Aws4 request&x amz signedheaders=host&x amz signature=11eae16cc2787dac0aa47f1397b2ec3fd2854c3830dffaaf853a51f065152b2e
Professional sports teams drop serious cash to try and secure the very best talent, and the dough can really pile up. But is all that money well spent? Conventional wisdom says that teams with higher payrolls ought to perform better than those with more modest means. Some leagues have even instituted limits on spending in order to make games more competitive.

But do higher-spending teams really do better, and do salary caps actually level the playing field? In this lesson, students look at data for four major pro sports leagues and try to answer the question: Can you buy wins?

Students will

  • Use technology to calculate linear regressions for wins versus team salary for major professional sports
  • Compare relative strengths of linear associations using correlation coefficients
  • Interpret the slope of a linear regression function in context
  • Discuss the effects of salary caps on the relationship between wins and team salary
  • Given regression functions and correlation coefficients, examine the relationship between wins and several other variables
  • Discuss the difference between correlation and causation

Before you begin

This lesson focuses on interpreting linear regression functions and correlation coefficients in the context of sports salaries. Students should be able to use technology to compute correlation data for two quantitative variables.

Common Core Standards

Content Standards
Mathematical Practices

Additional Materials

  • Graphing and regression technology

Shoutouts

MLB, NFL, NHL, NBA, Andy Rooney