CODEWITHSUNDEEP
pythonmachine-learningstatisticsdata-sciencelogistic-regression
Meio
Meio

Reputation: 180

Which of these variables is the best predictor for winning a match given this logit model

My goal is to find the best predictor variable for winning a match. I have a slight knowledge of basic statistics, so I decided to use logistic regression because result of match is a binary variable.

logit_model=sm.Logit(y,X)
result=logit_model.fit()
result.summary()

This comes out with following result:

========================================================================
Model:                 Logit              Pseudo R-squared:   0.515     
Dependent Variable:    win                AIC:                92784.8133
Date:                  2022-11-25 20:30   BIC:                92932.3349
No. Observations:      137967             Log-Likelihood:     -46377.   
Df Model:              14                 LL-Null:            -95631.   
Df Residuals:          137952             LLR p-value:        0.0000    
Converged:             1.0000             Scale:              1.0000    
No. Iterations:        7.0000                                           
------------------------------------------------------------------------
                        Coef.  Std.Err.     z     P>|z|   [0.025  0.975]
------------------------------------------------------------------------
kills                   0.2116   0.0050   42.7261 0.0000  0.2019  0.2213
assists                 0.2439   0.0025   98.3537 0.0000  0.2391  0.2488
deaths                 -0.4083   0.0039 -103.6498 0.0000 -0.4160 -0.4005
baronKills              0.7598   0.0338   22.4612 0.0000  0.6935  0.8261
dragonKills             0.3566   0.0157   22.6557 0.0000  0.3257  0.3874
timeCCingOthers        -0.0096   0.0006  -17.2654 0.0000 -0.0107 -0.0085
wardsPlaced             0.0051   0.0012    4.1346 0.0000  0.0027  0.0076
goldEarned             -0.0003   0.0000  -45.5422 0.0000 -0.0003 -0.0003
inhibitorTakedowns      2.1111   0.0212   99.5492 0.0000  2.0696  2.1527
largestKillingSpree    -0.0504   0.0070   -7.2300 0.0000 -0.0641 -0.0367
largestMultiKill        0.4043   0.0159   25.5014 0.0000  0.3732  0.4354
totalMinionsKilled      0.0043   0.0002   21.6630 0.0000  0.0039  0.0047
consumablesPurchased   -0.0395   0.0032  -12.3773 0.0000 -0.0458 -0.0333
damageDealtToBuildings  0.0002   0.0000   25.9200 0.0000  0.0001  0.0002
turretKills             0.3140   0.0131   23.8875 0.0000  0.2882  0.3397
========================================================================

What would be the best predictor for match win given these results? My initial thinking was I can't use the coefficient, because all variables come from different distributions. Is it valid thinking to use the z-score, since it standardizes values to the same distribution? Can variable assists and inhibitorTakedowns considered to be the best predictor for winning a match, since it has the highest z-score, or is this thinking flawed?

Upvotes: 0

Views: 480

Answers (1)

hsaltan
hsaltan

Reputation: 531

The first thing that you should pay attention to is if a variable is significant or not given the level of threshold. It seems from your results that all are significant. Z-scores are used to see the level of significance. The second thing is to look at the coefficients to see which one has more impact on the label. The larger the absolute value of the coefficient, the more effect it will have. This effect may be positive or negative. The caveat here is, to standardize all predictor variables before putting them into the model. As you mentioned, they all come from different distributions. So, standardizing them will fix that problem.

Upvotes: 1

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