Batter Up!

Problem/Question

Does a Major League Baseball player’s age affect his batting average?

Hypothesis/Conjecture

I think a player’s age will affect his batting average and that the older players will have a better batting average.

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Materials

Microsoft EXCEL Program

Computer

2019 Major League Baseball Team Roster (30 teams) and Statistics

Calculator

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Procedure

• With the help of my mom, I found rosters for each team that played in the 2019 season of Major League Baseball. We found the rosters on the internet.
• We “copied” the hitters from each list to the cells on an EXCEL worksheet.
• Then we sorted each hitter into one of four categories: 24 years old and younger, 25-29 years old, 30-34 years old, and 35 years and older.
• We wanted to pick 8 players at random from each category. To do this, we first sorted the players from youngest to oldest player and color-coded each of the four groups. Each player had a number assigned to it. I picked 8 numbers for each category and each of my numbers stood for a player on the color-coded list. This was important because the players had to be chosen randomly, otherwise I could have chosen the players with the best average.

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Procedure

• We made 4 new lists including only the new 8 players chosen from each age group.
• We created a table with each player’s age, number of hits each player had in 2019, the number of at bats in 2019 and the player’s batting average.
• Using a calculator I found the average batting average for each age group and then we created a bar graph showing the average batting average for each age group.
• I repeated this process 2 more times to test the validity of my experiment. The 3 groups of tables and bar graphs are called Test Group A, B and C.

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Test Group A Data

Data Table-Test Group A

Test Group B Data

Data Table- Test Group B

Test Group C Data

Data Table- Test Group C

Average Overall Data

Average Overall Results

Conclusion and Proofs

My hypothesis was supported. My results prove that a player’s age will affect his batting average since that overall players ages 35 and older had the highest overall batting average.

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For Test Group A, the oldest players, players in group 30-34 (0.242) and 35 and older (0.236) had the highest batting averages. In Test Group B, The youngest players, players less than 24 years old (0.224) and the oldest players, players 35 years and older (0.223) had the highest batting average. For Test Group C, 3 out of the 4 age groups nearly had the same batting average, with the 30-34 years old group less than the others (0.208).

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Conclusion and Proofs

Consistently, the youngest and oldest players seemed to have the highest batting average. The youngest players are more athletic and strong and therefore their batting averages were high as well. However overall, the oldest players finished on top. The average amount of time a player spends playing baseball professionally is 5.6 years. If a player is still playing in the major player leagues when he is 35 years old, he has probably been playing for a long time and is a good. These players have not retired yet because they can still help their teams. I know this is true because out of 668 batters only 56 of them are 35 years or older. Older players have more experience and have practiced a long time and this could be why they are better hitters.

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Real World Connection

This project relates to the real world because baseball is known as America’s favorite pastime.

I play travel softball and my own batting average is recorded also. Before doing this project I didn’t realize how batting averages were calculated. The results from this project are helpful since they prove that older players bring a lot to the game because they have been playing the game longer and therefore have more experience than younger players.

To find out the results of this project I had to use a lot of Math skills. I calculated averages and also rounded. I also practiced reading charts and bar graphs.

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