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In my previous “Deeper in Data” article “Meta Shift According to Player Level”, I highlight, thanks to Pixelborn data, that the metagame is affected by players’ level. So let’s apply this to a real situation to see if and how I was correct about it. To do so, I will take a tournament, try to predict its specific metagame and check afterward how far I was from reality considering the impact of “player level hypothesis”.
Lorcana Day #2 Tournament
First, let’s talk about the tournament itself. Lorcana Day #2 is an event hosted by Jiraya and “Gerome En Live”, two French content creators that are very enthusiastic about Lorcana, they try to build and push their community to enjoy the game as much as they are.
The event will take place in the Grand Magic Hotel, right next to Disneyland Paris!
The event is open to everyone and will host various activities such as, an open play area, an artist venue featuring Koni and Alex Accorsi, a shop, a card exchange area and (what is most important to us) a 64 player tournament!
Moreover, the tournament will be hosted live on twitch on Jiraya’s channel, but unfortunately for you English speakers it will be only available in French.
Nonetheless, let's take this tournament as an example for meta analysis!
Meta Overview
Here is a quick reminder made by gillygabyte of the latest state of the metagame, according to Pixelborn's top 100 players:
Player Sample
Now, we have to guess what kind of player will attend the main tournament. One important thing to know is that all 64 tournament tickets have been sold in less than a day. Meaning that tournament grinders might not have heard about this tournament before it was sold out. Therefore players will be there mostly for their bond with their favorite streamer and community regardless of their Lorcana game level.
One other important thing is that rewards have not been exactly announced yet, consequently players will be more likely to play the tournament for fun, fame and maybe practicing rather than expected value.
However, I know from their twitter that Team Savior managed to enroll 11 of their players, including Ptikouik who is the Lorcana Day #1 winner and she also came in 10th place in the 200 players tournament organized by Ludotrotter on December 3 at Angers.
Without further information on the player population, we might be in for a surprise about the players’ level. I still expect it to be above average but with a huge disparity from player to player.
Impact on the Meta
In my previous article I divided the meta into two different categories, one for the average player level and one for the top 100 players.
Considering ONLY this and the previous point about player sample, my guess is the following:
Without any surprise, the most represented decks should be Amethyst/Ruby. Moreover, Amethyst/Ruby meta share should be as close as top level considering that players will do their best to win and will go for top meta decks instead of testing new decks as it could be online.
For the 2nd most represented deck, Emerald/Steel might struggle a bit but should stay around 10% like it is in both categories over Pixelborn data.
Then it’s more difficult, because on one side there is Amber/Steel and Amber/Ruby that are popular at average level, and on the other side there is Sapphire/Steel and Amethyst/Steel which see more play at top level. I would like to keep it quite simple and put each of the 4 decks mentioned in the same basket at 8% but I will prove that I’m not a coward and order them in the final meta breakdown prediction below.
Then Ruby/Sapphire is the remaining color pair presented in the data above, only 6% meta share at any level and even lower at top level only 4%. If nothing goes crazy Ruby/Sapphire should stay at around 5%.
Final Prediction
To sum up here is my final prediction for the meta breakdown for the Lorcana Day #2 tournament.
This statement relies mainly on the player sample hypothesis. On my side I would have gone a bit further and pushed Amber/Steel to a 15 or 20% of the meta over Emerald/Steel. But let's see how the tournament goes and how big is the gap between my prediction and the real meta in the next article.
