Information

This dashboard shows one visualizations:

• A Line graph with two different statistics

Sources:

1. NBA Time Series dataset

1st Visualization: My first visualiztion is a visualization that expresses the NBA teams Offensive rating and offensive pace over the years(1980-current). Offensive rating being a stat that esentially rates how well the offense performs through a process of many different equations, The higher the better. Offensive Pace is a stat that puts the rate at which the offense runs up and down the court. The higher the rating the more possesions a team has, which means more shots being taken.

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Information

This dashboard shows three visualizations:

• A 3 point field goal made per game time series
• 10 top 3PM per game teams during the 2021 Season
• A Bar graph of all time three point leaders

1. NBA Time Series dataset
2. NBA 3PG
3. NBA All time 3 pointers made

1st visualization: My First visualization is a time series of multiple different 3 point statistics through the history of the NBA since the 3pt line was introduced(stats were kept from 1980-current). It provides information like the rise of shots attempted, shots made.

2nd visualization: My second visualization stems from the first as you can see in the first visualization the year with the highest 3 point field goals attempted per game was 2021 so I wanted to look into that year specifically and see what ten teams, made the highest number of 3 point field goals (3P FG)per game, so I created a Bar Chart with the top 10 teams in 3P FG per game in 2021.

3rd visualization: My third visualization is another 3 point made related graph, but this time its by player(3 point line creation-current day). I noticed most three point shooters were recent and so I looked at the top 10 players in total 3 pointers made. And low and be hold all but 1 player are still current, or retired in the last 10 years. Explaining once again the scoring boom.

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Information

This dashboard shows one visualizations:

• Steals and Blocks Visualization

Sources:

1. NBA Time Series dataset

1st Visualization: My first visualiztion is a visualization that expresses the NBA teams Ability to produce turnovers(since 1980), with stats such as steals and blocks. The more turnovers the less oppurtunities to score for the offense, and as you can see the turnovers decrease which helps describes the scoring jump.

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Information

This dashboard shows 2 visualizations:

• Turnover Line graph
• Turnover perctengae Line Graph

Sources:

1. NBA Time Series dataset

1st Visualization: My first visualization is a line graph that shows the number of turnovers a game since 1980. This helps my explain why NBA teams are scoring more, becuase if the teams commit less turnovers(possessions where the team gives the other team the ball) then they have more chances to score.

2nd visualization: My second visualization is a line graph showing teams turnover percentage since 1980. Turnover percentage is a stat that explain what percentage of possessions end in a turnover. And i felt this was useful because as we saw before turnovers decreased, but possessions increased like we saw earlier so i wanted to see what the percetnage of the increased possessions were also turnovers.

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Information

This dashboard shows one visualization:

• Leaflet map of NBA players

Sources:

1. NBA Birth Countries

1st Visualization: My visualization is a map of the world that specifies what countries NBA were born in. The Darker the Country the more NBA players born in that Country.

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