Zachary Kellar Dr Brandon Koch Dr Anna Panorska University of Nevada Reno Department of Mathematics and Statistics School of Community Health Sciences Baseball Introduction American sport between two teams where one team pitches a baseball to an opponent who attempts to hit the bas ID: 932738
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The Effect of Launch Angle and Exit Velocity on Hit Probability in Major League Baseball
Zachary Kellar | Dr. Brandon Koch* | Dr. Anna
Panorska
University of Nevada, Reno | Department of Mathematics and Statistics
*School of Community Health Sciences
Slide2Baseball Introduction
American sport between two teams where one team pitches a baseball to an opponent, who attempts to hit the baseball into the field of play
Objective of baseball is to score more runs (points) than the opponent
This is accomplished by recording “base hits”For this research, we understand “base hits” as the desired outcome, or successOur objective is to maximize the probability of successful outcomes
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Slide3Motivation for Study
Major League Baseball is very interested in statistics and quantification of the game
Statcast
camera system implemented in 2015Simple tracking of advanced baseball statisticsMajor League Baseball is interested in the influence of launch angle and exit velocity on the probability of success
Exit Velocity
Launch Angle
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Slide4Impact of Research
Major League Baseball
Change in game strategy
Alterations in how teams hire, scout, organize, and train players, coaches, and general staffPersonal GrowthProfessional development towards a career in sports statisticsSeeking publication of completed work to present to Major League teams, or statistic journals
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Slide5Scientific Question
What is the relationship between launch angle and exit velocity with the probability of success?
Our Goal:
Find statistical association between launch angle and/or exit velocity, and probability of successBuild a model that describes such a relationship
Discover what factors beyond launch angle and exit velocity that drive the probability of a successful outcome
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Slide6The Data
New camera-based system introduced in 2015 allows tracking of new variables for each thrown pitch of a season, for every team
Extension of 100+ year old database
New variables include launch angle, exit velocity, spray angleStatcast Database (2017)735,817 observations of 79 variables
One observation represents a “pitch”, or possibility of a successSubsetting the Data for our ResearchOnly consider pitches (observations) where ball was hit
129,365 observations composing analysis data set with variables of launch angle, exit velocity, and success/failure6
Slide7Exploratory Analysis: Launch Angle Distribution
Examine the distribution of all observed launch angles in 2017
We observe the launch angle is mostly symmetrically distributed
Two frequent observations at -20
⁰ and 70⁰
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Slide8Probability of Success as a Function of Launch Angle
Data was divided into 100 categories of equal size from smallest to largest launch angle
Percentage of successful outcomes recorded for all
100 intervals was computedPercentiles of launch angle were used for categories to have equal sample sizes for success rate computationWe can conclude that the best range of launch angles is between 11.4
⁰ and 18
⁰
8
-16
⁰
3.9
⁰
18
⁰
33⁰
Slide9Exploratory Analysis: Exit Velocity Distribution
Examine the distribution of all observed exit velocities in 2017
We observe that exit velocity is mostly skewed left
Frequent observations at 78 and 84 mph
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Slide10Probability of Success as a Function of Exit Velocity
Exploratory distributions were made for exit velocity in the same manner
Percentiles of exit velocity were used for categories to have equal sample sizes for success rate computation
We observe that larger velocities tend to be more successful
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76 mph
84 mph
92.3 mph
99.5 mph
Slide11Preliminary Conclusions
Launch Angle Relationship with Probability of Success
Probability of Success increases as launch angle rises to 11.5
⁰, declines thereafterBest interval of launch angles is (9.8
⁰-15.1⁰), where success rate is above 0.7Exit Velocity Relationship with Probability of Success
Upon rising to approximately 90 mph, probability of success exhibits linear growth Harder hit baseballs usually lead to more successful outcomes
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Slide12Probability of Success as a Function of Both Launch Angle and Exit Velocity
Relationship between success rate, exit velocity, and launch angle is clear
Use both variables to predict success rate, using new bins containing ranges of 10 degrees, and 10 mph respectively
We observe that there is a combination of launch angle and exit velocity that produces very high probability of success
Probability of Success Versus Launch Angle and Exit Velocity
Exit Velocity
Launch Angle
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Slide13Further Database Reduction
Extreme probabilities are observed around edges of graph
Examine sample sizes as a z-axis, as opposed to success rate
Subset data to contain launch angle greater than or equal to 60⁰, exit velocity greater than or equal to 20 mph
Sample Sizes of Created Bins
Exit Velocity
Launch Angle
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Slide14General Linear Model
Categorize launch angle into 10 intervals, and exit velocity into 4 intervals
Response variable is hit (success) indicator
Included main effects and interactions in a logistic regression model: log odds of success = a * velocity + b * angle + c * velocity * angle
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Slide15Model Statistics
Training Prediction Accuracy: 79%
Training Error: 21%
Training: prediction and model fitting is performed on the same data setNote: this accuracy was attained using only two (discretized) variables in the model
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Slide16Discussion and Conclusions
The most successful estimated combination is a launch angle of 15
⁰
, and exit velocity of approximately 81 mphYields success rate of 0.894Probability of success depends less on launch angle for higher exit velocitiesSpecific launch angles between approximately 8
⁰-15
⁰ yield higher success rate estimatesBaseballs hit at very low or very high launch angles have very low chances of success
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Slide17Future Directions
Explore probability of success with more variables in the model
Spray angle, number of outs
Create and compare models with those created from other seasons of StatcastObserve how model relates to older databases that do not possess same scope of information
Compare to early 1900’s databasesInvestigate future seasons of baseball that may be influenced by intentional change of launch angleCurrently not controlling variables that would confound the relationship between exit velocity, launch angle, and probability of successAccounted for in future research as more variables are added
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Slide18Thank you
Slide19References
“Free Image on
Pixabay
- Baseball, Field, Sports, Stadium.” Baseball Field Sports - Free Vector Graphic on Pixabay, pixabay.com/illustrations/baseball-field-sports-stadium-park-3778774/.“Statcast Search CSV Documentation.” Baseballsavant.com, baseballsavant.mlb.com/csv-docs.
Sheinin, Dave. “Why MLB Hitters Are Suddenly Obsessed with Launch Angles.” The Washington Post, WP Company, 1 June 2017, www.washingtonpost.com/graphics/sports/mlb-launch-angles- story/?utm_term=.e884252bd08f.
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