Related Experiment Video
Updated: Jun 26, 2025

In Vivo Protocol of Controlled Subconcussive Head Impacts for the Validation of Field Study Data
Published on: April 18, 2019
Classifying batted ball outcomes from Division I collegiate baseball players.
Z Farrel1, P C Jones1, C A Lowe2
1Athletics Department, University of Louisville, Louisville, KY, USA.
Modern baseball analytics show player height, exit speed, launch angle, and batted ball distance significantly impact hit likelihood. Hang time negatively affects outcomes, challenging traditional beliefs about in-game situations.
Area of Science:
- Sports Science
- Baseball Analytics
- Performance Optimization
Background:
- Anecdotal beliefs in baseball performance often lack empirical support.
- Modern technology allows for objective measurement of various performance factors.
- Understanding batted ball outcomes is crucial for evaluating player performance.
Purpose of the Study:
- To classify batted ball outcomes using objective data.
- To examine the influence of anthropometry, in-game situation, and technique-based variables on hit likelihood.
- To challenge and verify traditional beliefs regarding baseball performance factors.
Main Methods:
- Utilized data from 1,922 batted ball outcomes from 230 players in 2021 college baseball.
- Independent variables included anthropometry (height, weight), in-game situation (batter side, count, pitch type), and technique-based metrics (exit speed, launch angle, batted ball distance, hang time) measured by TrackMan radar.
- Binary logistic regression analysis was performed to determine the significance of independent variables on batted ball outcomes.
Main Results:
- The model, incorporating all independent variables, demonstrated a good fit and correctly classified nearly 75% of batted ball outcomes.
- Significant positive associations with hit outcomes were found for player height, exit speed (ExSp), launch angle (LA), and batted ball distance (BBD).
- Hang time (HT) showed a significant negative association with batted ball outcomes. In-game situation variables were non-significant, and anthropometry's contribution was modest.
Conclusions:
- Technique-based variables measured by TrackMan radar (ExSp, LA, BBD, HT) are significant predictors of batted ball outcomes.
- Player height has a modest but significant impact, while in-game situational factors have a non-significant impact, contradicting anecdotal beliefs.
- Objective data analysis provides a more accurate understanding of baseball performance than traditional assumptions.
Related Concept Videos
Relative Frequency Distribution
Stratified Sampling Method
To choose a stratified sample, divide the population into groups called strata and then take a...
Quantifying and Rejecting Outliers: The Grubbs Test
Percentage Frequency Distribution
The process of making a percentage frequency distribution involves the following few steps: note the total number of observations;...
How Data are Classified: Categorical Data
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
Binomial Probability Distribution
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...

