2.59% 1.51% 1.1
Shyvana 1.65% 0.52% 1.1
Leona 9.66% 8.53% 1.1
Camille 2.10% 0.88% 1.2
Galio 1.70% 0.48% 1.2
Taric 1.36% 0.11% 1.3
Wukong 1.59% 0.28% 1.3
Xin Zhao 2.25% 0.88% 1.4
Elise 3.32% 1.94% 1.4
Lissandra 1.75% 0.36% 1.4
Kayle 3.41% 2.01% 1.4
Sion 1.60% 0.20% 1.4
Rek’Sai 2.08% 0.64% 1.4
Olaf 3.18% 1.71% 1.5
Karma 1.99% 0.52% 1.5
Azir 1.90% 0.40% 1.5
Sona 1.93% 0.36% 1.6
Zoe 5.20% 3.62% 1.6
Ekko 13.95% 12.36% 1.6
Zilean 2.43% 0.71% 1.7
Warwick 3.28% 1.53% 1.8
Soraka 2.82% 1.07% 1.8
Swain 2.97% 1.18% 1.8
Ornn 2.15% 0.30% 1.9
Braum 3.06% 1.18% 1.9
Poppy 2.60% 0.70% 1.9
Volibear 3.41% 1.44% 2
Shaco 4.30% 2.28% 2
Ryze 2.91% 0.86% 2.1
Yorick 3.72% 1.64% 2.1
Miss Fortune 4.11% 2.01% 2.1
Cassiopeia 4.62% 2.48% 2.1
Kled 7.03% 4.87% 2.2
Ashe 4.90% 2.74% 2.2
LeBlanc 6.93% 4.69% 2.2
Janna 2.78% 0.52% 2.3
Twitch 4.71% 2.39% 2.3
Kennen 3.78% 1.39% 2.4
Gragas 3.07% 0.47% 2.6
Neeko 4.52% 1.82% 2.7
Urgot 7.53% 4.81% 2.7
Nunu & Willump 4.39% 1.58% 2.8
Caitlyn 19.80% 16.95% 2.8
Anivia 3.57% 0.66% 2.9
Kayn 14.75% 11.64% 3.1
Hecarim 6.64% 3.50% 3.1
Irelia 8.79% 5.61% 3.2
Gangplank 4.34% 1.08% 3.3
Amumu 4.83% 1.46% 3.4
Xerath 5.37% 1.79% 3.6
Katarina 12.33% 8.67% 3.7
Gnar 4.80% 1.11% 3.7
Ezreal 8.23% 4.28% 4
Vi 6.40% 2.23% 4.2
Lulu 5.69% 1.42% 4.3
Nami 4.84% 0.55% 4.3
Sivir 6.38% 2.02% 4.4
Veigar 8.88% 4.46% 4.4
Vladimir 15.63% 11.20% 4.4
Syndra 6.93% 2.49% 4.4
Zac 5.46% 0.99% 4.5
Shen 5.27% 0.45% 4.8
Tristana 8.08% 2.94% 5.1
Vel’Koz 7.65% 1.89% 5.8
Ahri 12.86% 6.76% 6.1
Riven 11.87% 5.74% 6.1
Lee Sin 15.29% 8.78% 6.5
Sejuani 7.30% 0.74% 6.6
Lux 12.59% 6.02% 6.6
Orianna 7.82% 0.94% 6.9
Jhin 11.34% 4.37% 7
Lucian 9.02% 1.92% 7.1
Rakan 10.59% 2.58% 8
Jarvan IV 9.75% 1.47% 8.3
Jinx 16.95% 5.82% 11
Vayne 21.33% 10.04% 11
Xayah 18.13% 6.20% 12
Thresh 19.86% 7.08% 13
Kai’Sa 24.46% 10.49% 14
Champion pickrate differences
Champion Clash Ranked Difference
Yasuo 11.00% 20.54% -9.5
Teemo 2.48% 10.05% -7.6
Master Yi 4.04% 11.14% -7.1
Lux 13.77% 20.53% -6.8
Lee Sin 8.77% 15.42% -6.6
Tryndamere 2.59% 8.93% -6.3
Riven 2.70% 8.86% -6.2
Zed 5.45% 11.52% -6.1
Kha’Zix 8.06% 13.85% -5.8
Ashe 12.37% 17.88% -5.5
Miss Fortune 5.71% 10.61% -4.9
Katarina 3.20% 7.99% -4.8
Blitzcrank 11.16% 15.94% -4.8
Jhin 13.11% 17.85% -4.7
Vayne 9.53% 14.22% -4.7
Rengar 2.41% 6.73% -4.3
Brand 4.18% 8.47% -4.3
Kayle 2.70% 6.31% -3.6
Jinx 15.75% 19.25% -3.5
Pyke 10.86% 14.34% -3.5
Shaco 1.13% 4.55% -3.4
Twitch 2.64% 5.95% -3.3
Nasus 5.85% 9.03% -3.2
Evelynn 3.87% 6.64% -2.8
Draven 4.79% 7.51% -2.7
Zyra 3.46% 6.13% -2.7
Fiddlesticks 1.41% 4.03% -2.6
Twisted Fate 1.64% 4.11% -2.5
Diana 4.24% 6.66% -2.4
Talon 2.39% 4.73% -2.3
Fizz 5.29% 7.61% -2.3
Soraka 3.68% 5.95% -2.3
Sona 2.11% 4.33% -2.2
Akali 7.66% 9.86% -2.2
Jax 13.92% 16.01% -2.1
Ezreal 14.09% 16.08% -2
Pantheon 9.61% 11.57% -2
Graves 1.24% 3.16% -1.9
Nidalee 0.87% 2.78% -1.9
Bard 1.68% 3.52% -1.8
Ryze 4.89% 6.66% -1.8
Quinn 0.86% 2.58% -1.7
Fiora 7.55% 9.21% -1.7
Qiyana 2.96% 4.59% -1.6
Irelia 5.33% 6.95% -1.6
Udyr 2.08% 3.36% -1.3
Wukong 1.43% 2.70% -1.3
Karthus 1.38% 2.65% -1.3
Kassadin 4.46% 5.73% -1.3
Gangplank 3.35% 4.61% -1.3
Zilean 1.96% 3.15% -1.2
Annie 2.67% 3.82% -1.2
Heimerdinger 3.13% 4.21% -1.1
Shyvana 1.93% 3.00% -1.1
Ekko 14.51% 15.56% -1.1
Kindred 1.44% 2.49% -1.1
Xin Zhao 3.57% 4.61% -1
Singed 0.82% 1.84% -1
Nocturne 5.55% 6.55% -1
Janna 5.53% 6.53% -1
Varus 2.89% 3.87% -0.98
Garen 9.32% 10.07% -0.74
LeBlanc 4.02% 4.75% -0.73
Zoe 3.58% 4.16% -0.58
Jayce 0.99% 1.52% -0.53
Warwick 5.40% 5.92% -0.52
Veigar 10.02% 10.51% -0.5
Kalista 0.71% 1.12% -0.41
Thresh 18.25% 18.65% -0.4
Xerath 5.66% 6.00% -0.34
Lucian 11.89% 12.17% -0.28
Camille 2.65% 2.92% -0.26
Cassiopeia 4.99% 5.24% -0.24
Kog’Maw 1.03% 1.25% -0.22
Sylas 5.20% 5.42% -0.22
Vel’Koz 7.57% 7.72% -0.15
Aurelion Sol 0.66% 0.78% -0.13
Yuumi 5.74% 5.84% -0.095
Swain 5.07% 5.16% -0.092
Ziggs 2.50% 2.51% -0.006
Taliyah 1.09% 1.04% 0.049
Rumble 2.00% 1.94% 0.062
Tahm Kench 1.31% 1.20% 0.11
Illaoi 4.91% 4.64% 0.27
Ivern 1.10% 0.81% 0.28
Aatrox 3.67% 3.31% 0.37
Anivia 2.66% 2.28% 0.38
Nami 10.16% 9.78% 0.39
Viktor 1.85% 1.43% 0.42
Azir 1.84% 1.35% 0.48
Darius 11.70% 11.04% 0.66
Elise 4.93% 4.23% 0.7
Dr. Mundo 7.51% 6.77% 0.75
Trundle 2.66% 1.78% 0.88
Taric 2.42% 1.54% 0.88
Skarner 1.95% 1.02% 0.93
Karma 5.39% 4.44% 0.95
Mordekaiser 11.60% 10.60% 1
Yorick 3.83% 2.82% 1
Corki 2.54% 1.52% 1
Caitlyn 24.80% 23.68% 1.1
Volibear 6.17% 5.03% 1.1
Tristana 14.03% 12.86% 1.2
Rek’Sai 2.95% 1.77% 1.2
Olaf 6.33% 4.85% 1.5
Kayn 12.64% 11.00% 1.6
Alistar 4.96% 3.31% 1.6
Renekton 9.81% 8.05% 1.8
Malzahar 7.55% 5.74% 1.8
Kennen 4.89% 3.07% 1.8
Hecarim 7.07% 5.20% 1.9
Gragas 5.83% 3.93% 1.9
Maokai 3.47% 1.53% 1.9
Neeko 7.69% 5.71% 2
Rammus 5.15% 3.12% 2
Galio 5.60% 3.55% 2.1
Nunu & Willump 5.87% 3.71% 2.2
Urgot 7.38% 5.20% 2.2
Malphite 17.36% 15.14% 2.2
Cho’Gath 6.92% 4.64% 2.3
Lissandra 4.04% 1.70% 2.3
Sion 5.27% 2.76% 2.5
Vladimir 10.25% 7.73% 2.5
Vi 9.78% 7.16% 2.6
Lulu 8.23% 5.61% 2.6
Ahri 13.18% 10.25% 2.9
Kled 6.60% 3.63% 3
Poppy 6.40% 3.13% 3.3
Amumu 9.48% 5.67% 3.8
Sivir 9.92% 5.56% 4.4
Leona 16.38% 11.93% 4.4
Kai’Sa 24.84% 20.38% 4.5
Zac 8.94% 4.05% 4.9
Gnar 9.34% 3.81% 5.5
Ornn 8.46% 2.74% 5.7
Braum 9.29% 3.48% 5.8
Syndra 12.21% 6.28% 5.9
Shen 13.05% 5.85% 7.2
Orianna 14.46% 6.80% 7.7
Jarvan IV 16.31% 7.07% 9.2
Nautilus 21.82% 12.30% 9.5
Sejuani 11.89% 2.19% 9.7
Morgana 26.20% 16.40% 9.8
Rakan 19.64% 9.34% 10
Xayah 27.48% 12.50% 15
Champion stats in SoloQ
Champion Banrate Pickrate Winrate Presence Ban Winrate
Yasuo 55.44% 20.54% 50.34% 75.98% 50.05%
Pyke 52.12% 14.34% 51.04% 66.46% 50.20%
Morgana 47.60% 16.40% 49.82% 64.00% 50.54%
Zed 49.94% 11.52% 49.63% 61.45% 49.77%
Blitzcrank 40.11% 15.94% 53.18% 56.05% 50.81%
Darius 39.76% 11.04% 49.82% 50.81% 49.70%
Jax 30.97% 16.01% 51.21% 46.98% 50.60%
Master Yi 33.86% 11.14% 51.25% 45.01% 50.36%
Caitlyn 16.95% 23.68% 50.48% 40.63% 50.12%
Malphite 24.03% 15.14% 50.75% 39.17% 51.09%
Draven 30.06% 7.51% 50.25% 37.57% 49.87%
Evelynn 28.66% 6.64% 49.57% 35.31% 50.64%
Akali 24.90% 9.86% 44.70% 34.76% 48.47%
Kai’Sa 10.49% 20.38% 47.37% 30.87% 48.09%
Kha’Zix 16.38% 13.85% 51.07% 30.24% 50.96%
Mordekaiser 19.24% 10.60% 51.53% 29.85% 50.41%
Ekko 12.36% 15.56% 51.59% 27.92% 51.10%
Pantheon 15.08% 11.57% 48.69% 26.66% 49.77%
Lux 6.02% 20.53% 50.20% 26.54% 49.83%
Thresh 7.08% 18.65% 48.29% 25.73% 48.56%
Nautilus 12.79% 12.30% 51.69% 25.09% 51.20%
Jinx 5.82% 19.25% 52.39% 25.08% 51.62%
Fiora 15.10% 9.21% 50.52% 24.31% 50.92%
Vayne 10.04% 14.22% 49.74% 24.26% 49.57%
Lee Sin 8.78% 15.42% 47.63% 24.20% 48.07%
Teemo 12.84% 10.05% 52.15% 22.89% 50.72%
Kayn 11.64% 11.00% 49.25% 22.64% 49.36%
Fizz 14.94% 7.61% 52.26% 22.55% 50.59%
Jhin 4.37% 17.85% 51.65% 22.22% 51.04%
Yuumi 15.30% 5.84% 43.49% 21.14% 48.22%
Ashe 2.74% 17.88% 52.75% 20.62% 52.21%
Leona 8.53% 11.93% 50.95% 20.46% 50.73%
Ezreal 4.28% 16.08% 45.91% 20.36% 46.78%
Tryndamere 11.39% 8.93% 50.24% 20.32% 50.08%
Brand 11.28% 8.47% 50.98% 19.75% 50.07%
Illaoi 14.90% 4.64% 51.62% 19.54% 49.87%
Nasus 9.98% 9.03% 51.00% 19.01% 50.38%
Vladimir 11.20% 7.73% 48.63% 18.93% 49.91%
Xayah 6.20% 12.50% 49.48% 18.71% 49.68%
Renekton 9.80% 8.05% 48.98% 17.86% 49.78%
Garen 7.09% 10.07% 52.14% 17.15% 50.99%
Ahri 6.76% 10.25% 51.83% 17.02% 50.97%
Katarina 8.67% 7.99% 49.99% 16.66% 49.71%
Tristana 2.94% 12.86% 49.36% 15.81% 49.26%
Veigar 4.46% 10.51% 50.46% 14.97% 50.13%
Sylas 9.45% 5.42% 41.28% 14.88% 46.77%
Diana 8.01% 6.66% 51.80% 14.67% 50.72%
Riven 5.74% 8.86% 47.21% 14.60% 48.38%
Rengar 7.85% 6.73% 49.18% 14.58% 50.64%
no ban 14.44% 0.00% 0.00% 14.44% 49.72%
Qiyana 9.62% 4.59% 45.61% 14.22% 48.95%
Malzahar 8.45% 5.74% 51.84% 14.19% 51.00%
Dr. Mundo 7.36% 6.77% 52.75% 14.13% 51.26%
Lucian 1.92% 12.17% 48.28% 14.09% 48.36%
Kassadin 7.04% 5.73% 51.41% 12.77% 51.55%
Miss Fortune 2.01% 10.61% 51.00% 12.62% 50.54%
Irelia 5.61% 6.95% 45.31% 12.57% 47.14%
Rakan 2.58% 9.34% 49.78% 11.92% 49.83%
Aatrox 7.22% 3.31% 45.04% 10.53% 47.72%
Nami 0.55% 9.78% 51.65% 10.33% 51.52%
Zyra 4.05% 6.13% 51.85% 10.17% 51.15%
Urgot 4.81% 5.20% 51.79% 10.01% 50.86%
Vel’Koz 1.89% 7.72% 51.58% 9.61% 51.12%
Nocturne 2.90% 6.55% 52.01% 9.45% 51.30%
LeBlanc 4.69% 4.75% 46.80% 9.44% 48.25%
Vi 2.23% 7.16% 52.61% 9.38% 52.22%
Syndra 2.49% 6.28% 49.50% 8.77% 49.77%
Hecarim 3.50% 5.20% 50.68% 8.69% 49.97%
Jarvan IV 1.47% 7.07% 50.64% 8.55% 50.44%
Kled 4.87% 3.63% 51.63% 8.50% 50.72%
Twitch 2.39% 5.95% 50.63% 8.34% 50.28%
Kayle 2.01% 6.31% 52.31% 8.32% 51.76%
Rammus 4.91% 3.12% 50.48% 8.03% 50.78%
Talon 3.21% 4.73% 48.93% 7.94% 49.17%
Xerath 1.79% 6.00% 51.38% 7.79% 50.88%
Zoe 3.62% 4.16% 47.51% 7.78% 48.44%
Orianna 0.94% 6.80% 50.19% 7.74% 50.22%
Cassiopeia 2.48% 5.24% 51.34% 7.72% 50.75%
Sivir 2.02% 5.56% 49.42% 7.57% 49.70%
Neeko 1.82% 5.71% 49.37% 7.53% 49.16%
Ryze 0.86% 6.66% 47.69% 7.52% 47.87%
Warwick 1.53% 5.92% 50.07% 7.45% 49.94%
Amumu 1.46% 5.67% 51.87% 7.13% 51.35%
Janna 0.52% 6.53% 52.08% 7.05% 51.90%
Lulu 1.42% 5.61% 49.40% 7.03% 49.67%
Soraka 1.07% 5.95% 51.97% 7.02% 51.77%
Shaco 2.28% 4.55% 49.16% 6.83% 48.99%
Olaf 1.71% 4.85% 49.22% 6.56% 49.18%
Volibear 1.44% 5.03% 52.72% 6.47% 52.31%
Swain 1.18% 5.16% 51.61% 6.34% 51.22%
Shen 0.45% 5.85% 49.99% 6.30% 49.90%
Elise 1.94% 4.23% 49.16% 6.17% 49.34%
Cho’Gath 1.51% 4.64% 48.86% 6.15% 48.85%
Heimerdinger 1.92% 4.21% 52.68% 6.13% 51.16%
Gangplank 1.08% 4.61% 47.60% 5.69% 48.09%
Xin Zhao 0.88% 4.61% 50.25% 5.49% 49.98%
Fiddlesticks 1.40% 4.03% 48.71% 5.43% 49.05%
Udyr 1.99% 3.36% 51.01% 5.35% 50.53%
Nunu & Willump 1.58% 3.71% 52.08% 5.29% 51.77%
Annie 1.45% 3.82% 49.06% 5.27% 49.12%
Zac 0.99% 4.05% 52.52% 5.03% 51.86%
Karma 0.52% 4.44% 47.00% 4.96% 47.25%
Gnar 1.11% 3.81% 48.37% 4.92% 48.45%
Sona 0.36% 4.33% 50.72% 4.69% 50.53%
Braum 1.18% 3.48% 46.32% 4.66% 47.05%
Yorick 1.64% 2.82% 52.56% 4.46% 51.55%
Kennen 1.39% 3.07% 49.76% 4.46% 50.35%
Gragas 0.47% 3.93% 44.81% 4.41% 45.26%
Twisted Fate 0.21% 4.11% 48.81% 4.33% 48.82%
Alistar 0.86% 3.31% 47.22% 4.17% 47.62%
Varus 0.28% 3.87% 47.15% 4.15% 47.20%
Karthus 1.50% 2.65% 49.79% 4.15% 49.97%
Galio 0.48% 3.55% 50.17% 4.03% 49.99%
Bard 0.40% 3.52% 50.00% 3.91% 49.83%
Zilean 0.71% 3.15% 51.01% 3.87% 51.00%
Poppy 0.70% 3.13% 48.29% 3.83% 48.69%
Camille 0.88% 2.92% 48.94% 3.80% 48.96%
Shyvana 0.52% 3.00% 49.67% 3.52% 49.67%
Graves 0.28% 3.16% 50.36% 3.44% 50.20%
Quinn 0.82% 2.58% 50.95% 3.40% 50.47%
Kindred 0.57% 2.49% 48.71% 3.06% 48.87%
Ornn 0.30% 2.74% 49.95% 3.03% 49.83%
Nidalee 0.24% 2.78% 46.51% 3.03% 46.72%
Wukong 0.28% 2.70% 50.70% 2.99% 50.34%
Sion 0.20% 2.76% 51.01% 2.95% 50.80%
Anivia 0.66% 2.28% 50.18% 2.94% 50.11%
Sejuani 0.74% 2.19% 44.95% 2.94% 46.34%
Ziggs 0.21% 2.51% 50.86% 2.71% 50.66%
Rek’Sai 0.64% 1.77% 49.34% 2.41% 50.45%
Rumble 0.29% 1.94% 50.16% 2.23% 49.96%
Singed 0.23% 1.84% 50.87% 2.07% 50.54%
Lissandra 0.36% 1.70% 47.71% 2.06% 48.04%
Tahm Kench 0.76% 1.20% 44.87% 1.96% 46.41%
Trundle 0.17% 1.78% 49.83% 1.95% 49.53%
Jayce 0.39% 1.52% 45.39% 1.91% 46.28%
Corki 0.30% 1.52% 45.81% 1.81% 46.15%
Azir 0.40% 1.35% 43.51% 1.76% 44.45%
Maokai 0.13% 1.53% 49.92% 1.66% 49.73%
Taric 0.11% 1.54% 50.86% 1.65% 50.62%
Viktor 0.12% 1.43% 47.69% 1.55% 47.70%
Kog’Maw 0.14% 1.25% 50.03% 1.40% 49.86%
Kalista 0.16% 1.12% 45.83% 1.28% 46.18%
Skarner 0.14% 1.02% 49.39% 1.15% 49.07%
Taliyah 0.07% 1.04% 49.18% 1.11% 49.10%
Aurelion Sol 0.31% 0.78% 51.28% 1.09% 50.26%
Ivern 0.21% 0.81% 46.68% 1.02% 47.09%
Champion stats in Clash
Champion Banrate Pickrate Winrate Presence Ban Winrate
Morgana 29.03% 26.20% 51.05% 55.23% 52.31%
Yasuo 41.02% 11.00% 50.69% 52.02% 48.63%
Kai’Sa 24.46% 24.84% 47.82% 49.29% 48.54%
Xayah 18.13% 27.48% 51.11% 45.61% 50.61%
Caitlyn 19.80% 24.80% 50.92% 44.60% 50.61%
Thresh 19.86% 18.25% 51.18% 38.11% 49.43%
Jax 20.60% 13.92% 48.72% 34.52% 49.57%
Pyke 22.19% 10.86% 50.31% 33.05% 49.25%
Nautilus 11.21% 21.82% 51.85% 33.02% 51.26%
Jinx 16.95% 15.75% 52.07% 32.70% 52.02%
Malphite 15.21% 17.36% 51.16% 32.56% 50.95%
Darius 20.18% 11.70% 50.58% 31.88% 49.36%
Vayne 21.33% 9.53% 50.67% 30.86% 48.31%
Zed 24.96% 5.45% 49.72% 30.41% 48.82%
Rakan 10.59% 19.64% 50.83% 30.23% 50.57%
Ekko 13.95% 14.51% 53.13% 28.46% 51.42%
Kayn 14.75% 12.64% 49.82% 27.39% 49.94%
Lux 12.59% 13.77% 48.35% 26.36% 50.39%
Jarvan IV 9.75% 16.31% 51.79% 26.06% 50.82%
Ahri 12.86% 13.18% 51.41% 26.04% 50.96%
Leona 9.66% 16.38% 51.17% 26.03% 51.32%
Vladimir 15.63% 10.25% 49.81% 25.88% 49.56%
Blitzcrank 14.58% 11.16% 54.85% 25.74% 52.70%
Jhin 11.34% 13.11% 51.05% 24.45% 50.52%
Lee Sin 15.29% 8.77% 47.16% 24.07% 47.28%
Mordekaiser 11.04% 11.60% 53.21% 22.64% 51.64%
Ezreal 8.23% 14.09% 46.79% 22.33% 47.62%
Orianna 7.82% 14.46% 51.64% 22.28% 51.10%
Tristana 8.08% 14.03% 47.80% 22.11% 48.73%
Akali 13.57% 7.66% 45.66% 21.23% 47.52%
Lucian 9.02% 11.89% 47.85% 20.91% 48.05%
Kha’Zix 12.10% 8.06% 49.13% 20.16% 49.47%
Draven 15.31% 4.79% 49.56% 20.10% 48.66%
Pantheon 10.38% 9.61% 48.05% 19.99% 49.31%
Renekton 9.79% 9.81% 48.62% 19.61% 48.97%
Sejuani 7.30% 11.89% 45.75% 19.19% 47.36%
Syndra 6.93% 12.21% 49.80% 19.14% 49.85%
Veigar 8.88% 10.02% 50.46% 18.90% 50.52%
Shen 5.27% 13.05% 50.01% 18.32% 50.11%
Fiora 9.91% 7.55% 50.48% 17.46% 49.91%
Master Yi 13.37% 4.04% 46.68% 17.40% 49.22%
Ashe 4.90% 12.37% 53.37% 17.27% 52.88%
Sivir 6.38% 9.92% 50.60% 16.31% 51.08%
Vi 6.40% 9.78% 50.54% 16.18% 50.79%
Fizz 10.73% 5.29% 49.33% 16.02% 49.39%
Malzahar 8.45% 7.55% 51.69% 16.01% 52.77%
Garen 6.38% 9.32% 50.08% 15.71% 50.87%
Katarina 12.33% 3.20% 47.59% 15.53% 50.12%
Vel’Koz 7.65% 7.57% 52.73% 15.21% 51.10%
Nami 4.84% 10.16% 49.32% 15.01% 50.89%
Urgot 7.53% 7.38% 50.50% 14.91% 51.27%
Yuumi 8.84% 5.74% 42.58% 14.59% 48.50%
Riven 11.87% 2.70% 48.19% 14.57% 48.34%
Zac 5.46% 8.94% 53.91% 14.40% 52.77%
Amumu 4.83% 9.48% 52.47% 14.31% 52.49%
Gnar 4.80% 9.34% 49.65% 14.14% 50.01%
Irelia 8.79% 5.33% 46.98% 14.12% 47.07%
Lulu 5.69% 8.23% 45.56% 13.92% 48.72%
Sylas 8.62% 5.20% 43.01% 13.82% 46.31%
Hecarim 6.64% 7.07% 49.50% 13.71% 49.62%
Kled 7.03% 6.60% 52.15% 13.63% 51.07%
Nasus 7.71% 5.85% 50.90% 13.56% 50.14%
Braum 3.06% 9.29% 48.27% 12.35% 49.03%
Neeko 4.52% 7.69% 48.16% 12.21% 49.22%
Evelynn 8.14% 3.87% 48.45% 12.01% 50.22%
Dr. Mundo 4.19% 7.51% 51.92% 11.71% 50.93%
Illaoi 6.58% 4.91% 51.02% 11.49% 51.00%
Xerath 5.37% 5.66% 50.76% 11.04% 49.56%
LeBlanc 6.93% 4.02% 46.30% 10.95% 47.24%
Ornn 2.15% 8.46% 50.98% 10.61% 50.66%
Diana 6.37% 4.24% 49.08% 10.61% 50.93%
Kassadin 6.05% 4.46% 51.66% 10.51% 51.11%
Nunu & Willump 4.39% 5.87% 54.22% 10.26% 53.10%
Rengar 7.80% 2.41% 51.33% 10.22% 49.61%
Miss Fortune 4.11% 5.71% 49.64% 9.83% 51.69%
Rammus 4.50% 5.15% 49.06% 9.66% 50.82%
Cassiopeia 4.62% 4.99% 52.81% 9.62% 50.96%
Volibear 3.41% 6.17% 53.35% 9.58% 52.42%
Cho’Gath 2.59% 6.92% 49.28% 9.51% 49.68%
Olaf 3.18% 6.33% 50.74% 9.51% 50.04%
Nocturne 3.77% 5.55% 51.06% 9.32% 50.78%
Poppy 2.60% 6.40% 47.50% 9.00% 48.74%
Gragas 3.07% 5.83% 45.92% 8.90% 46.01%
Zoe 5.20% 3.58% 49.45% 8.78% 49.87%
Warwick 3.28% 5.40% 46.86% 8.68% 49.12%
Kennen 3.78% 4.89% 52.57% 8.67% 51.89%
Tryndamere 6.05% 2.59% 48.65% 8.65% 49.48%
Brand 4.17% 4.18% 49.61% 8.35% 50.42%
Janna 2.78% 5.53% 48.71% 8.32% 50.58%
Elise 3.32% 4.93% 49.30% 8.25% 49.08%
Swain 2.97% 5.07% 54.14% 8.04% 52.66%
Aatrox 4.22% 3.67% 46.19% 7.90% 47.27%
Qiyana 4.94% 2.96% 48.56% 7.90% 48.84%
Ryze 2.91% 4.89% 46.67% 7.80% 47.46%
Gangplank 4.34% 3.35% 50.63% 7.69% 50.03%
Yorick 3.72% 3.83% 50.32% 7.55% 51.52%
Karma 1.99% 5.39% 44.17% 7.38% 45.51%
Twitch 4.71% 2.64% 52.43% 7.35% 51.37%
Galio 1.70% 5.60% 50.90% 7.30% 51.07%
Zyra 3.77% 3.46% 52.43% 7.23% 53.51%
Sion 1.60% 5.27% 51.29% 6.88% 51.20%
Alistar 1.75% 4.96% 49.02% 6.71% 49.28%
Soraka 2.82% 3.68% 49.38% 6.50% 50.92%
Teemo 4.02% 2.48% 48.49% 6.49% 49.94%
Talon 4.01% 2.39% 44.76% 6.40% 48.82%
Anivia 3.57% 2.66% 50.61% 6.23% 50.51%
Kayle 3.41% 2.70% 52.11% 6.11% 52.10%
Xin Zhao 2.25% 3.57% 47.39% 5.82% 48.69%
Lissandra 1.75% 4.04% 49.16% 5.79% 49.11%
Shaco 4.30% 1.13% 50.67% 5.43% 51.40%
Heimerdinger 2.16% 3.13% 52.35% 5.29% 52.33%
Udyr 2.99% 2.08% 49.92% 5.07% 49.90%
Rek’Sai 2.08% 2.95% 47.15% 5.03% 48.18%
Camille 2.10% 2.65% 49.19% 4.75% 49.51%
Zilean 2.43% 1.96% 54.62% 4.38% 54.22%
Annie 1.68% 2.67% 46.30% 4.34% 48.66%
no ban 4.24% 0.00% 0.00% 4.24% 35.93%
Maokai 0.61% 3.47% 47.90% 4.08% 48.00%
Sona 1.93% 2.11% 44.72% 4.04% 51.00%
Varus 0.98% 2.89% 47.38% 3.87% 47.53%
Corki 1.27% 2.54% 46.60% 3.80% 47.53%
Taric 1.36% 2.42% 53.66% 3.79% 53.36%
Azir 1.90% 1.84% 46.86% 3.74% 48.01%
Shyvana 1.65% 1.93% 48.85% 3.58% 50.73%
Trundle 0.78% 2.66% 48.44% 3.44% 48.98%
Ziggs 0.87% 2.50% 49.32% 3.37% 49.05%
Rumble 1.35% 2.00% 48.48% 3.34% 49.35%
Karthus 1.77% 1.38% 49.66% 3.14% 49.22%
Viktor 1.19% 1.85% 47.36% 3.05% 47.72%
Bard 1.34% 1.68% 50.24% 3.02% 50.54%
Wukong 1.59% 1.43% 48.04% 3.01% 51.51%
Kindred 1.52% 1.44% 51.50% 2.96% 51.77%
Twisted Fate 1.21% 1.64% 50.18% 2.85% 49.43%
Skarner 0.82% 1.95% 52.06% 2.76% 51.56%
Fiddlesticks 1.28% 1.41% 48.42% 2.68% 50.24%
Tahm Kench 1.04% 1.31% 43.95% 2.35% 47.12%
Graves 0.87% 1.24% 53.16% 2.11% 50.86%
Ivern 1.00% 1.10% 51.12% 2.10% 50.53%
Taliyah 0.94% 1.09% 50.27% 2.03% 49.83%
Jayce 0.96% 0.99% 46.17% 1.95% 47.61%
Quinn 0.97% 0.86% 45.88% 1.84% 48.67%
Singed 0.93% 0.82% 53.07% 1.75% 51.70%
Nidalee 0.73% 0.87% 50.07% 1.60% 49.42%
Aurelion Sol 0.92% 0.66% 50.80% 1.58% 51.89%
Kog’Maw 0.51% 1.03% 46.15% 1.54% 49.43%
Kalista 0.44% 0.71% 43.79% 1.15% 46.92%