Remember that nearby enemies can see which wall you're in.
Look at the line-up of both your team and the enemy's team when picking your form.
Gwen must hit something to recast her Ultimate, try to evade her between casts.
Gwen needs to attack a few times to set up her damage, so try to get the jump on her.
Gwen's Hallowed Mist shroud will only follow her once, after that it will dissipate when she leaves.
The stat comparisons provided here underscore some important Kayn against Gwen matchup stats that can help us appreciate the distinctions between these two champs. As an example, Kayn’s KDA ratio ([kills + assists] / deaths) of NaN is better than Gwen’s ratio of NaN, demonstrating that Kayn may be more central to his team's team fighting capacity than Gwen..
Kayn usually has a similar longest killing spree as his enemy does. On average, he receives more damage than Gwen. This commonly reflects differing health capacities; however, it can also show that the one champion has less agility and thus is unable to escape further damage when poked or engaged.
Both League of Legends champions are great champions. Both have their strengths, weaknesses, and counters. In the game's current meta, Kayn usually fairs equally well when trying to fight Gwen, with a 50.0% win rate. Therefore, Kayn makes an ok counter for Gwen.
While Kayn does have a higher winrate than Gwen, when on opposite teams, Kayn also has a much greater learning curve that makes him a more time consuming champ to pick up and master. You should be careful when picking Kayn into Gwenas his relative depth means you may not be able to reach his full potential without a lot of practice beforehand.
Additionally, Kayn also has only a small amount of utility and CC, a similar amount to Gwen. This often makes her just as valuable during team fights, especially when trying to counter champions with a lot of burst damage.
While there isn't one best champion overall in League of Legends, in Kayn vs Gwen matchups, Gwen is the better champion with a similar win rate, more champion depth, and a similar amount of utility to help out your team members during late stage team fights.
Kayn is a decent counter for Gwen. Make sure you focus your strategy on maximizing your CS and destroying objectives. If you can do that, you should hold your own as Kayn against Gwen.
If you would like to truly master Kayn in order to counter Gwen during both the early game and mid / late game phases of League of Legends, you should keep reading to gather a few extra tips and tricks for this matchup. If you listen to the build and stats shown above, you will grow your win rate by a lot and be closer to League of Legends pro players.
Kayn usually accumulates a lot less CS relative to Gwen. Champs who on average don't get many minion kills often don't require much CS to be effective, such as sup champs. They are capable of scaling properly off of their abilities and first items alone. Yet, champs with large amounts of CS, such as hyper-carries, usually require a lot of items to be effective. In either case, try to do better than the values shown on this page to do well.
The top items to use in your Kayn versus Gwen build include Edge of Night, Serylda's Grudge, and Axiom Arc. When Kayn incorporated at least these three items in his build, he did much better vs. Gwen than with most other commonly used counter builds. In fact, Kayn had an average winrate of 50.0% when playing against Gwen with this build.
To have the highest likelihood of annihilating Gwen as Kayn, you should take the Summon Aery, Nimbus Cloak, Transcendence, Gathering Storm, Sudden Impact, and Treasure Hunter runes from the Sorcery and Domination rune sets. Out of all the rune builds players chose for Kayn vs Gwen counter picks, this order of runes resulted in the greatest win rate. In fact, these runes provided a 50.0% win rate overall.
If you need to see Kayn x Gwen tips and counter builds for a an individual division rank, feel free to select one from the selection menu displayed above. By default, the stats and guides shown are computed using all rounds with data with both champs.