Introduction
Baseball statistics have evolved significantly over time, transitioning from basic metrics like batting average and earned run average (ERA) to advanced sabermetrics that offer deeper insights into player performance. In the early days of the sport, stats were simple and largely focused on outcomes like hits, runs, and strikeouts. However, with the advent of technologies like video analysis and data tracking systems, modern statistics now include sophisticated measures such as on-base percentage (OBP), slugging percentage (SLG), and advanced metrics like WAR (Wins Above Replacement) and OPS (On-base Plus Slugging). These new statistics help teams, analysts, and fans evaluate players' contributions more holistically, considering factors such as defense, base running, and the context of each at-bat. This shift towards data-driven decision-making has revolutionized how baseball is played, coached, and understood.
Task
In this WebQuest students will research the definitions of various baseball terms, such as batting average, ERA, and slugging percentage, as well as more advanced terms like WAR and OPS, to better comprehend how the game is played and analyzed. Second, they will create a fantasy baseball team and record their statistics. Finally, looking at the evolution of baseballs and using statistics to see if the composition of the baseball impacts hits involves investigating how the design and materials of the baseball have changed over time, and analyzing statistical data to determine whether these changes have influenced offensive performance.
Process
1. Use the Glossary of Baseball at https://en.wikipedia.org/wiki/Glossary_of_baseball_terms to define the following baseball terms:
- Hit (H)
- At-Bat (AB)
- Walk (BB)
- Single (1B)
- Double (2B)
- Batting Average (AVG)
- On-Base Percentage (OBP)
- Slugging Percentage (SLG)
- Perfect Game
- No-Hitter
2. Visit http://www.mlb.com/stats and create an 8 player (no pitcher) fantasy baseball team.
- Create a table with the following statistics for each player: AB, H, 2B, 3B, HR, AVG, SLG.
- Show the calculation to determine the AVG for any 4 players
- Show the calculation to determine the SLG for any 4 players
3. Home run mania hit the US in 1998 when both Mark McGwire and Sammy Sosa broke the major league home run record. Are baseball players getting better at hitting home runs, or is something else going on? One claim is that the way baseballs are made has changed over the years and that the newer balls travel farther than the old ones. Some people say modern baseballs are "juiced". The data provided shows the mean number of home runs hit per MLB game from 1960 to 2000. Do these data provide convincing evidence that baseball have flown farther over time?
a. Use http://www.stapplet.com to make a scatterplot of year versus the average number of home runs hit per game.
b. Describe the pattern you see in the plot
c. Calculate the correlation coefficient (r)
d. Write the equation of the line of best fit in the form y = a + bx.
e. Using the above calculations to support your argument, do you think that baseballs are "juiced"? Explain.
Evaluation
Task #1
| Points | 4 | 3 | 2 | 1 |
| all 12 terms are defined | 8-11 terms are correctly defined | 5-7 terms are correctly defined | 1-4 terms are correctly defined |
Task #2
| Points | 4 | 3 | 2 | 1 |
| Team | all stats are recorded for all 8 positions | ll stats are recorded for 6 or 7positions | ll stats are recorded for 4 or 5 positions | ll stats are recorded for 2 or 3 positions |
| Batting Average | AVG is correctly calculated for all 4 players | AVG is correctly calculated for 3 players | AVG is correctly calculated for 2 players | AVG is correctly calculated for 1 player |
Task #3
| Points | 4 | 3 | 2 | 1 |
| Student provides exceptional evidence to support their argument | Student provides adequate evidence to support their argument | Student provides proficient evidence to support their argument | Student provides marginal evidence to support their argument |