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Simple Linear Regression

Learn about simple linear regression in NFL point spreads from 2007, where bookmakers provide spread predictions for home and visiting teams. Explore the accuracy and variability of predictions through statistical models and tests.

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Simple Linear Regression

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  1. Simple Linear Regression NFL Point Spreads – 2007

  2. Background • Las Vegas Bookmakers provide a point spread for each game • The spread reflects how many points the home team “gets” from the visiting team (negative values mean the home team “gives” points to visitor) • If bookmakers are accurate, on average the actual difference should equal prediction • Accurate ? How variable ?

  3. Statistical model

  4. Summary Statistics / Regression Equation

  5. Testing normality of errors (I)

  6. Testing normality of errors (Ii)

  7. Example – NFL Spread errors

  8. Testing accuracy in mean • H0: b0 = 0, b1 = 1 • HA: b0≠ 0 and/or b1≠ 1 • Fit Model UnDer H0: Y*=X • Obtain error sum of squares under Y* • Compare with error sum of squares from full model (HA).

  9. Testing for Accuracy

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