IB Math Studies Internal Assessment:
What is the Relationship between Points per Game Scored and the Height of the Players in the NBA?
By xxxxxxxxx
Candidate #xxxxxx
February 17th 20xx
Mrsxxxx
Contents
Introduction……………………………………1
Chi-Squared Test……………………………...2
Correlation Coefficient Calculations and Line of Best Fit Calculations………………………...3-4
Discussion/Validity……………………………5
Conclusion…………………………………….5
Raw Data……………………………………6-7
Bibliography…………………………………..8
What is the Relationship between Points per Game Scored and the Height of the Players in the NBA?
Introduction:
The NBA is one of the United States’ favorite sports leagues, with each team averaging 100 million dollars of income each year before expenses.
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Another limitation is that not all players play the same position. The goals of different positions vary from scoring, defending, passing and many others. There are point guards, shooting guards, small forwards, power forwards, and centers. Not to mention that strategies involving these positions have specific players take shots rather than everyone attempting to.
Adding on that, there might be a limitation to the amount of data that was collected. Only having collected 64 pieces it would have been better to collect all players from the NBA to better reflect the full span of players.
Lastly, one reason for a lower PPG is the coach’s decisions or being suspended. Benching a player (sitting them out) would cause them less game time for the season and thus reduce their average.
Conclusion
In spite of the aforementioned limitations, the project was done according to plan and it was found that the chi squared calculation value of 0.242226345, which is less than the chi squared critical value of 3.841, thus accepts the null hypothesis that points scored are independent values to their player 's height. By analyzing this categorical data it helps disprove that if you expect points to be higher with height you will be wrong. Furthermore, the investigation clearly shows that there is almost no correlation between points scored and height by looking at the r-correlation coefficient. The r-correlation coefficient comes out to be -0.048247472 which is
In this project, many different statistics were used to try and predict the winners of the NCAA March Madness tournament. To do this, statistics were tested from the previous year to see if they moderately correlated to winning games. When a stat is moderately correlated, that means it relates to winning. Using a scatter plot, a graph that gives a visual of whether or not a stat is correlated, correlation coefficients were found for each stat. The correlation coefficient is a decimal that shows if a set of numbers is moderately correlated. After finding stats that were the closest to being moderately correlated, a metric was put together that used the best stats to determine which teams will win games. The stat that was the closest to being moderately correlated was the turnover ratio of the teams. Another stat that was almost moderately correlated was RPI, or Rating Percentage Index. This stat uses a team’s win percentage, their opponents’ win percentage, and their opponents’ opponents’ win percentage to rank teams. Also, missed field goal percentage was a stat that was used.
For offensive tackles broad jump and vertical leap showed the greatest positive relationship because offensive tackles need those skills in order to perform their tasks in the field and if someone have a high broad jump it means that score in a vert leap also going to be positively correlated.
During the 2012-13 season, his minutes were increased to 35.15 per game, and he responded by averaging 13.3 PPG with 6.3 RPG. Through 54 games with the Sixers in 2013-14, he upped his average during to 17.4 PPG.
Orlando: defensively, also rank 18th, on average allowing 101.6 points per game. The Los Angeles Lakers offensively, rank 18th in the NBA, on average scoring 102 points per game. Defensively; the Los Angeles Lakers rank 27th in the NBA allowing 109.3 points per game.
It does seem like some important information is missing. For instance, how can you tell who has better skills based on the number of years playing the game? After playing for five years in the league, none of them may be an all-star. Perhaps the kid who started playing at age 11 is a better player than the three who have five years of experience.
Professional basketball is a game of giants. Players ranging all the way up to 7 feet and higher battle on hardwood to place a ball through the hoop. In the United States, the average height for males comes in at around 5 foot 10 inches. Existing in a seemingly alternate universe, basketball players even 6 foot or 6 foot one are considered short. Floating inside of this universe of massive men, Isaiah Thomas challenges the norm. Could a 5 foot 8 player possibly survive, let alone thrive inside of the universe of professional basketball? Isaiah Thomas resoundingly answers this question in the affirmative. Coming in at 5 foot 8, 185 pounds, Thomas’ miniscule height, even for an average man, leaves him gazing up at the opposition. Drafted with
It stands to reason that with a hoop placed 10ft off the floor, anyone who wants to put a ball through an 18in basket would need to be tall. However, throughout history, there have not been many people, men or women, that could reach that tall. This poses a unique challenge of having a person who can at least jump and throw a ball accurately enough to have the ball sink through the hoop. With that, there still needs to be some tallness to the person jumping and throwing the ball. Most people can only jump a few feet up into the air, and some are not even able to make it that high. So how tall does a basketball player need to be?
If you extrapolate that points percentage over a full 82-game season, that would be a 110-point pace, elite level performance.
A potential issue arises from talent identification as it is not an exact science and often subjective, and with research showing that physical and biological attributes alone do not have great effect on player skill in team ball sports (Burgess., 2010). The use of these should be limited or only used as a compliment to the broader decision-making process. However talent identification programs are heavily influenced by these measures (Abbott.,
The data for this folio was numerical data. The sample size was sufficient as the scores have been averaged out of twenty throws not four or five. Twenty was a good number as if was done that's not enough but if thirty-five or forty was done it gives us to much data and the possibility for an increased number of outliers. This creates problems when creating histograms as the classes range could be too great. Leading to the data not being shown in great detail. Patrick had two outliers while Angus had zero outliers. The outliers affected Patrick’s results because the two outliers increased his average to a higher score. Without Patrick’s two outliers his mean or average would have been 96.61 instead of 121.85. This shows how much Patrick’s two outliers made a difference to his average. The outliers also made a difference to his range. His range would have been 180 - 12 = 168 instead of 336 - 12 = 324. Some of the centre for Patrick’s data has been effected by the outliers and so has the
In basketball, in order to score three points the players have to shoot the ball behind the three-point line. In College this three-point line is exactly 19 feet and 9 inches away from the hoop. As a player practices and improves, his/her shot is going to improve, so in the NBA, to make the game more competitive they made the distance for three pointers 23 feet and 9 inches away from the hoop (TITUS). Although the three-point line changes this is the only real difference between a NBA and College basketball court. The foul line and court size still all remains the same.
Analytical data includes different psychological aspects of a player’s mentality. Stopwatches record times, tape measures calculate distances and heights, plus video gives scouts and coaches a visual look at player performance. However, for all their usefulness, they do little more than categorize athletes based on a series of numbers.
Regarding to basketball every single position on the floor is key to having a successful team, but to me the most important position on the floor is the point guard. The point guard in many aspects is similar to a quarterback in football, because they are in charge of getting their teams into the correct sets and controlling the game on the offensive end. Many time point guards are asked to carry on more responsibility.
In the year 1985 there was a major adaptation to the collegiate men’s game of basketball, it was the addition of the shot clock. This would have ripple effects throughout the game for generations to come. Now 30 complete seasons with the shot clock in place; the game has made progression into a national phenomenon. Throughout the country people focus on brackets and the champions, even the POTUS will make a bracket for this event. But I will be focusing on the past champions and the commonality between them to see if the game has made advances over the past 30 seasons. The purpose of this statistical analysis is to see if trends have formed or not within team stats of champions and their counterparts. There are many
Furthermore Wilt Chamberlin who played in the 60’s, in which he was only seven footer at the time and owned the league, held the previous record.