NBA Positional Analyses

Preregistration of analyses

Analysis #1

Research question: Which NBA player position is the most impactful based on the highest cumulative average of the chosen offensive statistics combined (points, assists, offensive rebounds, turnovers)?

Null hypothesis: All NBA player positions are equally impactful based on the cumulative average of the offensive statistics combined (points, assists, offensive rebounds, turnovers).

Alternative hypothesis: At least one NBA player position is more impactful than the others based on the cumulative average of the offensive statistics combined (points, assists, offensive rebounds, turnovers).

Analysis plan: For each individual NBA player position (ex. point guard, shooting guard, etc.), we are going to find the average for each individual offensive statistic category (points, assists, offensive rebounds, turnovers). After this, for each individual NBA player position, we are going to add up each beneficial offensive averaged statistic (points, assists, and offensive rebounds), then subtract the harmful averaged statistic (turnovers). Then, we will compare this total value to every other player position. Our criteria for being the most impactful NBA position is whichever cumulative average of offensive statistics is the highest. For example, for the ‘point guard’ position, we are going to add up each player’s total points, and then divide this number by the total number of point guards. We will then repeat this process for the rest of the offensive statistics for point guards. Then, we will add together each beneficial averaged offensive statistic for point guards, and then subtract the harmful average statistic (turnovers) for point guards. This total number will be the point guard’s ‘positional impact rating’. We will repeat this process for the other four NBA positions, and then compare each ‘positional impact rating’ to see whose is the highest. We will conduct a hypothesis test to determine if the difference between each position’s ‘positional impact rating’ is statistically significant.

Analysis #2

Research question Which NBA player position has the highest disparity between field goal percentage and free throw percentage?

Null hypothesis: Each NBA player position has an equal disparity between field goal percentage and free throw percentage.

Alternative hypothesis: At least one NBA player position has a higher disparity between field goal percentage and free throw percentage.

Analysis plan: For each individual NBA player position, we will find the average of their field goal percentages, and then the average of their total free throw percentages. After we get these two values for each position, we will find the difference of these two values for each position. This value will represent the disparity between each position’s field goal percentage and free throw percentage. For example, for the ‘point guard’ position, we will add up each player’s field goal percentage, and then divide this number by the total number of point guards. Then, we will add up each player’s free throw percentage, and then divide this number by the total number of point guards. After we calculate these two averages, we will subtract averaged field goal percentage from the averaged free throw percentage to determine the disparity of this position’s field goal percentage and free throw percentage. This number will be called the ‘positional disparity percentage’. Then, we will repeat this process and find the other four positions’ ‘positional disparity percentages’. We will conduct a hypothesis test to find a p-value that will determine whether or not the difference between each position’s’ ‘positional disparity percentage’ is statistically significant.