Assessment 4
DATA4100
Data Visualisation Software
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List of Figures
Part A
Business problem
“How can basketball teams improve player performance by analysing rebounds, assists, fouls, and shooting efficiency using data visualizations?”
By analysing data on rebounds, assists, fouls, and shooting efficiency, basketball teams can identify areas for performance improvement. Teams can focus on increasing assists, managing fouls, and improving shooting drills to optimize gameplay. Data visualizations will provide clear insights into player and team performance that is guiding targeted coaching and strategy adjustments.
Part B
Analysis of dashboards
The analysis part is completed by using the Power BI tool.
This bar graph shows the distribution of rebounds (total) and assists across various teams. Each team is listed along the horizontal axis, including IND, ATL, SAN, and others. The vertical axis measures the values of rebounds and assists, with most teams showing higher rebound values.
This tree map visually highlights the top five players based on their performance values. Maya Moore leads with a score of 23.88, followed by Skylar Diggins at 20.09. Candace Parker ranks third with 19.43, while Angel McCoughtry and Elena Delle Donne score 18.52 and 17.88, respectively.
This donut chart highlights the players with the highest fouls, indicated by percentages. Chiney Ogwumike leads with 3.65 fouls (15.9%), followed by Sylvia Fowles with 3.38 fouls (14.7%). Other players include Courtney Paris, Brittney Griner, Glory Johnson, and Erlana Larkins.
The graph illustrates the shooting performance of the top five players, plotting field goals versus points. Each player has different goals: Angel McCoughtry, Candace Parker, Elena Delle Donne, and Maya Moore.
The "Players Comparison" radar chart evaluates the efficiency of players including Maya Moore, Candace Parker, Candice Dupree, and others. The orange region represents maximum efficiency across different players like Erika de Souza and Shoni Schimmel, showing balanced performance on various attributes.
The image shows a basketball match result. The team scored 76.43 points and won against the opponent who scored 75.91 points. The match was played away.
The graph shows the total rebounds and steals for different basketball teams. The team with the most rebounds is ATL, and the team with the most steals is WAS.
The graph shows the top 5 teams based on the sum of their wins. MIN has the most wins with 25, followed by ATL with 18, LAS with 15, TUL with 12, and CHI with 10.
The graph shows the number of assists made by different opponents in a basketball game. The largest number of assists was made by the opponent NYL, followed by the opponent and SAN. The percentage of assists made by each opponent is also shown.
The image shows a summary of a basketball match. The team won the match with a total score of 2010 points. The match was played away and lasted 83K minutes. The team attempted 7584 shots and committed 7456 fouls (Agarwal, 2024).
The image shows the three-point shooting percentage for different basketball teams. The highest percentage belongs to SAN, and the lowest belongs to ATL.
The image shows the sum of steals for different basketball players. The player with the most steals is Sancho, followed by Angel and Erlana.
The image shows the top 5 players based on the sum of their wins. Maya Moore has the most wins with 25, followed by Angel McCoughtry with 18, Candace Parker with 15, Skylar Diggins with 12, and Elena Delle Donne with 10.
The image shows the total rebounds and steals for different basketball players. The player with the most rebounds is Erla, and the player with the most steals is San (Mammoth, 2024).
The image shows the number of assists made by different basketball players. The largest number of assists was made by Erlana Larkins, followed by Brittney Griner and Courtney Paris.
Figure 17: Drill through on the team dashboard
Figure 18: Drill through for player dashboard
The drill-down function in Power BI allows users to explore hierarchical data by going deeper into more detailed levels. By clicking on data points, users can move from summary information to specific details, enhancing data analysis and insights.
Interpret of dashboards
Figure21: Dashboard 3
The dashboard visualizations provide insights into team and player performance in women’s basketball. In the Bar graph of Rebound and Assist Distribution, the highest number of teams has more rebounds compared to assists (Avijeet Biswal, 2020), though some outstanding teams like IND and ATL top the lot in both aspects. The Top 5 Players Treemap shows that Maya Moore is the top among them; Skylar Diggins is in the second position and Candace Parker is in the third. The Fouls Trouble Donut Chart shows that some of the players who have high foul counts are Chiney Ogwumike and Sylvia Fowles, from which foul management in these athletes will be imperative. The Radar Chart compares player efficiency and shows that Maya Moore, and Candace Parker, among others, show balance in their contribution. Further, Team Rebounds and Steals reveal that ATL does exceptionally well in rebounds, while WAS steals are one of its strong points. The Top 5 Teams by Wins lists MIN at the top with 25 wins.
Recommendations
Rebound Focus: Teams in the mold of IND and ATL should keep doing what they do best, while others need to improve through positioning and training.
Improvement by Assists: Those teams that have fewer numbers in assists should try to play the ball so that their skills can be improved.
Foul management: Chiney Ogwumike and Sylvia Fowles are some of the players who need focused coaching on minimizing fouls, hence avoiding turnovers with resultant penalties.
Shooting Efficiency: Teams with lower three-point percentages, especially ATL, need to work more on shooting drills and optimize their shot selection.
Part C
Pre-attentive attributes and Tufte's principles
The visualizations also fit well within cognitive load theory as they take large amounts of information, distilling it into easy-to-understand concepts, thus decreasing the cognitive load on the viewer. Pre-attentive attributes such as colour and size are utilized in Figures 1 and 2 through the use of bar graphs and tree maps to enable users to easily identify key players and teams. For instance, one’s first impression of Maya Moore is her outstanding display, which can be observed in the tree map because of her larger block. Tufte’s principles are followed because chart junk is avoided—each chart is simple and contains only the data necessary, for example, a donut chart in Figure 3 that conveys player fouls through percentage without additional frills. In particular, the radar chart in Figure 5 allows for comparing players’ efficiency along multiple metrics in a clear and tidy manner. These visuals incorporate detailed quantitative data into appealing designs while avoiding excessive cognitive load and ensuring that important insights stand out due to a hierarchy of visual elements.
Reference
Avijeet Biswal (2020). An Introduction to Power BI Dashboard. Accessed 5 Oct. 2024, <https://www.simplilearn.com/tutorials/power-bi-tutorial/power-bi-dashboard>
?Mammoth (2024). Best Power BI Dashboard Examples for Data-Driven Decisions. Best Data Management Platform | Mammoth Analytics. Accessed on 5 Oct. 2024, <https://mammoth.io/blog/power-bi-dashboard-examples/>
?Agarwal, V. (2024). Top 10 Power BI Dashboard Examples for Finance and Accounting. [online] GrowExx. Accessed on 5 Oct. 2024, <https://www.growexx.com/blog/top-10-power-bi-dashboard-examples-for-finance-and-accounting/>
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