O alcance de Artilharia Viva aumenta a cada nível.
Fuja de Kog'Maw quando ele morrer!
Kog'Maw não tem uma boa habilidade para fugir, sendo especialmente propenso a receber emboscadas.
Barragem Bio-Arcana permite que Kog'Maw derrote o Barão Na'Shor logo no início da partida. É uma boa ideia deixar uma sentinela no Barão Na'Shor quando Kog'Maw construir sua Espada do Rei Destruído.
The stat comparisons shown here feature several significant Samira against Kog'Maw matchup stats that may help us explain the differences and similarities between the pair. Samira’s KDA ratio ([kills + assists] / deaths) of NaN is more than Kog'Maw’s KDA ratio of NaN, showing that Samira may be more central to her team's team fighting capability than Kog'Maw..
Samira normally has a slightly larger longest killing spree than her counter does. On average, she takes more damage than Kog'Maw. This is usually reflective of differing health capacities, but it can also imply that the champion with higher HP has less mobility and thus is not able to flee from additional harm when poked or engaged.
Both LoL champions are great. Both have their pros and cons. In the game's current meta, Samira usually loses when taking on Kog'Maw, with a 46.8% win rate. As a result, Samira makes a poor counter to Kog'Maw.
While Samira does have a lower win rate than Kog'Maw, when they face off with one another, Samira also has a greater difficulty level that makes her a more difficult character to learn and master. You should be very concerned when picking Samira into Kog'Maw.
Additionally, Samira also has only a small amount of CC and other utility, a similar amount to Kog'Maw. This often makes her just as valuable during teamfights, especially when facing champions with a lot of burst damage.
While there is not a single best champion for every situation in League of Legends, in Samira vs Kog'Maw matchups, Kog'Maw is the better champ with a much lower win rate, similar champion depth, and a similar amount of utility to help out your team members during team fights.
Samira is a terribly counter for Kog'Maw. Make sure you focus your actions on maximizing your gold income and taking out objectives. If you can do that, you should do very well as Samira against Kog'Maw.
To learn all of the intricacies of Samira to counter Kog'Maw during both the early game and mid / late game phases of League of Legends, you should continue reading to gather a few extra tips and tricks for this matchup. If you pay attention to the build and tips presented above, you will grow your win rate significantly and be that much closer to League of Legends pro players.
Samira typically racks up a similar amount of CS relative to Kog'Maw. Champs who on average don't acquire much CS often don't have to have much CS to be valuable teammates, such as sup champs. These kinds of champions are able to scale properly off of their abilities and first items alone. Yet, champions with a lot of CS, such as hyper-carries, typically need many items to be effective. In either situation, try to exceed the numbers shown here to do well.
The best items to prioritize in your Samira versus Kog'Maw build include Gume do Infinito, Sedenta por Sangue, and Arco-escudo Imortal. When Samira included at least these three pieces in her build, she performed much better vs. Kog'Maw than with many other common item sets. In fact, Samira had an average win rate of 46.8% when playing against Kog'Maw with these items in her kit.
To have the best chance of beating Kog'Maw as Samira, Samira players should use the Conquistador, Triunfo, Lenda: Linhagem, Até a Morte, Gosto de Sangue, and Caçador de Tesouros runes from the Precisão and Dominação rune sets. Out of all the rune combinations that we analyzed for Samira vs Kog'Maw counters, this composite of runes resulted in the greatest win rate. Moreover, these runes averaged a 46.8% winrate overall.
If you want to see Samira x Kog'Maw tips and counter stats for a an individual division, feel free to choose one from the selection menu provided above. By default, the statistics and strategies displayed are computed using all rounds with data with these champions.