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NCAA Division I Baseball Records
Division I Baseball Records Individual Records .................................................................. 2 Individual Leaders .................................................................. 4 Annual Individual Champions .......................................... 14 Team Records ........................................................................... 22 Team Leaders ............................................................................ 24 Annual Team Champions .................................................... 32 All-Time Winningest Teams ................................................ 38 Collegiate Baseball Division I Final Polls ....................... 42 Baseball America Division I Final Polls ........................... 45 USA Today Baseball Weekly/ESPN/ American Baseball Coaches Association Division I Final Polls ............................................................ 46 National Collegiate Baseball Writers Association Division I Final Polls ............................................................ 48 Statistical Trends ...................................................................... 49 No-Hitters and Perfect Games by Year .......................... 50 2 NCAA BASEBALL DIVISION I RECORDS THROUGH 2011 Official NCAA Division I baseball records began Season Career with the 1957 season and are based on informa- 39—Jason Krizan, Dallas Baptist, 2011 (62 games) 346—Jeff Ledbetter, Florida St., 1979-82 (262 games) tion submitted to the NCAA statistics service by Career RUNS BATTED IN PER GAME institutions -
Sabermetrics: the Past, the Present, and the Future
Sabermetrics: The Past, the Present, and the Future Jim Albert February 12, 2010 Abstract This article provides an overview of sabermetrics, the science of learn- ing about baseball through objective evidence. Statistics and baseball have always had a strong kinship, as many famous players are known by their famous statistical accomplishments such as Joe Dimaggio’s 56-game hitting streak and Ted Williams’ .406 batting average in the 1941 baseball season. We give an overview of how one measures performance in batting, pitching, and fielding. In baseball, the traditional measures are batting av- erage, slugging percentage, and on-base percentage, but modern measures such as OPS (on-base percentage plus slugging percentage) are better in predicting the number of runs a team will score in a game. Pitching is a harder aspect of performance to measure, since traditional measures such as winning percentage and earned run average are confounded by the abilities of the pitcher teammates. Modern measures of pitching such as DIPS (defense independent pitching statistics) are helpful in isolating the contributions of a pitcher that do not involve his teammates. It is also challenging to measure the quality of a player’s fielding ability, since the standard measure of fielding, the fielding percentage, is not helpful in understanding the range of a player in moving towards a batted ball. New measures of fielding have been developed that are useful in measuring a player’s fielding range. Major League Baseball is measuring the game in new ways, and sabermetrics is using this new data to find better mea- sures of player performance. -
Understanding Advanced Baseball Stats: Hitting
Understanding Advanced Baseball Stats: Hitting “Baseball is like church. Many attend few understand.” ~ Leo Durocher Durocher, a 17-year major league vet and Hall of Fame manager, sums up the game of baseball quite brilliantly in the above quote, and it’s pretty ridiculous how much fans really don’t understand about the game of baseball that they watch so much. This holds especially true when you start talking about baseball stats. Sure, most people can tell you what a home run is and that batting average is important, but once you get past the basic stats, the rest is really uncharted territory for most fans. But fear not! This is your crash course in advanced baseball stats, explained in plain English, so that even the most rudimentary of fans can become knowledgeable in the mysterious world of baseball analytics, or sabermetrics as it is called in the industry. Because there are so many different stats that can be covered, I’m just going to touch on the hitting stats in this article and we can save the pitching ones for another piece. So without further ado – baseball stats! The Slash Line The baseball “slash line” typically looks like three different numbers rounded to the thousandth decimal place that are separated by forward slashes (hence the name). We’ll use Mike Trout‘s 2014 slash line as an example; this is what a typical slash line looks like: .287/.377/.561 The first of those numbers represents batting average. While most fans know about this stat, I’ll touch on it briefly just to make sure that I have all of my bases covered (baseball pun intended). -
Iscore Baseball | Training
| Follow us Login Baseball Basketball Football Soccer To view a completed Scorebook (2004 ALCS Game 7), click the image to the right. NOTE: You must have a PDF Viewer to view the sample. Play Description Scorebook Box Picture / Details Typical batter making an out. Strike boxes will be white for strike looking, yellow for foul balls, and red for swinging strikes. Typical batter getting a hit and going on to score Ways for Batter to make an out Scorebook Out Type Additional Comments Scorebook Out Type Additional Comments Box Strikeout Count was full, 3rd out of inning Looking Strikeout Count full, swinging strikeout, 2nd out of inning Swinging Fly Out Fly out to left field, 1st out of inning Ground Out Ground out to shortstop, 1-0 count, 2nd out of inning Unassisted Unassisted ground out to first baseman, ending the inning Ground Out Double Play Batter hit into a 1-6-3 double play (DP1-6-3) Batter hit into a triple play. In this case, a line drive to short stop, he stepped on Triple Play bag at second and threw to first. Line Drive Out Line drive out to shortstop (just shows position number). First out of inning. Infield Fly Rule Infield Fly Rule. Second out of inning. Batter tried for a bunt base hit, but was thrown out by catcher to first base (2- Bunt Out 3). Sacrifice fly to center field. One RBI (blue dot), 2nd out of inning. Three foul Sacrifice Fly balls during at bat - really worked for it. Sacrifice Bunt Sacrifice bunt to advance a runner. -
Baseball/Softball
July2006 ?fe Aatuated ScowS& For Basebatt/Softbatt Quick Keys: Batter keywords: Press this: To perform this menu function: Keyword: Situation: Keyword: Situation: a.Lt*s Balancescoresheet IB Single SAC Sacrificebunt ALT+D Show defense 2B Double SF Sacrifice fly eLt*B Edit plays 3B Triple RBI# # Runs batted in RLt*n Savea gamefile to disk HR Home run DP Hit into doubleplay crnl*n Load a gamefile from disk BB Walk GDP Groundedinto doubleplay alr*I Inning-by-inning summary IBB Intentionalwalk TP Hit into triple play nlr*r Lineupcards HP Hit by pitch PB Reachedon passedball crRL*t List substitutions FC Fielder'schoice WP Reachedon wild pitch alr*o Optionswindow CI Catcher interference E# Reachon error by # ALT+N Gamenotes window BI Batter interference BU,GR Bunt, ground-ruledouble nll*p Playswindow E# Reachedon error by DF Droppedfoul ball ALr*g Quit the program F# Flied out to # + Advanced I base alr*n Rosterwindow P# Poppedup to # -r-r Advanced2 bases CTRL+R Rosterwindow (edit profiles) L# Lined out to # +++ Advanced3 bases a,lr*s Statisticswindow FF# Fouledout to # +T Advancedon throw 4 J-l eLt*:t Turn the scoresheetpage tt- tt Groundedout # to # +E Advanced on effor l+1+1+ .ALr*u Updatestat counts trtrft Out with assists A# Assistto # p4 Sendbox score(to remotedisplay) #UA Unassistedputout O:# Setouts to # Ff, Edit defensivelineup K Struck out B:# Set batter to # F6 Pitchingchange KS Struck out swinging R:#,b Placebatter # on baseb r7 Pinchhitter KL Struck out looking t# Infield fly to # p8 Edit offensivelineup r9 Print the currentwindow alr*n1 Displayquick keyslist Runner keywords: nlr*p2 Displaymenu keys list Keyword: Situation: Keyword: Situation: SB Stolenbase + Adv one base Hit locations: PB Adv on passedball ++ Adv two bases WP Adv on wild pitch +++ Adv threebases Ke1+vord: Description: BK Adv on balk +E Adv on error 1..9 PositionsI thru 9 (p thru rf) CS Caughtstealing +E# Adv on error by # P. -
Name of the Game: Do Statistics Confirm the Labels of Professional Baseball Eras?
NAME OF THE GAME: DO STATISTICS CONFIRM THE LABELS OF PROFESSIONAL BASEBALL ERAS? by Mitchell T. Woltring A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in Leisure and Sport Management Middle Tennessee State University May 2013 Thesis Committee: Dr. Colby Jubenville Dr. Steven Estes ACKNOWLEDGEMENTS I would not be where I am if not for support I have received from many important people. First and foremost, I would like thank my wife, Sarah Woltring, for believing in me and supporting me in an incalculable manner. I would like to thank my parents, Tom and Julie Woltring, for always supporting and encouraging me to make myself a better person. I would be remiss to not personally thank Dr. Colby Jubenville and the entire Department at Middle Tennessee State University. Without Dr. Jubenville convincing me that MTSU was the place where I needed to come in order to thrive, I would not be in the position I am now. Furthermore, thank you to Dr. Elroy Sullivan for helping me run and understand the statistical analyses. Without your help I would not have been able to undertake the study at hand. Last, but certainly not least, thank you to all my family and friends, which are far too many to name. You have all helped shape me into the person I am and have played an integral role in my life. ii ABSTRACT A game defined and measured by hitting and pitching performances, baseball exists as the most statistical of all sports (Albert, 2003, p. -
Changing Compensation in MLB
Beyond Moneyball: Changing Compensation in MLB By Joshua Congdon-Hohman and Jonathan A. Lanning May 2017 COLLEGE OF THE HOLY CROSS, DEPARTMENT OF ECONOMICS FACULTY RESEARCH SERIES, PAPER NO. 17-02* Department of Economics College of the Holy Cross Box 45A Worcester, Massachusetts 01610 (508) 793-3362 (phone) (508) 793-3708 (fax) https://www.holycross.edu/academics/programs/economics-and-accounting *All papers in the Holy Cross Working Paper Series should be considered draft versions subject to future revision. Comments and suggestions are welcome. Beyond Moneyball: Changing Compensation in MLB By Joshua Congdon-Hohman† College of the Holy Cross and Jonathan A. Lanning†† College of the Holy Cross May 2017 Abstract This study examines the changes in player compensation in Major League Baseball during the last three decades. Specifically, we examine the extent to which recently documented changes in players’ compensation structure based on certain types of productivity fits in with the longer term trends in compensation, and identify the value of specific output activities in different time periods. We examine free agent contracts in three-year periods across three decades and find changes to which players’ performance measures are significantly rewarded in free agency. We find evidence that the compensation strategies of baseball teams increased the rewards to “power” statistics like home runs and doubles in the 1990s when compared to a model that focused on successfully reaching base with a batted ball without a significant regard for the number of bases reached. Similarly, we confirm and expand upon the increased financial return to bases-on-balls in the late 2000s as found in previous research. -
Stolen Base Physics David Kagan
Stolen Base Physics David Kagan Citation: Phys. Teach. 51, 269 (2013); doi: 10.1119/1.4801351 View online: http://dx.doi.org/10.1119/1.4801351 View Table of Contents: http://tpt.aapt.org/resource/1/PHTEAH/v51/i5 Published by the American Association of Physics Teachers Additional information on Phys. Teach. Journal Homepage: http://tpt.aapt.org/ Journal Information: http://tpt.aapt.org/about/about_the_journal Top downloads: http://tpt.aapt.org/most_downloaded Information for Authors: http://www.aapt.org/publications/tptauthors.cfm Downloaded 11 Apr 2013 to 128.174.13.178. Redistribution subject to AAPT license or copyright; see http://tpt.aapt.org/authors/copyright_permission Stolen Base Physics David Kagan, California State University, Chico, Chico, CA ew plays in baseball are as consistently close and excit- ing as the stolen base.1 While there are several studies 2-4 v of sprinting, the art of base stealing is much more slope = a Fnuanced. This article describes the motion of the base- stealing runner using a very basic kinematic model. The mod- - vf + el will be compared to some data from a Major League game. Velocity The predictions of the model show consistency with the skills slope = a needed for effective base stealing. The basic kinematic model Let’s just consider a steal of second base as opposed to Time third or home. The goal of the runner is to minimize the time required to get there. The basic kinematic model breaks the Fig. 1. The velocity-time graph for the kinematic model. It is the shape of the curve that describes the kinematic model, so units total distance between the bases (D = 90.0 ft) into four parts. -
Salary Correlations with Batting Performance
Salary correlations with batting performance By: Jaime Craig, Avery Heilbron, Kasey Kirschner, Luke Rector, Will Kunin Introduction Many teams pay very high prices to acquire the players needed to make that team the best it can be. While it often seems that high budget teams like the New York Yankees are often very successful, is the high price tag worth the improvement in performance? We compared many statistics including batting average, on base percentage, slugging, on base plus slugging, home runs, strike outs, stolen bases, runs created, and BABIP (batting average for balls in play) to salaries. We predicted that higher salaries will correlate to better batting performances. We also divided players into three groups by salary range, with the low salary range going up to $1 million per year, the mid-range salaries from $1 million to $10 million per year, and the high salaries greater than $10 million per year. We expected a stronger correlation between batting performance and salaries for players in the higher salary range than the correlation in the lower salary ranges. Low Salary Below $1 million In figure 1 is a correlation plot between salary and batting statistics. This correlation plot is for players that are making below $1 million. We see in all of the plots that there is not a significant correlation between salary and batting statistics. It is , however, evident that players earning the lowest salaries show the lowest correlations. The overall trend for low salary players--which would be expected--is a negative correlation between salary and batting performance. This negative correlation is likely a result of players getting paid according to their specific performance, or the data are reflecting underpaid rookies who have not bloomed in the major leagues yet. -
Guide to Softball Rules and Basics
Guide to Softball Rules and Basics History Softball was created by George Hancock in Chicago in 1887. The game originated as an indoor variation of baseball and was eventually converted to an outdoor game. The popularity of softball has grown considerably, both at the recreational and competitive levels. In fact, not only is women’s fast pitch softball a popular high school and college sport, it was recognized as an Olympic sport in 1996. Object of the Game To score more runs than the opposing team. The team with the most runs at the end of the game wins. Offense & Defense The primary objective of the offense is to score runs and avoid outs. The primary objective of the defense is to prevent runs and create outs. Offensive strategy A run is scored every time a base runner touches all four bases, in the sequence of 1st, 2nd, 3rd, and home. To score a run, a batter must hit the ball into play and then run to circle the bases, counterclockwise. On offense, each time a player is at-bat, she attempts to get on base via hit or walk. A hit occurs when she hits the ball into the field of play and reaches 1st base before the defense throws the ball to the base, or gets an extra base (2nd, 3rd, or home) before being tagged out. A walk occurs when the pitcher throws four balls. It is rare that a hitter can round all the bases during her own at-bat; therefore, her strategy is often to get “on base” and advance during the next at-bat. -
The Stolen Base Is an Integral Part of the Game of Baseball
THE STOLEN BASE by Lindsay S. Parr A thesis submitted to the Faculty and the Board of Trustees of the Colorado School of Mines in partial fulfillment of the requirements for the degree of Master of Science (Applied Mathematics and Statistics). Golden, Colorado Date Signed: Lindsay S. Parr Signed: Dr. William C. Navidi Thesis Advisor Golden, Colorado Date Signed: Dr. Willy A. Hereman Professor and Head Department of Applied Mathematics and Statistics ii ABSTRACT The stolen base is an integral part of the game of baseball. As it is frequent that a player is in a situation where he could attempt to steal a base, it is important to determine when he should try to steal in order to obtain more wins per season for his team. I used a sample of games during the 2012 and 2013 Major League Baseball seasons to see how often players stole in given scenarios based on number of outs, pickoff attempts, runs until the end of the inning, left or right-handed batter/pitcher, run differential, and inning. New stolen base strategies were created using the percentage of opportunities attempted and the percentage of successful attempts for each scenario in the sample, a formula introduced by Bill James for batter/pitcher match-up, and run expectancy. After writing a program in R to simulate baseball games with the ability to change the stolen base strategy, I compared new strategies to the current strategy used to see if they would increase each Major League Baseball team’s average number of wins per season. I found that when using a strategy where a team steals 80% of the time it increases its run expectancy and 20% of the time that it does not, the average number of wins per season increases for a vast majority of teams over using the current strategy. -
Pitching Safety & Performance Management
PITCHING SAFETY & PERFORMANCE MANAGEMENT o To accurately, and comprehensively, track safety-driven pitching restrictions: • Athletes pitch year-round across multiple teams • No centralized mechanism in THE NEED place for calculating & reporting mandated/recommended rest o To provide baseball organizations with a simple-to-use platform that allows real-time tracking of pitch loads and performance to enhance player safety and improve success THE SOLUTION THE SOLUTION: ChangeUp o Comprehensive player-centric tracking of an athlete’s pitch load across unlimited teams and seasons o Automated reporting and compliance tracking, with Preconfigured support for: o Little League® o USA Baseball/MLB Pitch Smart o National Federation of High School Associations (NFHS) o Powerful analytics focused on safety, durability, effectiveness, and other key performance metrics o Real-time, systematic reconciliation with opposing teams o Detailed historical player profiles enabling: o Current coaches to best deploy their athletes o Prospective coaches to evaluate recruits o Medical professionals to better understand athletes’ performance thresholds and injury trends o Governing organizations to use real data to evaluate existing and new regulations furthering the goal of player safety o Official Pitch Smart certified application THE SOLUTION: Player-Centric Tracking o The only Player-Centric solution in the marketplace o All pitching, regardless of team represented, tracked at the player level o For multi-team athletes, availability is properly reflected across