BSBWSBLTEAM9------ 85A 17 Report Created TUE 27 JUL 2021 22:21 Page 1/1

Total Page:16

File Type:pdf, Size:1020Kb

BSBWSBLTEAM9------ 85A 17 Report Created TUE 27 JUL 2021 22:21 Page 1/1 Baseball/Softball 野球・ソフトボール / Baseball/Softball Softball ソフトボール / Softball Best Offensive Players 野⼿成績 / Meilleurs joueurs offensifs As of TUE 27 JUL 2021 at 22:21 After 17 Games Batting Average Leaders Slugging Percentage Leaders (Minimum 2.7 Plate appearances per game played by the Team) Rank Player Team GP PA AB H AVG Rank Player Team GP PA AB TB SLG% 1 SALLING Jenn CAN 6 20 14 8 .571 1 SALLING Jenn CAN 6 20 14 13 .929 2 Mc CLENEY Haylie USA 6 21 17 9 .529 2 FUJITA Yamato JPN 6 19 18 16 .889 3 FUJITA Yamato JPN 6 19 18 7 .389 3 YAMAMOTO Yu JPN 6 19 18 12 .667 4 YAMAMOTO Yu JPN 6 19 18 6 .333 4 Mc CLENEY Haylie USA 6 21 17 11 .647 5 TSITSIKRONIS Taylah AUS 5 15 9 3 .333 5 URTEZ Anissa MEX 6 21 20 12 .600 6 GODFREY Leigh AUS 5 18 15 5 .333 6 WALL Jade AUS 5 14 11 5 .455 7 URTEZ Anissa MEX 6 21 20 6 .300 7 ROMERO Sydney MEX 6 21 18 8 .444 8 HAYWARD Victoria CAN 6 22 20 6 .300 8 TSITSIKRONIS Taylah AUS 5 15 9 4 .444 9 GONZALES Chelsea MEX 6 19 19 5 .263 9 BROOKSHIRE Suzannah MEX 6 19 16 7 .438 10 BROOKSHIRE Suzannah MEX 6 19 16 4 .250 10 HAYWARD Victoria CAN 6 22 20 8 .400 Home Run Leaders Runs Batted In Leaders Rank Player Team HR Rank Player Team RBI 1 FUJITA Yamato JPN 3 1 FUJITA Yamato JPN 7 2 YAMAMOTO Yu JPN 2 2 SALLING Jenn CAN 5 3 URTEZ Anissa MEX 2 3 YAMAMOTO Yu JPN 5 4 GILBERT Jen CAN 1 4 WALL Jade AUS 4 5 WALL Jade AUS 1 5 URTEZ Anissa MEX 4 6 SALLING Jenn CAN 1 6 ENTZMINGER Emma CAN 3 7 CERVANTES Brittany MEX 1 7 FRANKLIN Larissa CAN 3 7 NAITO Minori JPN 1 8 CHIDESTER Amanda USA 3 7 STEWART Kelsey USA 1 9 AGUILAR Ali USA 2 10 ROMERO Sydney MEX 1 9 ATSUMI Mana JPN 2 Runs Scored Leaders Stolen Base Leaders Rank Player Team R Rank Player Team SB 1 HAYWARD Victoria CAN 7 1 POLIDORI Erika CAN 2 2 NAITO Minori JPN 4 There are 10 players tied with 1 3 Mc CLENEY Haylie USA 4 4 FUJITA Yamato JPN 4 4 YAMAMOTO Yu JPN 4 6 SALLING Jenn CAN 3 7 BROOKSHIRE Suzannah MEX 3 8 HARSHMAN Kelsey CAN 3 8 ROMERO Sydney MEX 3 10 LYE Joey CAN 2 Note: Determination of rankings: Batting average: Batting average (descending), Slugging percentage (descending), At bats (descending) Slugging percentage: Slugging percentage (descending), At bats (descending) Home runs: Home runs (descending), At bats (ascending) Runs batted in: Runs batted in (descending), At bats (ascending) Runs scored: Runs scored (descending), At bats (ascending) Stolen bases: Stolen bases (descending), Stolen base percentage (descending) Legend: AB At bats AVG Batting average GP Games played H Hits HR Home runs PA Plate appearances R Runs RBI Runs batted in SB Stolen bases SLG% Slugging percentage TB Total bases on hits BSBWSBLTEAM9----------------------_85A 17 Report Created TUE 27 JUL 2021 22:21 Page 1/1.
Recommended publications
  • 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
    [Show full text]
  • League Leaders Batting Top 10 Batter Team Avg G Ab R H
    LEAGUE LEADERS BATTING TOP 10 BATTER TEAM AVG G AB R H HR RBI BB SO *Schwartz, JT LAC .378 52 196 40 74 1 35 25 23 *Bottcher, Matt EC .367 57 229 44 84 1 40 32 30 Berkey, Evan ROC .358 57 229 39 82 2 23 24 26 *Thompson, Jake LAK .355 50 186 34 66 2 41 36 15 Michaels, Logan MAD .354 48 192 29 68 0 27 16 23 Frank, Adam WIS .348 56 224 49 78 10 42 17 27 Bigbie, Justice MAD .346 68 283 53 98 12 70 28 58 *Myers, Daryl LAK .341 48 167 36 57 1 28 36 44 *Blazevic, Austin MAD .339 49 186 19 63 4 36 17 26 Dunham, Jake WRP .332 56 190 27 63 8 52 26 25 LEAGUE LEADERS PITCHING TOPTOP 10 PITCHER TEAM G W-L ERA IP H Hoffman, Andrew TVC 12 8-0 1.08 58.1 32 Portela, Polo WIL 10 8-0 1.23 58.1 43 *Koenig, Trevor STC 10 7-1 1.35 60.0 35 *Stroh, Gareth WRP 10 7-1 1.61 61.2 36 Hemmerling, Nathan WRP 12 7-2 2.28 59.1 47 Jones, Kyle TVC 13 6-2 2.73 62.2 68 *Osterberg, Matt WRP 11 6-2 3.10 58.0 61 Husson, Aaron KMO 19 7-1 3.16 68.1 51 *Newberg, Brett MAN 12 5-2 3.22 67.0 67 Traxel, Blaine KMO 18 1-3 3.47 57.0 61 HOME RUNS WINS BATTER TEAM HR PITCHER TEAM W *Holgate, Ryan LAC 13 Portela, Polo WIL 8 Bigbie, Justice MAD 12 Hoffman, Andrew TVC 8 *Elvir, Josh MAN 11 Hemmerling, Nathan WRP 7 Reeves, TJ WIS 10 *Stroh, Gareth WRP 7 Frank, Adam WIS 10 *Koenig, Trevor STC 7 RBI SAVES BATTER TEAM RBI PITCHER TEAM SV Bigbie, Justice MAD 70 Freilich, Jared LAC 13 Morrow, Andrew TVC 58 Denlinger, Theo MAD 12 *Holgate, Ryan LAC 53 Taylor, Keon ROC 12 Dunham, Jake WRP 52 Bonner, Brayden WRP 11 Delano, Garett STC 51 Haass, Joey KMO 10 STOLEN BASES STRIKEOUTS BATTER TEAM SB PITCHER
    [Show full text]
  • 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.
    [Show full text]
  • The Psychology of Baseball: How the Mental Game Impacts the Physical Game
    University of Connecticut OpenCommons@UConn Honors Scholar Theses Honors Scholar Program Spring 4-26-2018 The syP chology of Baseball: How the Mental Game Impacts the Physical Game Kiera Dalmass [email protected] Follow this and additional works at: https://opencommons.uconn.edu/srhonors_theses Part of the Applied Statistics Commons, Comparative Psychology Commons, and the Design of Experiments and Sample Surveys Commons Recommended Citation Dalmass, Kiera, "The sP ychology of Baseball: How the Mental Game Impacts the Physical Game" (2018). Honors Scholar Theses. 578. https://opencommons.uconn.edu/srhonors_theses/578 Student Researcher: Kiera Dalmass; PI: Haim Bar, Ph.D. Protocol Number: H17-238 The Psychology of Baseball: How the Mental Game Impacts the Physical Game Kiera Dalmass PI: Haim Bar, PhD. University of Connecticut Department of Statistics 1 Student Researcher: Kiera Dalmass; PI: Haim Bar, Ph.D. Protocol Number: H17-238 TABLE OF CONTENTS ACKNOWLEDGEMENTS 3 ABSTRACT 4 LITERATURE REVIEW 5 RESEARCH QUESTIONS AND HYPOTHESIS 14 METHODS 16 PARTICIPANTS 17 MATERIALS 18 PROCEDURE 21 RESULTS 24 STATISTICAL RESULTS SURVEY RESULTS DISCUSSION 58 LIMITATIONS OF STUDY 59 FINDINGS AND FUTURE OF THE STUDY 60 REFERENCES 64 APPENDIX A: DEFINITIONS AND FORMULAS FOR VARIABLES 66 APPENDIX B: SURVEYS 68 APPENDIX C: INSTITUTIONAL REVIEW BOARD FORMS 75 2 Student Researcher: Kiera Dalmass; PI: Haim Bar, Ph.D. Protocol Number: H17-238 ACKNOWLEDGEMENTS I would like to thank my family for always being my support system and helping me achieve my dreams. I would like to give a special thank you to Professor Haim Bar, my research mentor. Without him, none of this project would have been possible.
    [Show full text]
  • 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).
    [Show full text]
  • Shut out Free Download
    SHUT OUT FREE DOWNLOAD Kody Keplinger | 272 pages | 06 Nov 2012 | Little, Brown & Company | 9780316175555 | English | New York, United States Shutouts in baseball A pitcher must face at least one batter before being removed to be considered the starting pitcher and get recorded with the game started, whether the batter faced reached base or was put out in any way. If two or more pitchers Shut Out to complete this act, no pitcher will be awarded a shutout, although the team itself can be said to have "shut out" the opposing team. Shut Out Expos failed to score as well, and the game was forced into extra innings. Take the quiz Forms of Government Quiz Name that government! If one team did not allow a goal, then that team's "details of Shut Out conceded" page would appear blank, leaving a clean sheet. For games that were shortened due to weather, darkness, Shut Out other uncontrollable scenarios, a shutout can still be Shut Out by a single pitcher, but under Major League Baseball's official definition of a no-hitter, a no-hitter cannot be achieved unless the game lasts nine innings. Chicago White Stockings. See how many words from the week of Oct 12—18, you get right! Jim Creighton of the Excelsior of Brooklyn club is widely regarded to have thrown the first official shutout in history on Shut Out 8, Main article: Shutouts in baseball. Run Stolen base Stolen base percentage Caught stealing. See how many words from the week of Oct 12—18, you get right! Wins and winning percentage.
    [Show full text]
  • 2016 NFCA National Convention New Orleans: Speaker Outlines Table of Contents
    2016 NFCA National Convention New Orleans: Speaker Outlines Table of Contents “CHAMPIONSHIP COACHING: THE ‘POWER’ IN EMPOWERMENT” ………………………………….………1 Patty Gasso, head coach, University of Oklahoma “THE NEXT 60 FEET (BASERUNNING)” ………………………………………………………………………….……….2 Shonda Stanton, head coach, Marshall University “COACHING COLLEGE HITTERS” ……………………………………………………………………………….……………3 Kathy Riley, head coach, Longwood University “OPERATE LIKE A PRO” DIRECTOR OF OPERATIONS SEMINAR……………………..……………...……….4 Katie Brown, Quinlan Duhon & Kate Harris “SUPPORTING STUDENT-ATHLETES IN SUSTAINING QUALITY MENTAL & BEHAVIORAL HEALTH” …………………………………………………………………………………………………………6 Dave Mikula, Center for Family Development “DEFENSE: AN EVOLUTION” …………………………………………………………………………………………………..8 Mickey Dean, head coach, James Madison University “INNER WORKINGS OF A SUCCESSFUL STAFF” ………………………………………………………..……………10 Bo Hanson & Notre Dame staff “GRASSROOTS SUMMIT” (HS/TB/YOUTH SPECIAL PROGRAMMING) …………………………………..11 Steve Babinski, Marie Curran, Melissa Frost, Bo Hanson, Donna Papa, Maria Winn-Ratliff, Beverly Smith & NCSA staff “DRILLS, DRILLS, DRILLS”……………………………………………………………………………………………..……12 Kim Borders Dunlap (pitching), Megan Smith (infield), Stacey Nuveman Deniz (hitting & catching) “PARENT ORIENTATION” …………………………………………………………………………………………………….18 Margo Jonker, head coach, Central Michigan Univ. “HOW STATISTICS & METRICS CAN HELP YOU WIN GAMES” ……………………………………………….19 Matt Meuchel, assistant coach, University of Arkansas “CREATING CULTURE: AUTONOMY IN ACTION” ………………………………………………………...………...24
    [Show full text]
  • UPCOMING SCHEDULE and PROBABLE STARTING PITCHERS DATE OPPONENT TIME TV ORIOLES STARTER OPPONENT STARTER June 12 at Tampa Bay 4:10 P.M
    FRIDAY, JUNE 11, 2021 • GAME #62 • ROAD GAME #30 BALTIMORE ORIOLES (22-39) at TAMPA BAY RAYS (39-24) LHP Keegan Akin (0-0, 3.60) vs. LHP Ryan Yarbrough (3-3, 3.95) O’s SEASON BREAKDOWN KING OF THE CASTLE: INF/OF Ryan Mountcastle has driven in at least one run in eight- HITTING IT OFF Overall 22-39 straight games, the longest streak in the majors this season and the longest streak by a rookie American League Hit Leaders: Home 11-21 in club history (since 1954)...He is the first Oriole with an eight-game RBI streak since Anthony No. 1) CEDRIC MULLINS, BAL 76 hits Road 11-18 Santander did so from August 6-14, 2020; club record is 11-straight by Doug DeCinces (Sep- No. 2) Xander Bogaerts, BOS 73 hits Day 9-18 tember 22, 1978 - April 6, 1979) and the club record for a single-season is 10-straight by Reggie Isiah Kiner-Falefa, TEX 73 hits Night 13-21 Jackson (July 11-23, 1976)...The MLB record for consecutive games with an RBI by a rookie is No. 4) Vladimir Guerrero, Jr., TOR 70 hits Current Streak L1 10...Mountcastle has hit safely in each of these eight games, slashing .394/.412/.848 (13-for-33) Yuli Gurriel, HOU 70 hits Last 5 Games 3-2 with three doubles, four home runs, seven runs scored, and 12 RBI. Marcus Semien, TOR 70 hits Last 10 Games 5-5 Mountcastle’s eight-game hitting streak is the longest of his career and tied for the April 12-14 fourth-longest active hitting streak in the American League.
    [Show full text]
  • 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.
    [Show full text]
  • Round Rock Express 2019 GAME NOTES 3400 E
    round rock Express 2019 GAME NOTES 3400 E. Palm Valley Blvd. | Round Rock, TX 78665 | RRExpress.com Media Contact: Andrew Felts | [email protected] | 512.238.2213 Exhibition Game 2 | March 31, 2019 | 2:05 p.m. | Dell Diamond | Round Rock, TX | AM 1300 The Zone Round Rock Express (0-1) at Corpus Christi Hooks (1-0) Express: RHP Akeem Bostick (0-0, 0.00) | Hooks: LHP Brett Adcock (0-0, 0.00) EXPRESS AT A GLANCE TODAY’S GAME Overall Record: 0-0 Current Streak: -- The Triple-A Round Rock Express and Double-A Corpus Christi Hooks cap off 2019 Houston Home: 0-0 Away: 0-0 Astros Futures Weekend on Sunday at Dell Diamond. The Express and Hooks are facing off Standings: T-1st (0.0) in a two-game, home-and-home series to begin the year. Express RHP Akeem Bostick is scheduled to get the start against Hooks LHP Brett Adcock. First pitch is set for 2:05 p.m. SERIES INFORMATION BROADCAST INFORMATION Game 1 | Saturday, March 30 | L 2-1 Today’s game can be heard live on the flagship home of the Round Rock Express, Whataburger Field | Corpus Christi, TX AM 1300 The Zone. Online audio is also available at am1300thezone.iheart.com and via the WP: RHP Jose Hernandez (0-0, 0.00) LP: RHP Cy Sneed (0-1, 18.00) iHeartRadio app. Express Director of Broadcasting Mike Capps handles play-by-play duties while AM 1300 The Zone personality Mike Hardge provides color commentary. FloSports Game 2 | Sunday, March 31 | 2:05 p.m.
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]