Challenge #18: Predicting Baseball Wins

[RWvanLeeuwen]

This is my proposed solution: I performed association analysis using Pearson's correlations. Next, I manually selected those fields and modelled the complete dataset using only those predictors  - and I explicitly disregarded any multicollinearity, assumptions checking etc. Subsequently I used that model to score the teams of interest and added two more fields: [Projected Losses] = Round(162 - [Projected Wins], 0)

[Games Back] = Round([Max_Projected Wins] - [Projected Wins], 0)

This shouldn't be the best way to perform this type of analysis as I'd prefer working with stepwise elimination and VIF and checks for multivariate normality... However, my results match with the solution... I'd suppose I should get a badge for this

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[echuong]

Good practice with predictive tools! Also included a win difference percent to see how the model did

[joemkcarr]

Good to learn a bit of predictive 

[Hannah_Lissaman]

My solution 🙂 

[myastarling]

Fun fun fun! Full disclosure, I've never used the Association Analysis tool before so I did have to take a peek at a solution for this part.

[phottovy]

Fun challenge!

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[KMiller]

Solution attached

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[bnelly1987]

Great Challenge for learning the predictive tools!

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[mpennington]

Solution attached.  

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