체력이 낮을 때는 악의 장막이 주는 체력 회복 촉진 및 위장 효과로 전투에 복귀해 적의 빈틈을 노릴 수 있습니다.
은신 상태에서는 적 챔피언에게 얼마나 다가가면 감지되는지 주의를 기울이십시오. 근처 적 챔피언 위에 노란색이나 빨간색 눈이 빛나므로 적의 감지 여부를 파악할 수 있습니다.
황홀한 저주의 매혹 시전 시간이 길게 느껴질 수도 있지만 이블린은 매혹과 마법 저항력 감소 효과로 매우 유리한 입장에서 싸울 수 있기 때문에 기다릴 만한 가치가 있습니다.
하이머딩거는 어떤 곤경에 처해도 거의 다 업그레이드!!! 스킬로 해결할 수 있으니 조심하세요. 궁극기가 빠진 다음 들어가서 처치하시면 됩니다!
하이머딩거의 포탑은 하나씩 제거하기보다 미니언의 도움을 받아 한꺼번에 제거하는 편이 낫습니다.
The stats shown here highlight several important 이블린 against 하이머딩거 matchup statistics that can help you interpret the differences between the pair. 이블린’s KDA ratio ([kills + assists] / deaths) of NaN is better than 하이머딩거’s KDA ratio of NaN, indicating that 이블린 may be more central to her team's team fighting capacity than 하이머딩거. This observation is in large part a result of the difference in kills.
이블린 normally has a much larger longest kill spree than her enemy does. Commonly, she takes more damage than 하이머딩거. This typically indicates different amounts of tankyness; however, it can also indicate that the champion with higher health has less mobility and thus is unable to escape additional harm when engaged or poked.
Both League of Legends champs are great champions. Both champs have their strengths, weaknesses, and counters. In League's current meta, 이블린 usually fairs equally well when trying to fight 하이머딩거, with a 50.2% win rate. Therefore, 이블린 makes an ok counter to 하이머딩거.
While 이블린 does have a higher winrate compared to 하이머딩거, when on opposite teams, 이블린 also has a greater learning curve that makes her a more challenging champion to develop with. You still need to be cautious when picking 이블린 into 하이머딩거as her relative depth means that you may not be able to unleash her full potential without a significant amount of practice beforehand.
Moreover, 이블린 also has some amount of CC and other utility, a similar amount to 하이머딩거. This often makes her just as valuable during teamfights, especially when fighting champions with a ton of burst damage.
While there is not one best champion for every situation in League of Legends, in 이블린 vs 하이머딩거 matchups, 이블린 is the better champion with a similar win rate, more champion depth, and a similar amount of utility to help out your allies during late stage team fights.
이블린 is a decent counter to 하이머딩거. Focus your strategy on keeping up your gold income and destroying objectives. If you can do that, you should be able to stand on your own as 이블린 against 하이머딩거.
To truly master 이블린 to counter 하이머딩거 during both the laning and mid / late game phases of League of Legends, you should continue reading to learn a few extra tricks and insights into this matchup. If you mind the build and stats presented above, you should increase your win rate significantly and be closer to League of Legends pro players.
이블린 often picks up a lot less CS as 하이머딩거. Champs who on average don't earn many minion kills often don't need much CS to be valuable teammates, such as support champions. These kinds of champions are capable of scaling properly off of their skills, stats, and first items alone. Yet, champs with large amounts of CS, such as hyper-carries, often need many items to be effective. In either situation, try to do better than the values shown on this page to do well.
The most crucial items to use in your 이블린 versus 하이머딩거 build include 라바돈의 죽음모자, 그림자불꽃, and 폭풍 쇄도. When 이블린 included at least these three items in her build, she did much better versus 하이머딩거 than with many other common counter builds. In fact, 이블린 boasted an average winrate of 50.2% when countering 하이머딩거 with these items in her kit.
To have the greatest probability of annihilating 하이머딩거 as 이블린, you should equip the 감전, 돌발 일격, 사냥의 증표, 끈질긴 사냥꾼, 우주적 통찰력, and 마법의 신발 runes from the 지배 and 영감 rune sets. Of all the rune builds players chose for 이블린 vs 하이머딩거 matchups, this mixture of runes resulted in the best win rate. Moreover, these runes gave a 50.2% winrate overall.
If you would like to get 이블린 versus 하이머딩거 tips and counter builds for a a particular rank, feel free to choose one from the selection menu above. At first, the stats and build suggestions displayed are computed using every match with data with these champions.