Data Visualization report on NBA Games using Tableau and Power BI.

1. Data Visualization Analysis on NBA Player’s
Subject: Data Visualization
Inderpreet Singh Chawla
X01523951
National College of Ireland

2. Abstract
National Basketball Association (NBA) is one of the
most popular League in the world. NBA is highly
recognised for innovative and entertaining league in
the United States and Canada. NBA shows the greatest
fans on globe. There is no any league brings what this
game gives to their fans every season. People are so
much passion and excited to take part in this game
that’s the reason why NBA is popular. This paper uses
the study of novel measure to analyse the performance
of NBA players and it investigates how team in the NBA
plays closely with their potential. Specially, this study
has certain subsets of different players like, usage
percentage, field goal attempts, shooting, players
salary and win percentage of team etc. I am using
Tableau, Power BI and excel to Visualize the data and
the datasets is regarding the Social Power NBA on the
court performance with Social Influence, Popularity
and Power in the season of 2016 to 2017.
Keywords: NBA, Salary, League, Win percentage.
Introduction
National Basketball Association is currently the 3rd
largest sports professional league in the America with
the overall revenue of $5 Billion dollars. NBA also highly
paid to its players. With the interest and cheers in the
NBA, fans have interest on players salary. [1] NBA
player always impact the game with their strategies
either offense or defence. However, the NBA league
were not always acclaimed. NBA struggled also to gain
popularity amount the sports fans. [2] whereas
basketball was not popular in 1940s and the college
basketball team shown the attraction in this game.
Moreover, there is a shortage in the empirical
investigation that effect the wining experience in the
sports economics. NBA also relegated to assumption
that experience is always impact on wining than
inexperience and this assumption changes the attitude
on the player into winning and losing the game. There
are 30 team in the NBA and it was founded on 6 June
1946 in NEW YORK USA. In this paper, I try to present
the study of NBA to understand the performance and
experience of team. Player have played highest
competition in their entire lives. [3]
Data source: - Understanding the datasets for better visualization and analysis is very important. I have taken NBA
dataset from Kaggle with the name of Social Power NBA that published on August 2017 which consist of different
column like, Player name, Age, GP, L, MIN, DEF_RATING and so. it is in CSV format. Below table gives more details
about the datasets. Available: https://www.kaggle.com/noahgift/social-power-nba/data [4]
Published on: “August 2017”
Player Name Name of the player in the team.
Age Player age.
GP Game played.
W Game played where team won.
L Game played where team lost.
W_PCT Percentage of game played won.
MIN Minutes played.
DEF Rating Player defensive rating.
OFF Rating Players offensive rating.
PIE Player impact factor on the game.

3. Sample Datasets: -
FIG:1
Implementation and Visualization
Case Study: 1
Which player performance is best among 20 top players in NBA?
FGA Field goal mage attempted.
Salary Player’s salary in million.
PTS Points scored.
Twitter follower People followed on twitter.
Pace rank League rank pace score.

4. FIG:2
This Bar chart shows the performance of top 20 NBA players. We are measuring the performance of players with the
help of Game played correspondence to Game won and loss. We can see that Y Axis defines the performance by
Game played in Blue, won in green and loss in red colour. Whereas, X Axis defines the Players name. Here, best
performer in NBA 2016-2017 was David Lee as he played 79 games in which he won 58 and 21 loses. So, ratio of
winning game is high compare to game loss. Similarly, David West also played very well in NBA where he won 56
games out of 68 games. Moreover, Lebron James also won 51 and lose 23 games out of 74 games. On the other
hand, Carmelo Anthony loss more games i.e. 45 out of 74 games. so, winning and losing the game always depend
upon the experience and practice as practice makes the man perfect. Tableau is used to made this chart.
Case study: -2
Does Age effect the winning Game?
FIG:3

5. This line Graph shows performance of players with their AGE. Here, Y axis tells about the percentage of Game
winning and X axis tells different Age varies from 18 to 39. From the graph, we can see that Age between 18-24 has
low winning rate that is not more than 9.7 percent. Whereas Age 27 gain the highest winning rate that comes to
18.56 percent. On the other hand, performance of player from age 30-39 is continuously decreasing. We can say that
age effect the performance of the player as performance of player is decreasing after age 27. we can also predict
that players between age 24 to 30 has high stamina because they have good winning percentage.
Case study: - 3
Does Players have both Offensive and Defensive Strategies?
FIG:4
This Butterfly chart describes the players strategies and skills to perform well in the game. Here, we are analysing
top 30 players performance on the behalf of offensive rating that recognised by green colour and defensive rating
that is recognised by orange colour. We can see that Brandon Bass has the highest offensive rating with 116.70 and
defensive rating with 103.70. Whereas, 2ND
highest rating is Carmelo Anthony with 111.10 offensive rating and
defensive rating with 106.10. but on the other side, JaVale McGee has highest offensive rating with 121.40 and
102.30 defensive rating. So, we can conclude that all players have both similar capabilities to perform in the game as
some have high defensive rate and some high offensive rate but there is not so huge difference in both capabilities.
Case study: - 4
Comparing Average minutes player played with point scored in top 10 NBA Team.

6. FIG:5
This Pareto chart tells about the point scored by the team in 2016 to 2017 with respect to minutes played in the
game. Here, average minutes played is represented by green colour and Average point scored is represented by
yellow colour. From the chart, we can see that player from Team Cleveland Cavaliers scored highest point in NBA i.e.
19.15 with highest minutes played in the game. i.e. 29.53. Similarly, Memphis Grizzlies also scored 15.225 point with
2nd
highest minutes played i.e. 26.98. So, we can conclude that team those have highly professional player plays long
time in the game and scored high points that leads to win the game. On the other side, Team like Detroit Pistons
scored low points i.e. 10.225 with low minutes that explains the poor performance and player skills.
Case study: - 5
Player performance with Goals made and Point scored.

7. FIG:6
Diverging chart
FIG:7
Bar graph Team won
This diverging bar charts show the player name with Goals made and point scored in NBA. Here, blue colour
represented by average fields goals made and grey colour represented by Average Point scored. We can see that the
top position occupied by the LeBron James with 736 goals in the league and scored 26.40 points. Similarly, 2nd
position occupied by the Carmelo Anthony in which he scored 22.40 points with 602 goals. On the other side,
Collison, David West and Brandon Bass scored the lowest points with 1.60,4.60 and 5.60 respectively. From the bar

8. graph, we taken top 30 player contribution in the team. we can see that Lebron James comes to 6th
position
represented by green colour in overall winning team that means rest of the players in Lebron Team does not
performed well in the League. Similarly, Carmelo Anthony comes at 23rd
position with 29 won percentage that
means his team also not performed well. On the other hand, David west and Collison performance was not good but
their team scored well in the league. It means that another member of their team performed well in NBA.
Case study: 6
Does Pace factor of player effect the Game won?
FIG:8
This Bubble chart explains about the Pace factor to win or lose the Game. We can see from the chart that JaVale
McGee has high Pace factor that is darker in colour and Average percentage of game won is also high. Similarly,
Stephen Curry has also high percentage in both Pace factor and game. But Ruby Gobert has low Pace factor i.e.
lighter in colour with low rate in game won that means chances of winning is high if player have Pace factor.
Case study: 7
Which Team is paying high salary to their Players?

9. FIG:9
This Funnel chart describe about different team with Player salaries. Team represented by different colour are the
dress code of the team. Here, team is paying huge salary to their player based on their performance and strategies.
The highest salary payed by the team Cleveland Cavaliers i.e. 70.77 Million and Los Angeles Clippers that is 66.63
Million to their players and Golden State Warriors as well. Whereas, Philadelphia and Los Angeles Lakers has paying
low salaries to their players. The reason paying high salaries to their players is that their team players performing
very well in the game. We can see from the above table that team like, Golden State Warriors, Cleveland Cavaliers
and Los Angeles Clippers is at the top in the list of their performance.
Case study: 8
Comparing Players impact factor with Team Name.
FIG:10

10. This Tree maps tells the maximum Impact factor of the players to win the game. We can see that highest impact
factor of team Oklahoma City Thunder i.e. 0.23 and 2nd
highest impact factor is with Detroit Pistons whereas the
lowest impact factor is with Los Angeles Lakers. Impact Factor is measures by the overall contribution of the player
to win the game. We can say that team with high impact factor has performed well in the League.
Case study:9
Player name vs Twitter fan followers.
FIG:11
This pie chart explains about the maximum followers of the players. We can see that LeBron James has the highest
fan followers on twitter i.e. 37 million. Whereas, 2nd
highest fan followers were Kevin Durant that is 16 million and
rest of the players have less followers on twitter. It means that people likes the performance and strategies of player
who performed well in the game.
Case study:10
Player those have good goals percentage have the True shooting percentage to win the Game.

11. FIG:12
This Stacked column chart shows the True shooting percentage with respect of high Goal percentage in the NBA.
Here, True shooting percentage of the players presented by Pink colour and Field Goals percentage presented by
dark grey colour. We can see that player like, Jarnell Stokes, Demetrius Jackson and Tyson Chandler has high True
shooting percentage and Goals percentage that’s the reason of team won. Whereas, players like David West, Blake
Griffin and Kemba Walker has low Goal percentage and True shooting percentage. We can say that successful Team
will be those have all skill and strategies to win the game.
Conclusion: -
Overall, this project basically focused on the Basketball data and with the visualization tools like TABLEAU
and POWER BI we addressed the business queries by using different charts and graphs. As a result, from
above visualization, it seems that there are several factors varies to win the Game either it would be less salary,
over age, low stamina or less practice. From the observation, it concludes that all-rounder players should plays an
important role in winning match. Players those are good performer should take the lead to train their inexperience
player or the new once so that there will be no chance to lose the game and association should also take care of
their players.
Reference: -
1. Jason Huang, “Salary in the National Basketball Association” 2016. [Online]. Available:
https://repository.upenn.edu/cgi/viewcontent.cgi?referer=https://www.google.ie/&httpsredir=1&article=10
09&context=joseph_wharton_scholars [17/2/2018].
2. David G. Surdam,” The Rise of the National Basketball Association” Available:
https://muse.jhu.edu/chapter/678101 [17/2/2018]
3. James Tarlow, “Experience and Winning in the National Basketball Association”, Available:
http://www.sloansportsconference.com/wp-content/uploads/2012/02/18-James-Tarlow-Sloan-Analyitcs-
Conference-Submission-in-template_updated.pdf [16/2/2018]
4. Noah Gift,” Social Power NBA”, Available: https://www.kaggle.com/noahgift/social-power-nba/data
[17/2/2018]