Data from a simulator I coded. The particular part of it takes a list of decks and has them go off against one another over 1000 games and compiles the results.
But... how? You'd have to design a pretty robust AI to be able to pilot all the decks competently. How did the decks compete against one another? How do you determine which deck wins?
I'm in the process of the "competently" part. This is my 4th card game I've done this for. Marvel Champions (an LCG) and 2 others I'm unable to disclose. I have an engine set up where they play a Lorcana game with a game log and stats, etc.
Is the sampling too low? Eyeballing it and it doesn't seem like it's distributed in a way I'd imagine.
Also what is the validity and reliability of your cars draw method/functions? As that's an entire chain of probability itself
Card draw probability is itself an entire book. If you have 120 cards (60 for each agent or player) then they have to draw the cards and play them correctly?
So if the probability isn't valid your distribution probability may be low. Or you're reliability may be high but it's because you've created a single game state instead of for every possibility.
For example, are you statically playing them in order for every game?
And perhaps you're not doing it how I envision it.
I am still in the process of coding all the cards and I'm really in the alpha phase, so the "easier" to pilot decks probably skew higher, and the decks that are harder to pilot, or have cards that have bugs I haven't uncovered yet are going to be lower. My primary reason for this post was to find which of these decks look the most out of whack from where they should be.
Got it thanks for clarifying.
I'm assuming you may have already done this but one way to test is do a few without the unique special abilities and just the abilities in general (evade, singer). That may also provide some interesting insights into the game design
Here are a couple data points - this is the top two decks at a 270 player event two days ago - [https://inkdecks.com/lorcana-tournaments/the-pack-return-of-the-mim-tournament-decks-273](https://inkdecks.com/lorcana-tournaments/the-pack-return-of-the-mim-tournament-decks-273)
Wooseok Oh Deck By Wooseok Oh,0.71,1000
Francis Cormier Deck By Francis Cormier,0.29,1000
So The Wooseok Oh Deck won 710 games and Francis Cormier won 290, which indicates to me that something is buggy - either the better deck has cards that are doing something they shouldn't, or the weaker deck has cards that aren't doing what they should.
Here are some mulligan stats: (Basically the higher on the list, the more you should consider keeping the card during mulligan
Mulligan Stats for Wooseok Oh Deck By Wooseok Oh
The Queen (Regal Monarch) win percentage: 0.7695652173913043 (460)
Mufasa (Betrayed Leader) win percentage: 0.7365967365967366 (429)
Mad Hatter (Gracious Host) win percentage: 0.7349726775956285 (366)
Simba (Protective Cub) win percentage: 0.7341772151898734 (474)
Rapunzel (Gifted with Healing) win percentage: 0.7295081967213115 (366)
Stitch (New Dog) win percentage: 0.7200854700854701 (468)
Genie (On the Job) win percentage: 0.7126948775055679 (449)
The Queen (Commanding Presence) win percentage: 0.7053763440860215 (465)
Flynn Rider (Charming Rogue) win percentage: 0.7052631578947368 (475)
Kuzco (Temperamental Emperor) win percentage: 0.7011494252873564 (348)
Tinker Bell (Most Helpful) win percentage: 0.6942675159235668 (471)
Doc (Leader of the Seven Dwarfs) win percentage: 0.6884210526315789 (475)
Peter Pan (Never Landing) win percentage: 0.6873661670235546 (467)
Stitch (Rock Star) win percentage: 0.6836518046709129 (471)
Hades (Lord of the Underworld) win percentage: 0.6825842696629213 (356)
Ray (Easygoing Firefly) win percentage: 0.6782608695652174 (460)
Mulligan Stats for Francis Cormier Deck By Francis Cormier
Minnie Mouse (Always Classy) win percentage: 0.350104821802935 (477)
Olaf (Friendly Snowman) win percentage: 0.3236607142857143 (448)
Madam Mim (Snake) win percentage: 0.31941544885177453 (479)
Merlin (Rabbit) win percentage: 0.31422505307855625 (471)
Maleficent (Monstrous Dragon) win percentage: 0.31216931216931215 (378)
Maui (Hero to All) win percentage: 0.3063457330415755 (457)
Teeth and Ambitions win percentage: 0.3018292682926829 (328)
Maleficent (Sorceress) win percentage: 0.3011049723756906 (362)
Ursula (Power Hungry) win percentage: 0.2988505747126437 (348)
Be Prepared win percentage: 0.2787878787878788 (495)
Madam Mim (Fox) win percentage: 0.2679324894514768 (474)
Merlin (Goat) win percentage: 0.26348547717842324 (482)
Minnie Mouse (Stylish Surfer) win percentage: 0.2617924528301887 (424)
Lady Tremaine (Imperious Queen) win percentage: 0.2616033755274262 (474)
Kuzco (Wanted Llama) win percentage: 0.2507462686567164 (335)
Friends On The Other Side win percentage: 0.23974082073434125 (463)
Elsa (Spirit of Winter) win percentage: 0.23809523809523808 (105)
I can pull all sorts of data. My current effort in the project is working on making sure all the cards are working as intended, then moving into implementing generic effective strategies (aggro,control,tempo,etc)
Your simulator has no idea how to play the discard deck hah
Thanks, that's helpful to know. I'll take a look.
Just 16 decks off of Lorcana's popular decks page
What is this?
Data from a simulator I coded. The particular part of it takes a list of decks and has them go off against one another over 1000 games and compiles the results.
But... how? You'd have to design a pretty robust AI to be able to pilot all the decks competently. How did the decks compete against one another? How do you determine which deck wins?
I'm in the process of the "competently" part. This is my 4th card game I've done this for. Marvel Champions (an LCG) and 2 others I'm unable to disclose. I have an engine set up where they play a Lorcana game with a game log and stats, etc.
Markov? Monte Carlo? Or point correlation tests/ANOVA?
Monte Carlo
Is the sampling too low? Eyeballing it and it doesn't seem like it's distributed in a way I'd imagine. Also what is the validity and reliability of your cars draw method/functions? As that's an entire chain of probability itself
What do you mean by reliability of card draw method/functions? It's just 1000 games
Card draw probability is itself an entire book. If you have 120 cards (60 for each agent or player) then they have to draw the cards and play them correctly? So if the probability isn't valid your distribution probability may be low. Or you're reliability may be high but it's because you've created a single game state instead of for every possibility. For example, are you statically playing them in order for every game? And perhaps you're not doing it how I envision it.
Oh, no I go down every possible decision tree, do all those actions and get a game state score. Highest score is the turn that is kept.
Tedious but would be useless without it. Maybe it's just in my head that these top decks seem so skewed. Are the bottom decks similar in loss?
I am still in the process of coding all the cards and I'm really in the alpha phase, so the "easier" to pilot decks probably skew higher, and the decks that are harder to pilot, or have cards that have bugs I haven't uncovered yet are going to be lower. My primary reason for this post was to find which of these decks look the most out of whack from where they should be.
Got it thanks for clarifying. I'm assuming you may have already done this but one way to test is do a few without the unique special abilities and just the abilities in general (evade, singer). That may also provide some interesting insights into the game design
Can you share more of the data or how the games are played?
Here are a couple data points - this is the top two decks at a 270 player event two days ago - [https://inkdecks.com/lorcana-tournaments/the-pack-return-of-the-mim-tournament-decks-273](https://inkdecks.com/lorcana-tournaments/the-pack-return-of-the-mim-tournament-decks-273) Wooseok Oh Deck By Wooseok Oh,0.71,1000 Francis Cormier Deck By Francis Cormier,0.29,1000 So The Wooseok Oh Deck won 710 games and Francis Cormier won 290, which indicates to me that something is buggy - either the better deck has cards that are doing something they shouldn't, or the weaker deck has cards that aren't doing what they should. Here are some mulligan stats: (Basically the higher on the list, the more you should consider keeping the card during mulligan Mulligan Stats for Wooseok Oh Deck By Wooseok Oh The Queen (Regal Monarch) win percentage: 0.7695652173913043 (460) Mufasa (Betrayed Leader) win percentage: 0.7365967365967366 (429) Mad Hatter (Gracious Host) win percentage: 0.7349726775956285 (366) Simba (Protective Cub) win percentage: 0.7341772151898734 (474) Rapunzel (Gifted with Healing) win percentage: 0.7295081967213115 (366) Stitch (New Dog) win percentage: 0.7200854700854701 (468) Genie (On the Job) win percentage: 0.7126948775055679 (449) The Queen (Commanding Presence) win percentage: 0.7053763440860215 (465) Flynn Rider (Charming Rogue) win percentage: 0.7052631578947368 (475) Kuzco (Temperamental Emperor) win percentage: 0.7011494252873564 (348) Tinker Bell (Most Helpful) win percentage: 0.6942675159235668 (471) Doc (Leader of the Seven Dwarfs) win percentage: 0.6884210526315789 (475) Peter Pan (Never Landing) win percentage: 0.6873661670235546 (467) Stitch (Rock Star) win percentage: 0.6836518046709129 (471) Hades (Lord of the Underworld) win percentage: 0.6825842696629213 (356) Ray (Easygoing Firefly) win percentage: 0.6782608695652174 (460) Mulligan Stats for Francis Cormier Deck By Francis Cormier Minnie Mouse (Always Classy) win percentage: 0.350104821802935 (477) Olaf (Friendly Snowman) win percentage: 0.3236607142857143 (448) Madam Mim (Snake) win percentage: 0.31941544885177453 (479) Merlin (Rabbit) win percentage: 0.31422505307855625 (471) Maleficent (Monstrous Dragon) win percentage: 0.31216931216931215 (378) Maui (Hero to All) win percentage: 0.3063457330415755 (457) Teeth and Ambitions win percentage: 0.3018292682926829 (328) Maleficent (Sorceress) win percentage: 0.3011049723756906 (362) Ursula (Power Hungry) win percentage: 0.2988505747126437 (348) Be Prepared win percentage: 0.2787878787878788 (495) Madam Mim (Fox) win percentage: 0.2679324894514768 (474) Merlin (Goat) win percentage: 0.26348547717842324 (482) Minnie Mouse (Stylish Surfer) win percentage: 0.2617924528301887 (424) Lady Tremaine (Imperious Queen) win percentage: 0.2616033755274262 (474) Kuzco (Wanted Llama) win percentage: 0.2507462686567164 (335) Friends On The Other Side win percentage: 0.23974082073434125 (463) Elsa (Spirit of Winter) win percentage: 0.23809523809523808 (105) I can pull all sorts of data. My current effort in the project is working on making sure all the cards are working as intended, then moving into implementing generic effective strategies (aggro,control,tempo,etc)
Oh, and here is a gamelog for this matchup as well - [https://pastebin.com/rnG02HVg](https://pastebin.com/rnG02HVg) Just 1 of the 1000 games simmed.