Placez-vous près des murs et attirez vos ennemis pour les étourdir avec votre ultime.
Connaissez vos forces ! Mini Gnar est rapide, fragile et il inflige de gros dégâts soutenus. Méga Gnar est lent, résistant et il a un gros burst.
La gestion de votre Rage est très importante. Effectuez vos transformations aux bons moments pour profiter au maximum de vos deux formes.
The stats provided here highlight several critical Gnar vs. Akshan matchup statistics that may help us appreciate the distinctions between the two. For instance, Gnar’s KDA ratio ([kills + assists] / deaths) of NaN is more than Akshan’s KDA ratio of NaN, showing that Gnar may be more central to his team's team fighting potential than Akshan..
Gnar usually has a slightly smaller longest killing spree than his enemy does. Typically, he receives more damage than Akshan. This typically indicates different amounts of tankyness; however, it can also show that the champion with increased HP has less mobility and thus is not able to kite away from additional damage when poked or engaged.
Both League champs are great champions. Both champs have their pros and cons. In the game's current meta, Gnar usually loses when facing off against Akshan, with a 46.1% win rate. As a result, Gnar makes a poor counter to Akshan.
While Gnar does have a lower win rate than Akshan, when facing one another, Gnar also has a much greater learning curve that makes him a more time consuming champ to develop with. You should expect to face a difficult match when picking Gnar into Akshanas his relative depth means that you may not be able to reach his full potential without a significant amount of practice beforehand.
Additionally, Gnar has some amount of CC and other utility, a similar amount to Akshan. This often makes her just as valuable during teamfights, especially when fighting champions with a lot of burst damage.
While there isn't one best champion overall in League of Legends, in Gnar vs Akshan matchups, Akshan is the better champ with a much lower win rate, more champion depth, and a similar amount of utility to help out your teammates during late stage team fights.
Gnar is a trash counter to Akshan. Make sure you focus your strategy on maximizing your gold income and clearing objectives. If you do that, you should be able to stand on your own as Gnar against Akshan.
If you would like to truly master Gnar to counter Akshan during both the lane and mid / late game phases of League of Legends, you should keep reading to learn a few extra lessons on this matchup. If you mind the build and suggestions displayed here, you will increase your win rate significantly and be that much closer to League of Legends pro players.
Gnar most often gets a similar amount of CS as Akshan. Champs who on average don't get many minion kills usualy don't require much CS to be effective, such as supports. These kinds of champions are capable of scaling well off of their skills, stats, and first items alone. Yet, champions with a lot of CS, such as hyper-carries, often require a lot of items to be effective. In either situation, try to do better than the values reported on this page to do well.
The ideal items to use in your Gnar versus Akshan build include Couperet noir, Force de la trinité, and Ciel éventré. When Gnar incorporated at least these three pieces in his build, he did significantly better vs Akshan than with many other commonly used item sets. In fact, Gnar had an average win rate of 46.1% battling Akshan with this build.
To have the highest chance of vanquishing Akshan as Gnar, you should use the Jeu de jambes, Triomphe, Légende : alacrité, Baroud d'honneur, Plaque d'os, and Surcroissance runes from the Précision and Volonté rune sets. Out of all the runes we have analyed for Gnar vs Akshan face-offs, this combination of runes yielded the best win rate. Moreover, these runes averaged a 46.1% winrate overall.
If you need to see Gnar vs Akshan tips and counter builds for a an individual skill level, please choose one from the selection menu displayed above. At first, the statistics and strategies given are computed using every game with data with these champs.