Presentation is loading. Please wait.

Presentation is loading. Please wait.

Baserunner Scoring Percentage (BSP): an analysis using play-by- play data William Knapp and Dr. Jason A. Osborne, Dept. of Mathematics and Dept. of Statistics,

Published byStephanie Hunt Modified over 9 years ago

Similar presentations

Presentation on theme: "Baserunner Scoring Percentage (BSP): an analysis using play-by- play data William Knapp and Dr. Jason A. Osborne, Dept. of Mathematics and Dept. of Statistics,"— Presentation transcript:

1 Baserunner Scoring Percentage (BSP): an analysis using play-by- play data William Knapp and Dr. Jason A. Osborne, Dept. of Mathematics and Dept. of Statistics, N.C. State University

2 Introduction What is BSP? Which teams have the best BSP? Effect of sacrifice bunts and stolen bases BSP as a predictor for runs scored and wins Methodology Linear and logistic regression Correlation

3 Data Acquisition Web-scraping and parsing with R and Java R functions: readLines() and regexp() Java: sort into arrays and change certain variables to binary

4 Analysis: Sacrifice and SB effects OutsBuntAttemptSBattemptEst. ProbStd Error 0No 0.38740.000910 0NoYes0.37160.003404 0YesNo0.51920.002538 0Yes 0.58330.012930 1No 0.24880.000744 1NoYes0.26610.003301 1YesNo0.35540.005538 1Yes 0.51950.040670 2No 0.14330.000649 2NoYes0.16690.003238 2YesNo-- 2Yes --

5 Analysis: MLR on Runs and Wins Variables# of Predictorsrsqrpgrsqwlpct obp1.8202.2821 bsp1.7335.1987 hr1.4982.1866 lob1.2227.0984 obp bsp2.9147.2922 obp hr2.9005.3171 obp lob2.8846.2913 bsp hr2.8732.2695 bsp lob2.8063.2431 lob hr2.6322.2487 obp bsp hr lob4.9776.3235

6 BSP vs Winning Percentage Scatter of all 30 teams over all 16 years Individual teams to show trends Houston needs some work

Download ppt "Baserunner Scoring Percentage (BSP): an analysis using play-by- play data William Knapp and Dr. Jason A. Osborne, Dept. of Mathematics and Dept. of Statistics,"

Similar presentations

Methodology- Framework Homeruns Batting Average Base on Balls Runs Batted In Strikeouts Errors Double Plays Fielding % Salaries Performance.

Methodology- Framework Homeruns Batting Average Base on Balls Runs Batted In Strikeouts Errors Double Plays Fielding % Salaries Performance.
Bunting and Sacrificing in MLB Lauren McNulty and Drew Jack.

Bunting and Sacrificing in MLB Lauren McNulty and Drew Jack.
© McGraw-Hill Higher Education. All Rights Reserved. Chapter 2F Statistical Tools in Evaluation.

© McGraw-Hill Higher Education. All Rights Reserved. Chapter 2F Statistical Tools in Evaluation.
Correlational Research 1. Spare the rod and spoil the child 2. Idle hands are the devil’s workplace 3. The early bird catches the worm 4. You can’t teach.

Correlational Research 1. Spare the rod and spoil the child 2. Idle hands are the devil’s workplace 3. The early bird catches the worm 4. You can’t teach.
LINEAR REGRESSION: What it Is and How it Works Overview What is Bivariate Linear Regression? The Regression Equation How It’s Based on r.

LINEAR REGRESSION: What it Is and How it Works Overview What is Bivariate Linear Regression? The Regression Equation How It’s Based on r.
LINEAR REGRESSION: What it Is and How it Works. Overview What is Bivariate Linear Regression? The Regression Equation How It’s Based on r.

LINEAR REGRESSION: What it Is and How it Works. Overview What is Bivariate Linear Regression? The Regression Equation How It’s Based on r.
Chapter 8 Logistic Regression 1. Introduction Logistic regression extends the ideas of linear regression to the situation where the dependent variable,

Chapter 8 Logistic Regression 1. Introduction Logistic regression extends the ideas of linear regression to the situation where the dependent variable,
Who Wins The Ironman? Best Swimmer, Cyclist, or Runner A Project Demonstration by Dr. Moffit.

Who Wins The Ironman? Best Swimmer, Cyclist, or Runner A Project Demonstration by Dr. Moffit.
Statistics 350 Lecture 16. Today Last Day: Introduction to Multiple Linear Regression Model Today: More Chapter 6.

Statistics 350 Lecture 16. Today Last Day: Introduction to Multiple Linear Regression Model Today: More Chapter 6.
Statistics. Overview 1. Confidence interval for the mean 2. Comparing means of 2 sampled populations (or treatments): t-test 3. Determining the strength.

Statistics. Overview 1. Confidence interval for the mean 2. Comparing means of 2 sampled populations (or treatments): t-test 3. Determining the strength.
STAT 104: Section 2 4 Oct, 2007 TF: Daniel Moon. TF Daniel Moon G2 (A.M. in Statistics Dept) Office hour:

STAT 104: Section 2 4 Oct, 2007 TF: Daniel Moon. TF Daniel Moon G2 (A.M. in Statistics Dept) Office hour:
1 BA 275 Quantitative Business Methods Simple Linear Regression Introduction Case Study: Housing Prices Agenda.

1 BA 275 Quantitative Business Methods Simple Linear Regression Introduction Case Study: Housing Prices Agenda.
Reliability and Linking of Assessments. Figure 1 Differences Between Percentages Proficient or Above on State Assessments and on NAEP: Grade 8 Mathematics,

Reliability and Linking of Assessments. Figure 1 Differences Between Percentages Proficient or Above on State Assessments and on NAEP: Grade 8 Mathematics,
Linear Regression MARE 250 Dr. Jason Turner.

Linear Regression MARE 250 Dr. Jason Turner.
MARE 250 Dr. Jason Turner Correlation & Linear Regression.

MARE 250 Dr. Jason Turner Correlation & Linear Regression.
Introduction to Linear and Logistic Regression. Basic Ideas Linear Transformation Finding the Regression Line Minimize sum of the quadratic residuals.

Introduction to Linear and Logistic Regression. Basic Ideas Linear Transformation Finding the Regression Line Minimize sum of the quadratic residuals.
CORRELATIONAL RESEARCH I Lawrence R. Gordon Psychology Research Methods I.

CORRELATIONAL RESEARCH I Lawrence R. Gordon Psychology Research Methods I.
Correlation 1. Correlation - degree to which variables are associated or covary. (Changes in the value of one tends to be associated with changes in the.

Correlation 1. Correlation - degree to which variables are associated or covary. (Changes in the value of one tends to be associated with changes in the.
1 Chapter 17: Introduction to Regression. 2 Introduction to Linear Regression The Pearson correlation measures the degree to which a set of data points.

1 Chapter 17: Introduction to Regression. 2 Introduction to Linear Regression The Pearson correlation measures the degree to which a set of data points.
Correlational Research Strategy. Recall 5 basic Research Strategies Experimental Nonexperimental Quasi-experimental Correlational Descriptive.

Correlational Research Strategy. Recall 5 basic Research Strategies Experimental Nonexperimental Quasi-experimental Correlational Descriptive.

Similar presentations

Ads by Google