Correlation Between The Height Of Nba Players And The Average Points Per Minute Played

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Abstract

The National Basketball Association (NBA) is famous for the tall men who throw a ball through a hoop, but there is not much know about the influence of the length of a basketball player on the numbers of scores made. This study has showed whether there is a relationship between the length of NBA player in the Western Conference and the average number of scores they make per minute. The sample consisted of three teams which participate in the Western Conference: Golden State Warriors, Denver Nuggets and Portland Trail Blazers. This is done by the use of a two-sided Pearson correlation test, and the calculation of the t-test statistic for which a p-value below 0.05 is considered significant.

The results of the test statistics showed that there was no correlation between the length of the players and the average number of scores per minute. This means that there is no relationship between the two variables and that the ability to score points a certain number of points in a basketball game is not related to the length of the player.

Introduction

The National Basketball Association (NBA) is the professional men’s basketball league in the north of America, which consists of a collection of thirty teams each playing a total of 82 games all over the season. This season’s average score at the end of a game for a certain team was 111.2 points made, according to the site of basketball-reference (NBA League Averages - Per Game, 2000-2019). This are high scores, but it is not known whether there is something specific causing the scores to be this high. In this study, there will be studied whether length has an influence on the number of scores made by an individual player in the western conference league of the NBA.

There has been done some research on the female area of the basketball sport in the last years, but not so much on the male part of the sport. There has been done some research which had to do with the height of American basketball players and their health. For example, the study done by S. Lemez, which showed that the tallest players lived a shorter live than the smallest players (Lemez, 2017). Another study showed that the correlation between team assists and win-and-loss records are higher than the correlation between unassisted points and win-and-loss records (Melnick, 2001). But there no answer related to the question whether there is a relationship between length and scoring ability of NBA basketball players in the Western Conference.

In this study there has been taken a look at the correlation between the length and the average scoring capacity per minute of all the players in the Western Conference, one of the two conferences which together make up the National Basketball association (NBA) in the north of America. The study has a focus on the top three teams of the season 2018-19, which consisted of the Golden State Warriors, Denver Nuggets and Portland Trail Blazers.

In order to answer the research question there will be performed a Pearson correlation test by calculating the correlation coefficient, and the t-statistic with the corresponding p-value with a significance level of 0.05. The hypothesis is that the taller the NBA basketball players are the higher their average number of scores per minute is.

Materials and methods

Research individuals

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The test subjects (n=51) who were observed in this study were all male NBA basketball players playing for teams which played in the Western Conference, from different origins, mostly America. The players had played basketball games in the season of 2018-’19 for one of the top three teams of the Western Conference; Golden State Warriors, Denver Nuggets, or Portland Trail Blazers. The test subjects represent one small random sample of the entire population of male NBA basketball players who participated in at least one game for their team in the studied season, 2018-’19. The data for this study was collected on one specific date, 13th of May 2019. At this date all the games of the regular season were played, so in this study the playoffs were not take in the data collection. The variables which were compared, length and the average number of scores made per minute, were seen as normally distributed procedure

The data which was used for the study included the length, total number of points which were made over the season and the number of minutes which were played over all the games, separately for each player. The primary source used to find these data was the official website of the National Basketball Association, were most of these player statistics, length, total number of points scores and the number of minutes played, were already listed (NBA advanced stats, 2019). The rest of the data which was needed, the average number of scores made per played minute, could be calculated from the found data. With the use of excel, there was made a scatterplot with the length of the players plotted against the average number of scores per minute played for each player.

Data analysis

To analyse the data, the correlation coefficient of all the data points together was calculated using the Pearson correlation test method. Because both variables were seen as normally distributed and the sample was consisting of independent individuals, the Pearson correlation test was the test to be used. To perform the test there was calculated the correlation between the length and the average number of scores per minutes played of every individual in the sample of NBA basketball players. The correlation coefficient and the p-value for a two-sided correlation t-test were determined with a statistical significance level () of 0.05. The test was performed to check whether the data support the hypothesis that there was a positive correlation between the two variables, the length of NBA basketball player and their average number of points scored per minute.

Results

The correlation between the length and the average scores made per minute player is displayed in figure 1. The different colours are there to show that the players are form different teams. The study showed that there was a negative correlation between the two measured variables, the correlation coefficient r = -0,1834906, however this result is not significant, the p-value was equal to 0,19744188 and only a p-value for a two-sided test below 0.05 would be considered significant, so these results considered significant

r = -0,1834906,

p = 0,19744188

The correlation between the length and the average scores per minute played of NBA basketball players over the season of 2018-'19. Including the correlation coefficient, and the p-value. The data about the length and average scores per minute was collected for 51 basketball players who played for one of the following NBA teams in the season of 2018- ‘19: Golden State Warriors, Denver Nuggets or Portland Trail Blazer.

Conclusion and discussion

The study examined whether there was a relationship between the length of NBA basketball player and their average number of scores per minute played. The results showed that there was no significant result, a p-value of 0.19744188 with a statistical significance level of 0.05, so the expected hypothesis, that there is a positive correlation between the length of NBA players in the Western Conference and their average number of scores per minute played, should be rejected. The results of this research showed that there is no relationship between length and average number of scores per minute played when taking a sample of NBA players in the western conference and only the data of season 2018-’19 is considered.

Based on this study, it can be concluded that there is no relationship between the length of NBA basketball players and their average number of scores per played minute. This is not the result which was expected, however there are multiple things which can have an effect on the performance of professional basketballers. The statistics per game differ because the conditions are never the same, in every game there are different opponents to which the tactics are adjusted, more focus on the offense or on the defence. When there is more focus on defence, there will be less scores for the entire team. Likewise, the position of each player on the field can impact their scoring ability, but also age and injuries can have an influence on the number of scores that can be made in a game. These factors are not considered in this study, but might have made a difference.

The results of this study might have been influenced by the assumption that the two variables, length of basketball players and the average number of scored made per minute, are normally distributed. This is the case for the variable of length, but the distribution of the average number of scores is a bit skewed to the right, which could have led to different results if the spearman correlation test was used to calculate the results. Also, the sample of the top three teams in the Western conference of the NBA are maybe not the best to represent the total of players in the Western conference NBA competition. This also could have resulted in errors in drawing a conclusion because a different sample with a few players of all the different team might have given a totally different result.

The result of no correlation between length and scoring ability could influence the tactics of NBA teams in the future. Previous research showed that there is a link between playing as a team and the win-and-lose records of the team (Melnick, 2001), the combination of the study of Melnick and this study there could be thought of different game strategies because the length of the player does not necessarily have an influence on the ability to score, but playing as a team has. This could lead to higher win-and-lose records and higher total scores per game.

In this research all the points made during the season of 2018-’19 have been used as data, but in further research there could be differentiated between different distances to the basket, for example the categories, free throw, field goals, and three-pointers. That would give a more elaborate view on the ability of players of different lengths.

This study showed that there is no significant relationship between the length of an NBA basketball player who plays for a team in the Western Conference and the average number of scores made per minute played. This means that the length of a player has no influence on their ability to score points in a basketball game.

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