MLB players’ performance and salary

1B Avg, HR, Salary 2B Avg, HR, Salary 3B Avg, HR, Salary

Software 

Software used are Microsoft Excel, Tableau, and Notepad.

Source

Found my salary of MLB players through http://www.baseballplayersalaries.com/ and performance statistics through http://mlb.mlb.com/stats/ for 2014 season.

Data Extraction

Extracting the data with a simple copy and paste to a notepad.

Process

This process was easy since the data was easy to find on MLB’s website. It was an easy task of copy and paste to a Notepad and then uploaded to Microsoft Excel. This point I just had to clean the data which was simple. The next step was adding their salaries to Microsoft Excel which was a simple task of looking players up from http://www.baseballplayersalaries.com/ . After the data has been cleaned it was then uploading it to Tableau. Tableau allows you to drag and drop attributes you want use. I use scatter plot graph for my visual on this project. It allows you to also see clusters of players’ performance relative attributes I wanted to see.

Analyzing the Data

The visualization of my first graph using Tableau’s scatter plot has 1B representing position first base players. The x-axis has HR as home run and the y-axis Avg as avg hit per ball. The plots are circled with different sizes which determine their salary. The bigger the plots the bigger the salary of the player. Also the plots are different color to represent different players.The great part of using Tableau’s scatter plot is that it allows you to visualize the performance of a player by certain attributes and see if they are performing anywhere near what they are getting paid for. Also it can help show clusters of where most players stats are around.

As you can see for the first graph there is about 4-5 different clusters depending how you cluster the players together. The graph also lets you see outliers (a plot that is completely no where near the others) for example Jose Abreu of 36 home runs and a batting average of 0.317. Also you can see some players salaries aren’t as big, but still perform as well as high paid salary players for example Anthony Rizzo.

The same explanation is for the other graphs with different position of players of 2B (second base), 3B(third base) and so on.

The great thing about Tableau under each graph you make they explain the attributes you use and the detail of everything that needs to be explained about the graph produced from Tableau.

Baseball Team Salary and World Series

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Software

Software used is Microsoft Excel.

Source
Finding Major League Baseball salary through http://www.usatoday.com/sports/mlb/salaries/2014/team/all/ .

Data Extraction
Extracting the data with a simple copy and paste to a notepad.

Process
The process of this was a simple copy and paste to a notepad. After that I upload the file to an Excel and cleaned the data and sorting the data to my preference. The next step was sorting the data by “Salary” largest to smallest for each year. After that filling the team with proper visual analytics colors.

Analyzing the Data
The visualization shows MLB team salaries from each year from 2004 to 2014. Each column represents the lowest (bottom) to the highest (top) paid salaries. All the World Series Championships winners (highlighted orange) are aligned horizontally to easily compare relative team salaries.

I’ve also wanted to show a simple bar chart from 2004-2006 graph made with excel to compare the different visualization techniques.

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Both charts have its’ pros and cons. If I wanted something to pop out with a quick glance the first graph would be better, but if I wanted detail data the second graph would be a better choice.

The question we have to ask “Does a higher salary equate to a better chance or more World Series Championships? “