What Makes a Great Baseball Player? 

Role: Data Analyst & Visualization Designer
Tools Used: Tableau, Excel

GOAL

Use Tableau to explore what sets great baseball players apart: How do we define a ‘great’ player? Are they left or right handed, or both? Are they taller? Heavier? The objective is to highlight relationships and communicate findings in a Tableau story.

WHAT I DID

• Use Tableau to examine a dataset of 1,157 major league players and 5 statistics

• Highlight characteristics that set great players apart from the rest

• Create a Tableau Workbook Story to communicate findings

Background

What makes a baseball player great? Sure it's a combination of catching, throwing, hitting, and running. However, as Yogi Berra said, baseball is more of a mental game. It is a game of endurance, passion, reaction times, focus, excellent vision, eye-hand coordination, confidence, ability to rebound from failure, stress management, practice, adaptability, motivation, and much more.

Batting average is a common statistic but rarely tells us a complete story—a player might hit the ball every time at bat but when a fielder catches it their batting average remains zero. A pitcher might use a pinch hitter, also having a zero batting average. There are also more complex sub-statistics; Michael Lewis illuminated the importance of these in 'Moneyball': on-base percentage (OBP), on-base plus slugging (OPS, total bases divided by times at bats), and secondary averages.

Although we don't have access to sub-statistics or mental traits, our dataset does include handedness, home runs, batting average, height, and weight. I added an additional column for Body Mass Index (BMI).

Process

I used Tableau workbooks and dashboards to explore the dataset, then weaved these into a final story.

I used histograms for batting average and home run distribution data. There are many players that have a zero batting average and no home runs; these are likely pitchers and can be treated as outliers. I created handedness (left, right, both) and performance (elite, mid, low) filters for users to toggle between, and color coded both. I used box plots to compare performance to handedness, height, weight, and BMI to best view medians and variations.

I defined 'elite' players as the top 0.02% (22 out of 1,157). They have more than 300 home runs and a batting average above 0.24.

Conclusion

Although physical traits tell a small story of what makes a player 'great', or elite, the most significant relationships I found in this dataset are:

• Elite players usually favor a hand, left or right, rarely both. However, since only 9% of our dataset are both left and right handed and our dataset has only 1,157 records (a relatively small sample of the over 15,000 players in baseball history), this might not be correlated.

• Elite players are heavier; they tend to weigh 5 pounds more and have 1 higher Body Mass Index.

• Elite players that are right-handed have a higher batting average. Overall, left-handed players have a higher batting average.

VISUALIZATION

Screen shot of the Tableau story: