{"id":104,"date":"2007-10-16T20:47:47","date_gmt":"2007-10-16T20:47:47","guid":{"rendered":"https:\/\/seamheads.com\/blog\/chapter-one-the-win-shares-system\/"},"modified":"2010-03-11T04:05:34","modified_gmt":"2010-03-11T04:05:34","slug":"chapter-one-the-win-shares-system","status":"publish","type":"page","link":"https:\/\/seamheads.com\/blog\/chapter-one-the-win-shares-system\/","title":{"rendered":"Chapter One: The Win Shares System"},"content":{"rendered":"

\"baseballsbest.jpg\"<\/a><\/p>\n

Title: <\/font> BASEBALL’S BEST: The TRUE Hall of Famers<\/strong> <\/font>
\nAuthor: <\/font> Michael Hoban, Ph.D. <\/font>
\n Formats: <\/font> PDF (ebook) | Paperback <\/font>
\n<\/font> Pages: <\/font> 223<\/font><\/p>\n

\"blank2.jpg\"<\/a><\/p>\n\n\n\n\n\n
Click cover to order book<\/em><\/td>\n<\/tr>\n
 <\/td>\n<\/tr>\n
Chapter One<\/strong><\/font><\/td>\n<\/tr>\n
The Win Shares System<\/strong><\/font><\/td>\n<\/tr>\n<\/table>\n

The analysis in this book is based on the state of the art system called WIN SHARES<\/strong> devised by the baseball statistical guru Bill James and explained in the book of the same name. <\/span>From p.260 of the book, the author\u00e2\u20ac\u2122s intention is clear as he states:<\/em> <\/o><\/span><\/p>\n

\u00e2\u20ac\u0153The purpose of figuring Win Shares was not to wrap up any discussion; rather, the purpose was to open up many more issues, to make additional topics and additional issues more accessible to research. <\/span>The original idea of Win Shares was not that people would read it and say \u00e2\u20ac\u0153Oh, well, that answers that question.\u00e2\u20ac\u009d <\/span>Exactly the opposite; what I wanted was for people to say \u00e2\u20ac\u0153Oh, I can use that to study this. <\/span>I can use these Win Shares to study \u00e2\u20ac\u00a6\u00e2\u20ac\u009d whatever it is you want to study.\u00e2\u20ac\u009d<\/o><\/span><\/p>\n

When I first began to work with the system, I sent an early article to Mr. James for his consideration. <\/span>Mr. James responded to the article as follows (12\/2\/2004):<\/em> <\/o><\/span><\/p>\n

\u00e2\u20ac\u0153<\/span>Mike– I read and enjoyed the article, and I appreciate your using Win <\/o> Shares for the purpose for which it was intended. . .thanks. \u00e2\u20ac\u00a6 Bill\u00e2\u20ac\u009d <\/o><\/span><\/p>\n

This book explains the rationale behind and the use of the NEWS system (Non-traditional Evaluative Win Shares). <\/span>The NEWS system uses win shares to tell us which players had the best careers<\/strong>. <\/span>This could be interpreted to mean which players were \u00e2\u20ac\u0153the best players.\u00e2\u20ac\u009d <\/span>But that conclusion might be open to further discussion.<\/o><\/span><\/p>\n

The \u00e2\u20ac\u0153Best Players\u00e2\u20ac\u009d<\/o><\/span><\/strong><\/h6>\n

Fans of any sport are usually interested in knowing who are (or were) the best players in the game. <\/span>At the end of the playing season, many fans enjoy looking back and being able to say that player A had a better season than player B. <\/span>And when a player\u00e2\u20ac\u2122s career is ending, we like to conclude that \u00e2\u20ac\u0153C was better than D and almost as good as E.\u00e2\u20ac\u009d <\/span>Comparing athletes in this way is almost a national pastime in itself. <\/span><\/o><\/span><\/p>\n

Baseball fans are particularly fortunate in that no other sport rivals baseball for the sheer number of statistics available for comparing the players. <\/span>In fact, there are so many numbers available, that it often leads to confusion as to what to look at in order to judge how good a player really is (or was). <\/span>For many years, a player\u00e2\u20ac\u2122s batting average (BA) was used to suggest who were the best hitters. <\/span>But, careful analysis over a number of years has now convinced us that a combination of on-base-percentage (OBP) and slugging average (SLG) is a better indicator of who were the most effective batters. <\/span><\/o><\/span><\/span><\/p>\n

Of course, in baseball, batting alone does not tell us who is a \u00e2\u20ac\u0153better player.\u00e2\u20ac\u009d <\/span>Fielding must also enter into the equation. <\/span>And judging fielding has always been more difficult than judging hitting. <\/span>The skills required of a good shortstop or catcher are much different than those required of a left fielder or a first baseman. <\/span>And attempting to judge who was the best \u00e2\u20ac\u0153all-around\u00e2\u20ac\u009d player has always been difficult.<\/o><\/span><\/p>\n

But not to worry. <\/span>Over the years, there have been a number of dedicated people who have devoted a considerable amount of time into researching these questions. <\/span>Many of these analysts are members of an organization known as SABR (Society for American Baseball Research). <\/span>As a baseball fan and a mathematician, I have spent considerable time over the past ten years studying the various approaches that have been taken regarding the comparison of baseball players. <\/span>And I am happy to report that the most highly respected of all of these analysts, Bill James, has developed a system that I believe is a quantum leap ahead of all such systems<\/strong> in this regard.<\/o><\/span><\/p>\n

Bill James is a dedicated researcher and a prolific and enjoyable writer. <\/span>For more than thirty years he has been considered the guru of baseball analysis. <\/span>In fact, in 2004, as a special advisor to the Boston Red Sox front office, he contributed to that team\u00e2\u20ac\u2122s first World Series triumph in more than eighty years.<\/o><\/span><\/p>\n

In 2002, Bill James published his book called WIN SHARES<\/strong> in which he introduced a new system that was the product of more than twenty-five years of research. <\/span>And it is this system that I am convinced is far better than any other that has been developed<\/strong>. <\/span>The method is so revolutionary that I believe that it is fair to say that FOR THE FIRST TIME EVER, we are able to validly look at and compare players (including hitting and fielding and pitching) no matter when they played or who they played for. <\/span>The key to the value of Win Shares is that it tells us how valuable a player was to his team<\/em> each season<\/strong>. <\/span>And, of course, a player\u00e2\u20ac\u2122s value to his team is what the game is all about.<\/o><\/span><\/span><\/p>\n

Win Shares is a very complex system (the book is 728 pages long). <\/span>But it is not really necessary to understand every nuance of the system in order to appreciate its value. <\/span>The true genius of the approach seems to be two-fold. <\/span>First, like any valid evaluation system, it measures a player’s value relative to the era in which he played and to the playing conditions under which he performed. <\/span>That is, adjustments are made to account for such things as playing in the \u00e2\u20ac\u0153dead-ball era\u00e2\u20ac\u009d or playing in a \u00e2\u20ac\u0153pitcher\u00e2\u20ac\u2122s ballpark.\u00e2\u20ac\u009d <\/span>But the second (and more remarkable achievement) is that it appears to be able to measure a player’s value regardless of whether he played on a winning or a losing team. <\/span>And it is not necessary to completely understand how the system works in order to enjoy the results that it produces.<\/o><\/span><\/p>\n

Put as simply as possible, here is what the Win Shares system does – it tells us how good a season a player had. <\/span>It awards a team a certain number of win shares for the season \u00e2\u20ac\u201c depending on the number of games that the team won during the season. <\/span>It then takes those win shares and distributes them among the players on the team depending on each player\u00e2\u20ac\u2122s contribution to the team during the season. <\/span>And, as a rule of thumb, here is how the number of win shares in a season can be interpreted for an individual position player:<\/span><\/p>\n

1. <\/span>30-40 Win Shares <\/span>= <\/span>MVP-type Season<\/o>
\n2. <\/span><\/span><\/span>20-30 Win Shares <\/span>= <\/span>All-Star Season<\/o>
\n3. <\/span><\/span><\/span>10-20 Win Shares <\/span>= <\/span>Solid Regular Player <\/o>
\n4. <\/span>0-10 Win Shares <\/span>= <\/span>Bench Player<\/span>\n<\/p>\n

It is worth noting that the average MVP winner through 2004 had 33.4 win shares for the season. <\/span><\/o><\/span><\/p>\n

Here is how the Win Shares system is described in The Bill James Handbook 2005 <\/strong><\/span>(ACTA Sports) \u00e2\u20ac\u201c p. 361<\/o><\/span><\/span><\/p>\n

\u00e2\u20ac\u0153Bill James devised Win Shares to reduce a player\u00e2\u20ac\u2122s statistics to a single number related to the number of wins he contributed to his team. <\/span>It includes offensive, pitching and defensive accomplishments. <\/span>The quality of the team does not effect an individual player\u00e2\u20ac\u2122s Win Shares. <\/span>A great player on a bad team will rate as well as a great player on a good team. \u00e2\u20ac\u00a6<\/o><\/span><\/em><\/p>\n

A Win Share is one-third of a team\u00e2\u20ac\u2122s win, credited to an individual player. <\/span>The Win Shares credited to the players on a team always total up to exactly three times the team\u00e2\u20ac\u2122s win total. <\/span>If the team wins 100 games, the players on the team will be credited with 300 Win Shares \u00e2\u20ac\u201c 300 thirds of a win. <\/span>If the team wins 80 games, the players on the team will be credited with 240 Win Shares, always and without exception.<\/o><\/em><\/span><\/p>\n

<\/em>Win Shares are a great tool for evaluating trades, award voting and Hall of Fame credentials.\u00e2\u20ac\u009d<\/o><\/span><\/em><\/p>\n

I certainly agree with this last statement and that is why I feel that Win Shares (when used appropriately) can tell us which players definitely have Hall of Fame numbers.<\/o><\/span><\/p>\n

To get a little more flavor of what Win Shares are all about, consider the following statements from Bill James himself in the Introduction to the book WIN SHARES <\/strong><\/span><\/em>(STATS, Inc., 2002).<\/o><\/span><\/em><\/span><\/p>\n

<\/em>\u00e2\u20ac\u0153For many years, I have wanted to have a system to summarize each player\u00e2\u20ac\u2122s value each season into a simple integer. <\/span>Willie Mays\u00e2\u20ac\u2122 value in 1954 is 40, in 1955, 40, in 1956, 27, while Mickey Mantle in the same three years is 36,41,49. <\/span>If we had an analytical system <\/em><\/span>in which we had<\/em> <\/em>confidence, and which delivered results in that simple a form, it would open the door to researching thousands of questions which are virtually inaccessible without such a method. <\/span>It would reduce enormously the time and effort required to research such questions, which can be accessed by other methods, but only with great difficulty. <\/span>(p.3)<\/o><\/em><\/span><\/p>\n

<\/em>We have dozens of methods to compare players. <\/span>We have piecemeal ways to put those together. <\/span>What we lack is a way of tying them all into a coherent analysis. <\/span>We need a comprehensive system, in which we have confidence, which has a place for all of the things we must think about when trying to assess value \u00e2\u20ac\u201c productivity, park illusions, defense, playing time, contributions to winning teams. <\/span>Everything. <\/span>(p. 5)<\/o><\/span><\/em><\/p>\n

<\/em>This is the only analytical system I am aware of which is team-based, rather than derived from individual stats. <\/span>Most analysis builds up from the performance of individuals. <\/span>This analysis breaks down the performance of the team.<\/span><\/em> <\/span>(p. 9) <\/o><\/p>\n

This last point is crucial to understanding the uniqueness of the Win Shares approach and to appreciating the system. <\/span>Besides being comprehensive, it looks first at the team\u00e2\u20ac\u2122s accomplishments and then determines each player\u00e2\u20ac\u2122s contribution to the team\u00e2\u20ac\u2122s success.<\/o><\/span><\/p>\n

Win Shares \u00e2\u20ac\u201c Comprehensive Yet Simple<\/o><\/span><\/strong><\/p>\n

As long as the game has been played, fans have attempted to compare players using the many statistics available to do so. <\/span>How many hits or home runs or runs-batted-in or runs scored or stolen bases did the player have? <\/span>What was his batting average or on-base percentage or slugging average or OPS? <\/span>And these numbers do not tell us anything about his fielding ability.<\/o><\/span><\/p>\n

The true genius of Win Shares is that it includes ALL of a player\u00e2\u20ac\u2122s contributions to his team and represents them in a single number. <\/span>So that if we want to know who had the best season, we can simply list those players who had the most win shares for that particular season. <\/span>For example, here are the top ten players in each league in 2006 (data from hardballtimes.com). <\/o><\/span><\/p>\n\n\n
American League<\/strong><\/font><\/td>\n<\/tr>\n<\/table>\n\n\n\n\n\n\n\n\n\n\n\n\n
 <\/td>\nPlayer<\/strong><\/font><\/td>\nBatting<\/strong><\/font><\/td>\nFielding<\/strong><\/font><\/td>\nWin Shares<\/strong><\/font><\/td>\n<\/tr>\n
1.<\/strong><\/font><\/td>\nDerek Jeter<\/strong><\/font><\/td>\n28.0<\/strong><\/font><\/td>\n4.6<\/strong><\/font><\/td>\n33<\/strong><\/font><\/td>\n<\/tr>\n
2.<\/strong><\/font><\/td>\nJoe Mauer <\/strong><\/font><\/td>\n<\/font>21.3<\/strong><\/font><\/td>\n<\/font>9.5<\/strong><\/font><\/td>\n31<\/strong><\/font><\/td>\n<\/tr>\n
3.<\/strong><\/font><\/td>\nDavid Ortiz<\/strong><\/font><\/td>\n<\/font>29.3<\/strong><\/font><\/td>\n<\/font>0.1<\/strong><\/font><\/td>\n<\/font>29<\/strong><\/font><\/td>\n<\/tr>\n
4.<\/strong><\/font><\/td>\nManny Ramirez<\/strong><\/font><\/td>\n<\/font>26.9<\/strong><\/font><\/td>\n<\/font>2.1<\/strong><\/font><\/td>\n<\/font>29<\/strong><\/font><\/td>\n<\/tr>\n
5.<\/strong><\/font><\/td>\nJustin Morneau <\/strong><\/font><\/td>\n<\/font>25.5<\/strong><\/font><\/td>\n<\/font>2.0<\/strong><\/font><\/td>\n<\/font>28<\/strong><\/font><\/td>\n<\/tr>\n
6.<\/strong><\/font><\/td>\nRaul Ibanez<\/strong><\/font><\/td>\n<\/font>24.0<\/strong><\/font><\/td>\n<\/font>3.1<\/strong><\/font><\/td>\n<\/font>27<\/strong><\/font><\/td>\n<\/tr>\n
7.<\/strong><\/font><\/td>\nJermaine Dye<\/strong><\/font><\/td>\n<\/font>23.7<\/strong><\/font><\/td>\n<\/font>2.8<\/strong><\/font><\/td>\n<\/font>27<\/strong><\/font><\/td>\n<\/tr>\n
8.<\/strong><\/font><\/td>\nJim Thome <\/strong><\/font><\/td>\n<\/font>25.9<\/strong><\/font><\/td>\n<\/font>0.0<\/strong><\/font><\/td>\n<\/font>26<\/strong><\/font><\/td>\n<\/tr>\n
9.<\/strong><\/font><\/td>\nCarlos Guillen<\/strong><\/font><\/td>\n<\/font>21.5<\/strong><\/font><\/td>\n<\/font>4.3<\/strong><\/font><\/td>\n<\/font>26<\/strong><\/font><\/td>\n<\/tr>\n
10.<\/strong><\/font><\/td>\nMichael Young<\/strong><\/font><\/td>\n<\/font>18.5<\/strong><\/font><\/td>\n<\/font>7.7<\/strong><\/font><\/td>\n<\/font>26<\/strong><\/font><\/td>\n<\/tr>\n<\/table>\n\n\n
<\/font><\/td>\n<\/tr>\n<\/table>\n\n\n
National League<\/strong><\/font><\/td>\n<\/tr>\n<\/table>\n\n\n\n\n\n\n\n\n\n\n\n\n
 <\/td>\nPlayer<\/strong><\/font><\/td>\nBatting<\/strong><\/font><\/td>\nFielding<\/strong><\/font><\/td>\nWin Shares<\/strong><\/font><\/td>\n<\/tr>\n
1.<\/strong><\/font><\/td>\nAlbert Pujols <\/strong><\/font><\/td>\n<\/font>36.3<\/strong><\/font><\/td>\n<\/font>2.4<\/strong><\/font><\/td>\n<\/font>39<\/strong><\/font><\/td>\n<\/tr>\n
2.<\/strong><\/font><\/td>\nCarlos Beltran<\/strong><\/font><\/td>\n<\/font>30.0<\/strong><\/font><\/td>\n<\/font>8.3<\/strong><\/font><\/td>\n<\/font>38<\/strong><\/font><\/td>\n<\/tr>\n
3.<\/strong><\/font><\/td>\nLance Berkman <\/strong><\/font><\/td>\n<\/font>31.7<\/strong><\/font><\/td>\n<\/font>2.0<\/strong><\/font><\/td>\n<\/font>34<\/strong><\/font><\/td>\n<\/tr>\n
4.<\/strong><\/font><\/td>\nMiguel Cabrera <\/strong><\/font><\/td>\n<\/font>30.9<\/strong><\/font><\/td>\n<\/font>2.8<\/strong><\/font><\/td>\n<\/font>34<\/strong><\/font><\/td>\n<\/tr>\n
5.<\/strong><\/font><\/td>\nDavid Wright<\/strong><\/font><\/td>\n<\/font>27.4<\/strong><\/font><\/td>\n<\/font>4.3<\/strong><\/font><\/td>\n<\/font>32<\/strong><\/font><\/td>\n<\/tr>\n
6.<\/strong><\/font><\/td>\nRyan Howard
\n<\/strong><\/font><\/td>\n		<\/font>29.8<\/strong><\/font><\/td>\n<\/font>1.2<\/strong><\/font><\/td>\n<\/font>31<\/strong><\/font><\/td>\n<\/tr>\n
7.<\/strong><\/font><\/td>\nAlfonso Soriano <\/strong><\/font><\/td>\n<\/font>25.9<\/strong><\/font><\/td>\n<\/font>3.6<\/strong><\/font><\/td>\n<\/font>30<\/strong><\/font><\/td>\n<\/tr>\n
8.<\/strong><\/font><\/td>\nJose Reyes <\/strong><\/font><\/td>\n<\/font>26.3<\/strong><\/font><\/td>\n<\/font>3.1<\/strong><\/font><\/td>\n<\/font>29<\/strong><\/font><\/td>\n<\/tr>\n
9.<\/strong><\/font><\/td>\nMike Cameron<\/strong><\/font><\/td>\n<\/font>21.2<\/strong><\/font><\/td>\n<\/font>7.2<\/strong><\/font><\/td>\n<\/font>28<\/strong><\/font><\/td>\n<\/tr>\n
10.<\/strong><\/font><\/td>\nChase Utley <\/strong><\/font><\/td>\n<\/font>23.2<\/strong><\/font><\/td>\n<\/font>4.9<\/strong><\/font><\/td>\n<\/font>28<\/strong><\/font><\/td>\n<\/tr>\n<\/table>\n

As you can see, Derek Jeter had the best overall season in the American League in 2006 although David Ortiz had the best hitting season. <\/span>And in the National League, Albert Pujols had both the best overall season and the best hitting season. <\/span>As it turns out, Justin Morneau (American League) and Ryan Howard (National League) were voted the MVPs for 2006. <\/span><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Title: BASEBALL’S BEST: The TRUE Hall of Famers Author: Michael Hoban, Ph.D. Formats: PDF (ebook) | Paperback Pages: 223 Click cover to order book   Chapter One The Win Shares System The analysis in this book is based on the state of the art system called WIN SHARES devised by the baseball statistical guru Bill […]<\/p>\n","protected":false},"author":18,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"open","template":"","meta":{"footnotes":""},"class_list":["post-104","page","type-page","status-publish","hentry"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/seamheads.com\/blog\/wp-json\/wp\/v2\/pages\/104","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/seamheads.com\/blog\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/seamheads.com\/blog\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/seamheads.com\/blog\/wp-json\/wp\/v2\/users\/18"}],"replies":[{"embeddable":true,"href":"https:\/\/seamheads.com\/blog\/wp-json\/wp\/v2\/comments?post=104"}],"version-history":[{"count":0,"href":"https:\/\/seamheads.com\/blog\/wp-json\/wp\/v2\/pages\/104\/revisions"}],"wp:attachment":[{"href":"https:\/\/seamheads.com\/blog\/wp-json\/wp\/v2\/media?parent=104"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}