# Baseball Classics All-Time All-Star Greats Game Team Roster

Total Page：16

File Type：pdf, Size：1020Kb

Recommended publications
• The Decline and Fall of the Pirates Family
[Show full text]
• Problem of the Day Make a Scatter Plot of the Data. Is Linear Regression
Problem of the Day Weight in Static motion(kg) Weight(kg) Make a scatter plot 26 27.9 of the data. 29.9 29.1 Is linear regression 39.5 38.0 appropriate? Why 25.1 27.0 or why not? 31.6 30.3 36.2 34.5 25.1 27.8 31.0 29.6 35.6 33.1 40.2 35.5 Salary(in Problem of the Day Player Year millions) Nolan Ryan 1980 1.0 Is it appropriate to use George Foster 1982 2.0 linear regression Kirby Puckett 1990 3.0 to predict salary Jose Canseco 1991 4.7 from year? Roger Clemens 1996 5.3 Why or why not? Ken Griffey, Jr 1997 8.5 Albert Belle 1997 11.0 Pedro Martinez 1998 12.5 Mike Piazza 1999 12.5 Mo Vaughn 1999 13.3 Kevin Brown 1999 15.0 Carlos Delgado 2001 17.0 Alex Rodriguez 2001 22.0 Manny Ramirez 2004 22.5 Alex Rodriguez 2005 26.0 Chapter 10 Re­Expressing Data: Get It Straight! Linear Regression­easiest of methods, how can we make our data linear in appearance Can we re­express data? Change functions or add a function? Can we think about data differently? What is the meaning of the y­units? Why do we need to re­express? Methods to deal with data that we have learned 1. 2. Goal 1 ­making data symmetric Goal 2 ­make spreads more alike(centers are not necessarily alike), less spread out Goal 3(most used) ­make data appear more linear Goal 4(similar to Goal 3) ­make the data in a scatter plot more spread out Ladder of Powers(pg 227) Straightening is good, but limited ­multi­modal data cannot be "straightened" ­multiple models is really the only way to deal with this data Things to Remember ­we want linear regression because it is easiest (curves are possible, but beyond the scope of our class) ­don't choose a model based on r or R2 ­don't go too far from the Ladder of Powers ­negative values or multi­modal data are difficult to re­express Salary(in Player Year Find an appropriate millions) Nolan Ryan 1980 1.0 linear model for the George Foster 1982 2.0 data.
[Show full text]
• Fair Ball! Why Adjustments Are Needed
© Copyright, Princeton University Press. No part of this book may be distributed, posted, or reproduced in any form by digital or mechanical means without prior written permission of the publisher. CHAPTER 1 Fair Ball! Why Adjustments Are Needed King Arthur’s quest for it in the Middle Ages became a large part of his legend. Monty Python and Indiana Jones launched their searches in popular 1974 and 1989 movies. The mythic quest for the Holy Grail, the name given in Western tradition to the chal- ice used by Jesus Christ at his Passover meal the night before his death, is now often a metaphor for a quintessential search. In the illustrious history of baseball, the “holy grail” is a ranking of each player’s overall value on the baseball diamond. Because player skills are multifaceted, it is not clear that such a ranking is possible. In comparing two players, you see that one hits home runs much better, whereas the other gets on base more often, is faster on the base paths, and is a better ﬁelder. So which player should rank higher? In Baseball’s All-Time Best Hitters, I identiﬁed which players were best at getting a hit in a given at-bat, calling them the best hitters. Many reviewers either disapproved of or failed to note my deﬁnition of “best hitter.” Although frequently used in base- ball writings, the terms “good hitter” or best hitter are rarely deﬁned. In a July 1997 Sports Illustrated article, Tom Verducci called Tony Gwynn “the best hitter since Ted Williams” while considering only batting average.
[Show full text]
• CONGRESSIONAL RECORD— Extensions of Remarks E933 HON
[Show full text]
DETROIT TIGERS’ 4 GREATEST HITTERS Table of CONTENTS Contents Warm-Up, with a Side of Dedications ....................................................... 1 The Ty Cobb Birthplace Pilgrimage ......................................................... 9 1 Out of the Blocks—Into the Bleachers .............................................. 19 2 Quadruple Crown—Four’s Company, Five’s a Multitude ..................... 29 [Gates] Brown vs. Hot Dog .......................................................................................... 30 Prince Fielder Fields Macho Nacho ............................................................................. 30 Dangerfield Dangers .................................................................................................... 31 #1 Latino Hitters, Bar None ........................................................................................ 32 3 Hitting Prof Ted Williams, and the MACHO-METER ......................... 39 The MACHO-METER ..................................................................... 40 4 Miguel Cabrera, Knothole Kids, and the World’s Prettiest Girls ........... 47 Ty Cobb and the Presidential Passing Lane ................................................................. 49 The First Hammerin’ Hank—The Bronx’s Hank Greenberg ..................................... 50 Baseball and Heightism ............................................................................................... 53 One Amazing Baseball Record That Will Never Be Broken ......................................
[Show full text]
• Tml American - Single Season Leaders 1954-2016
TML AMERICAN - SINGLE SEASON LEADERS 1954-2016 AVERAGE (496 PA MINIMUM) RUNS CREATED HOMERUNS RUNS BATTED IN 57 ♦MICKEY MANTLE .422 57 ♦MICKEY MANTLE 256 98 ♦MARK McGWIRE 75 61 ♦HARMON KILLEBREW 221 57 TED WILLIAMS .411 07 ALEX RODRIGUEZ 235 07 ALEX RODRIGUEZ 73 16 DUKE SNIDER 201 86 WADE BOGGS .406 61 MICKEY MANTLE 233 99 MARK McGWIRE 72 54 DUKE SNIDER 189 80 GEORGE BRETT .401 98 MARK McGWIRE 225 01 BARRY BONDS 72 56 MICKEY MANTLE 188 58 TED WILLIAMS .392 61 HARMON KILLEBREW 220 61 HARMON KILLEBREW 70 57 TED WILLIAMS 187 61 NORM CASH .391 01 JASON GIAMBI 215 61 MICKEY MANTLE 69 98 MARK McGWIRE 185 04 ICHIRO SUZUKI .390 09 ALBERT PUJOLS 214 99 SAMMY SOSA 67 07 ALEX RODRIGUEZ 183 85 WADE BOGGS .389 61 NORM CASH 207 98 KEN GRIFFEY Jr. 67 93 ALBERT BELLE 183 55 RICHIE ASHBURN .388 97 LARRY WALKER 203 3 tied with 66 97 LARRY WALKER 182 85 RICKEY HENDERSON .387 00 JIM EDMONDS 203 94 ALBERT BELLE 182 87 PEDRO GUERRERO .385 71 MERV RETTENMUND .384 SINGLES DOUBLES TRIPLES 10 JOSH HAMILTON .383 04 ♦ICHIRO SUZUKI 230 14♦JONATHAN LUCROY 71 97 ♦DESI RELAFORD 30 94 TONY GWYNN .383 69 MATTY ALOU 206 94 CHUCK KNOBLAUCH 69 94 LANCE JOHNSON 29 64 RICO CARTY .379 07 ICHIRO SUZUKI 205 02 NOMAR GARCIAPARRA 69 56 CHARLIE PEETE 27 07 PLACIDO POLANCO .377 65 MAURY WILLS 200 96 MANNY RAMIREZ 66 79 GEORGE BRETT 26 01 JASON GIAMBI .377 96 LANCE JOHNSON 198 94 JEFF BAGWELL 66 04 CARL CRAWFORD 23 00 DARIN ERSTAD .376 06 ICHIRO SUZUKI 196 94 LARRY WALKER 65 85 WILLIE WILSON 22 54 DON MUELLER .376 58 RICHIE ASHBURN 193 99 ROBIN VENTURA 65 06 GRADY SIZEMORE 22 97 LARRY
[Show full text]
• 2011 Topps Gypsy Queen Baseball
Hobby 2011 TOPPS GYPSY QUEEN BASEBALL Base Cards 1 Ichiro Suzuki 49 Honus Wagner 97 Stan Musial 2 Roy Halladay 50 Al Kaline 98 Aroldis Chapman 3 Cole Hamels 51 Alex Rodriguez 99 Ozzie Smith 4 Jackie Robinson 52 Carlos Santana 100 Nolan Ryan 5 Tris Speaker 53 Jimmie Foxx 101 Ricky Nolasco 6 Frank Robinson 54 Frank Thomas 102 David Freese 7 Jim Palmer 55 Evan Longoria 103 Clayton Richard 8 Troy Tulowitzki 56 Mat Latos 104 Jorge Posada 9 Scott Rolen 57 David Ortiz 105 Magglio Ordonez 10 Jason Heyward 58 Dale Murphy 106 Lucas Duda 11 Zack Greinke 59 Duke Snider 107 Chris V. Carter 12 Ryan Howard 60 Rogers Hornsby 108 Ben Revere 13 Joey Votto 61 Robin Yount 109 Fred Lewis 14 Brooks Robinson 62 Red Schoendienst 110 Brian Wilson 15 Matt Kemp 63 Jimmie Foxx 111 Peter Bourjos 16 Chris Carpenter 64 Josh Hamilton 112 Coco Crisp 17 Mark Teixeira 65 Babe Ruth 113 Yuniesky Betancourt 18 Christy Mathewson 66 Madison Bumgarner 114 Brett Wallace 19 Jon Lester 67 Dave Winfield 115 Chris Volstad 20 Andre Dawson 68 Gary Carter 116 Todd Helton 21 David Wright 69 Kevin Youkilis 117 Andrew Romine 22 Barry Larkin 70 Rogers Hornsby 118 Jason Bay 23 Johnny Cueto 71 CC Sabathia 119 Danny Espinosa 24 Chipper Jones 72 Justin Morneau 120 Carlos Zambrano 25 Mel Ott 73 Carl Yastrzemski 121 Jose Bautista 26 Adrian Gonzalez 74 Tom Seaver 122 Chris Coghlan 27 Roy Oswalt 75 Albert Pujols 123 Skip Schumaker 28 Tony Gwynn Sr. 76 Felix Hernandez 124 Jeremy Jeffress 2929 TTyy Cobb 77 HHunterunter PPenceence 121255 JaJakeke PPeavyeavy 30 Hanley Ramirez 78 Ryne Sandberg 126 Dallas
[Show full text]
• From the Bullpen
1 FROM THE BULLPEN Official Publication of The Hot Stove League Eastern Nebraska Division 1992 Season Edition No. 11 September 22, 1992 Fellow Owners (sans Possum): We have been to the mountaintop, and we have seen the other side. And on the other side was -- Cooperstown. That's right, we thought we had died and gone to heaven. On our recent visit to this sleepy little hamlet in upstate New York, B.T., U-belly and I found a little slice of heaven at the Baseball Hall of Fame. It was everything we expected, and more. I have touched the plaque of the one they called the Iron Horse, and I have been made whole. The hallowed halls of Cooperstown provided spine-tingling memories of baseball's days of yore. The halls fairly echoed with voices and sounds from yesteryear: "Say it ain't so, Joe." "Can't anybody here play this game?" "Play ball!" "I love Brian Piccolo." (Oops, wrong museum.) "I am the greatest of all time." (U-belly's favorite.) "I should make more money than the president, I had a better year." "Where have you gone, Joe DiMaggio?" And of course: "I feel like the luckiest man alive." Hang on while I regain my composure. Sniff. Snort. Thanks. I'm much better From the Bullpen Edition No. 11 September 22, 1992 Page 2 now. If you ever get the chance to go to Cooperstown, take it. But give your wife your credit card and leave her at Macy's in New York City. She won't get it.
[Show full text]
• MLB Curt Schilling Red Sox Jersey MLB Pete Rose Reds Jersey MLB