Step 4 : Data Splitting

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• Split your data into training and testing sets to evaluate your model's performance.

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need to do for both models @Shmulvi

• create a winner prediction model
• create a home score prediction model
• create a away score prediction model

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compare the actual and prediction plot and observe for the outliers tune the model

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There are some points that are far away from the red line, especially in the higher actual score range (>200). These points indicate instances where the model's predictions were considerably off from the actual values.