Mainboard_CardName | WR | Mainboard_Count | most_common_quantity | Card_not_in_deck | Not_most_common_count |
---|---|---|---|---|---|
0 % | 2-4/8/11/13-15 | 3 | 0 | 28 | |
1.75 % | 1-3 | 2 | 9 | 27 | |
-0.15 % | 2-4 | 4 | 1 | 2 | |
Land_tot | 0 % | 20/22-26/34 | 25 | 0 | 10 |
1.92 % | 4 | 4 | 6 | 0 | |
-0.26 % | 4 | 4 | 10 | 0 | |
0 % | 3/4 | 4 | 3 | 1 | |
1.57 % | 3/4 | 4 | 7 | 3 |
5 Deck analysis
This analysis attempts to use regression to determine the cards with the best performance inside archetype or base archetype.
A binomial regression is initially trained on a set of decks. In order to be included in this analysis the archetype must be present at least 50 times in the dataset.
In order to be considered a card must be included at least 50 times in either the main deck or the sideboards, one or the other being considered separately. In models comparing the number of copies of each card, when a number of copies is less than 50 it is grouped with an adjacent number of copies. For example, a card that is present 32 times in 1 copy 200 times in 2 copies, 15 times in 3 copies and 47 times in 4 copies would lead to the following result 1/2 : 232 and 3/4 : 62. The formulation 2-4 indicates that the numbers of copies 2, 3 and 4 have been grouped together.
Be careful, this part leads to results that I’m not really sure of. The interpretation of the regression coefficients seems really questionable, particularly in relation to the collinearity problem and the very large number of variables with sometimes small sample sizes. I would therefore encourage you to be very careful.
Templates are created separately for the maindeck and the sideboard and maindeck and side board pull together (Total 75) according to the following scheme :
Base Cards cards systematically present in decks with an almost fixed number of copies less than 50 decks that do not have the most common number of copies. decks with zero copies are grouped with the majority class) contained in the decks, for which the number of copies varies, quasibinomial regression models are created using the wins and losses of each deck :
Comparing for each card presence Most common count vs absence Other
Comparing each card count with a sufficient sample size Most common count vs 1 vs 3-4 for example
Uncommon Cards, These cards are not always included in decks, quasibinomial regression models are created using the wins and losses of each deck :
Comparing for each card presence +1 vs absence 0
Comparing each card count with a sufficient sample size 0 vs 1 vs 3-4 for example.
Model produce odds ratio, an odds ratio greater than 1 indicates that the condition or event is more likely to occur in the first cards count. And an odds ratio less than 1 indicates that the condition or event is less likely to occur in the first cards count.
If the probabilities of the event in each of the groups of cards count are p1 (first group 4 copy of a cards) and p2 (second group 0-3 copy of the cards), then the odds ratio is:
\[OR = \frac{p_1/(1-p_1)}{p_2/(1-p_2)}\]
6 Archetype
6.1 B Demon : Demons
Number of deck : 60 for 130 wins over 238 rounds
6.1.1 Main deck
6.1.1.1 Base Cards
Cards Always in deck with nearly fix count
Total number of most common count : 50
6.1.2 Side Board
6.1.2.1 Base Cards
Cards Always in deck with nearly fix count
Total number of most common count : 0
Sideboard_CardName | WR | Sideboard_Count | most_common_quantity | Card_not_in_deck | Not_most_common_count |
---|---|---|---|---|---|
Land_tot | 0 % | 0 | 0 | 0 | 0 |
6.1.3 Total 75
6.1.3.1 Base Cards
Cards Always in deck with nearly fix count
Total number of most common count : 51
Mainboard_CardName | WR | Mainboard_Count | most_common_quantity | Card_not_in_deck | Not_most_common_count |
---|---|---|---|---|---|
0 % | 2-4/8/11/13-15 | 3 | 0 | 28 | |
0.49 % | 2-4 | 3 | 4 | 20 | |
-0.15 % | 2/4 | 4 | 1 | 1 | |
Land_tot | 0 % | 20/22-26/34 | 25 | 0 | 10 |
1.92 % | 4 | 4 | 6 | 0 | |
-0.26 % | 4 | 4 | 10 | 0 | |
-0.15 % | 3/4 | 4 | 1 | 2 | |
1.57 % | 3/4 | 4 | 7 | 3 |
6.2 Mono Red Aggro
Number of deck : 109 for 249 wins over 476 rounds
6.2.1 Main deck
6.2.1.1 Variable Cards
Cards not always in deck using binomial regression for WR
| Mono Red Aggro N :476 | |||
---|---|---|---|---|
Characteristic | N | OR | 95% CI | p-value |
Color | ||||
R | 167 | — | — | |
Other | 309 | 0.44 | 0.09, 2.08 | 0.3 |
Number_of_cards | 476 | 1.02 | 0.95, 1.10 | 0.5 |
1-4 | 273 | — | — | |
Other | 203 | 0.94 | 0.52, 1.72 | 0.9 |
1-5 | 262 | — | — | |
Other | 214 | 0.73 | 0.25, 2.09 | 0.6 |
0 | 234 | — | — | |
Other | 242 | 0.86 | 0.41, 1.77 | 0.7 |
1/3/4 | 278 | — | — | |
Other | 198 | 0.67 | 0.31, 1.41 | 0.3 |
0 | 249 | — | — | |
Other | 227 | 0.89 | 0.41, 1.92 | 0.8 |
1-4 | 264 | — | — | |
Other | 212 | 1.10 | 0.52, 2.32 | 0.8 |
2-4/6/8/12 | 285 | — | — | |
Other | 191 | 0.61 | 0.16, 2.13 | 0.4 |
1-4 | 270 | — | — | |
Other | 206 | 1.17 | 0.73, 1.88 | 0.5 |
Abbreviations: CI = Confidence Interval, OR = Odds Ratio |
| Mono Red Aggro N :476 | |||
---|---|---|---|---|
Characteristic | N | OR | 95% CI | p-value |
Color | ||||
R | 167 | — | — | |
Other | 91 | 0.53 | 0.10, 2.62 | 0.4 |
WR | 97 | 0.76 | 0.10, 5.67 | 0.8 |
RG | 80 | 0.69 | 0.09, 5.18 | 0.7 |
BR | 41 | 0.47 | 0.06, 3.40 | 0.5 |
Number_of_cards | 476 | 1.01 | 0.94, 1.10 | 0.7 |
1-4 | 273 | — | — | |
0 | 203 | 1.04 | 0.56, 1.97 | 0.9 |
1-5 | 262 | — | — | |
0 | 214 | 0.77 | 0.25, 2.30 | 0.6 |
0 | 234 | — | — | |
1/4 | 242 | 0.88 | 0.41, 1.87 | 0.7 |
1/3/4 | 278 | — | — | |
0 | 198 | 0.63 | 0.28, 1.38 | 0.3 |
0 | 249 | — | — | |
1-4 | 227 | 0.76 | 0.31, 1.82 | 0.5 |
1-4 | 264 | — | — | |
0 | 212 | 1.08 | 0.51, 2.32 | 0.8 |
2-4/6/8/12 | 285 | — | — | |
0 | 191 | 0.72 | 0.18, 2.78 | 0.6 |
1-4 | 270 | — | — | |
0 | 206 | 1.15 | 0.70, 1.89 | 0.6 |
Abbreviations: CI = Confidence Interval, OR = Odds Ratio |
6.2.2 Side Board
6.2.2.1 Base Cards
Cards Always in deck with nearly fix count
Total number of most common count : 0
Sideboard_CardName | WR | Sideboard_Count | most_common_quantity | Card_not_in_deck | Not_most_common_count |
---|---|---|---|---|---|
Land_tot | 0 % | 0-2/15 | 0 | 0 | 4 |
6.2.3 Total 75
6.2.3.1 Variable Cards
Cards not always in deck using binomial regression for WR
| Mono Red Aggro N :476 | |||
---|---|---|---|---|
Characteristic | N | OR | 95% CI | p-value |
Color | ||||
R | 167 | — | — | |
Other | 309 | 0.48 | 0.10, 2.05 | 0.3 |
Number_of_cards | 476 | 1.04 | 0.97, 1.12 | 0.3 |
1-4 | 273 | — | — | |
Other | 203 | 0.92 | 0.51, 1.68 | 0.8 |
1-5 | 262 | — | — | |
Other | 214 | 0.74 | 0.25, 2.10 | 0.6 |
0 | 234 | — | — | |
Other | 242 | 0.83 | 0.40, 1.72 | 0.6 |
1/3/4 | 278 | — | — | |
Other | 198 | 0.68 | 0.31, 1.43 | 0.3 |
0 | 249 | — | — | |
Other | 227 | 0.94 | 0.43, 2.04 | 0.9 |
1-4 | 264 | — | — | |
Other | 212 | 0.99 | 0.46, 2.13 | >0.9 |
2-4/6/8/12 | 285 | — | — | |
Other | 191 | 0.62 | 0.17, 2.06 | 0.4 |
1-4 | 270 | — | — | |
Other | 206 | 1.16 | 0.72, 1.87 | 0.5 |
0 | 250 | — | — | |
Other | 226 | 1.31 | 0.85, 2.00 | 0.2 |
Abbreviations: CI = Confidence Interval, OR = Odds Ratio |
| Mono Red Aggro N :476 | |||
---|---|---|---|---|
Characteristic | N | OR | 95% CI | p-value |
Color | ||||
R | 167 | — | — | |
Other | 91 | 0.55 | 0.11, 2.47 | 0.4 |
WR | 97 | 0.80 | 0.11, 5.27 | 0.8 |
RG | 80 | 0.66 | 0.09, 4.29 | 0.7 |
BR | 41 | 0.48 | 0.07, 3.13 | 0.5 |
Number_of_cards | 476 | 1.03 | 0.95, 1.12 | 0.5 |
1-4 | 273 | — | — | |
0 | 203 | 1.03 | 0.55, 1.94 | >0.9 |
1-5 | 262 | — | — | |
0 | 214 | 0.77 | 0.25, 2.29 | 0.6 |
0 | 234 | — | — | |
1/4 | 242 | 0.83 | 0.38, 1.77 | 0.6 |
1/3/4 | 278 | — | — | |
0 | 198 | 0.63 | 0.28, 1.37 | 0.2 |
0 | 249 | — | — | |
1-4 | 227 | 0.83 | 0.34, 2.00 | 0.7 |
1-4 | 264 | — | — | |
0 | 212 | 0.97 | 0.44, 2.11 | >0.9 |
2-4/6/8/12 | 285 | — | — | |
0 | 191 | 0.72 | 0.19, 2.58 | 0.6 |
1-4 | 270 | — | — | |
0 | 206 | 1.13 | 0.68, 1.85 | 0.6 |
0 | 250 | — | — | |
1-4 | 226 | 1.33 | 0.85, 2.07 | 0.2 |
Abbreviations: CI = Confidence Interval, OR = Odds Ratio |