Tag Archives: history

Top Clutch Game Winning Hitters in Post Season History

Here is another example of a statistic that can only be derived from knowing event data.

Clutch Game Winning  is described in the previous post. I thought it would be interesting to run post season event data through this algorithm to see who were the best clutch game winning hitters with respect to giving his team the lead when it mattered in post season play. The events included in this set are for all post season play from 1903 to 2012. Modern era players have had more opportunities since there are so many more playoff games with divisional and now wild card playoff games.

This list differs from the RISP post season list previously posted which measures runs above average in runners in scoring position. A batter must put his team in the lead to earn one of these.  A clutch game winning stat increments once for each occurrence  whereas the RISP stat counts batted in runs and compares that to league averages.

Post Season Clutch Hitters

23 Bernie_Williams_NYA
21 Manny_Ramirez_TBA
17 Chipper_Jones_ATL
15 David_Ortiz_MIN
14 Derek_Jeter_NYA
14 David_Justice_OAK
14 Lou_Gehrig_TOT
14 Paul_O’Neill_TOT
13 Albert_Pujols_SLN
12 George_Brett_TOT
12 Babe_Ruth_TOT
12 Jim_Edmonds_SLN
11 Fred_McGriff_TOT
11 Miguel_Cabrera_FLO
11 John_Olerud_NYA
10 Tino_Martinez_SLN
10 Josh_Hamilton_TEX
10 Chase_Utley_PHI
10 Jermaine_Dye_OAK
10 Lance_Berkman_SLN
9 Joe_DiMaggio_TOT
9 Brian_Jordan_ATL
9 Alex_Rodriguez_NYA
9 Edgardo_Alfonzo_SFN
9 Joe_Carter_TOT
9 Reggie_Jackson_TOT
9 Johnny_Damon_TBA
9 Yogi_Berra_TOT
9 Jim_Leyritz_TOT

Pitching and ERA

This post will focus on the career of Christy Mathewson to further explain what WAA represents when judging  value of baseball players.  Christy Mathewson pitched from 1900 – 1916 for the New York Giants (SFN) and had one of the top careers of all time; ranked #36 with a 92.5 career WAA.

There is an interesting blip in the year 1906 of his career.  Christy pitched a 22-8 season yet his WAA=-1.7  is below average meaning he hurt his team by 1.7 games.   Stats like WAA provide a lens through which a collection of data can be seen.  At first glance one would look at a pitcher’s W/L record to make a judgment as to that player’s worth.  In this case the win loss record deceives.

Oddities like this make me check the code and math generating these tables to see if a bug exists.   This post will explain the result of my analysis and hopefully provide insight to the philosophy behind WAA and other player rating methods to be introduced later.

First a shout out to baseball-reference.com which I use a lot for reference.   Baseball-reference has far more information about players, teams, history, and everything baseball.  This site cannot possibly reproduce their fine work.  Tables presented here are of one format, the reasoning for which will be explained in a future post.  Baseball-reference has a stat called WAR which resembles WAA but calculated very differently and will produce very different rankings at times.  Christy Mathewson’s full career stats can be seen here on their site.  His value amongst other 1906 players according to WAR can be seen here (click on WAR to see rankings).  Even baseball-reference ranks him #19 amongst pitchers with a WAR=2.5 so  they see a problem with this 20+ game winning pitcher too.

Let’s take a look at Mathewson’s career trends by listing his stats 2 years before and after 1906.

1904 5.3 367.7 2.03 48 33 12 Christy_Mathewson_SFN PITCH
1905 12.8 338.7 1.28 43 31 9 Christy_Mathewson_SFN PITCH
1906 -1.7 266.7 2.97 38 22 12 Christy_Mathewson_SFN PITCH
1907 3.8 315.0 2.00 41 24 12 Christy_Mathewson_SFN PITCH
1908 8.7 390.7 1.43 56 37 11 Christy_Mathewson_SFN PITCH

Mathewson came off a 31 win season in 1905 posting a historical high WAA=12.8 and then dipped negative in 1906 after which he climbs to a top tier player again in the next two years.  Notice the correlation between the ERA column and WAA.  In 1906 Mathewson posted an ERA more than double that of 1905 and 50% higher than 1904 and 1907.

Pitchers as a class are the only players responsible for team runs against column.  ERA directly relates to the number of runs against a pitcher gives up.

ERA = RA/Games where Games = IP/9.

The above formula is the definition of ERA.  The more runs a pitcher gives up directly relates to  team losses.  Let’s take a look at Mathewson’s ranking amongst the league to provide context with respect to his ERA.

Top 5 Pitchers:

1 10.6 277.3 1.04 36 26 6 Mordecai_Brown_CHN PITCH
2 7.3 322.0 1.73 41 23 13 Vic_Willis_PIT PITCH
3 6.8 260.7 1.59 34 16 11 Barney_Pelty_BAL PITCH
4 6.7 250.7 1.51 31 20 8 Jack_Pfiester_CHN PITCH
5 5.9 219.3 1.52 28 18 6 Doc_White_CHA PITCH
143 -1.7 266.7 2.97 38 22 12 Christy_Mathewson_SFN PITCH
175 -7.7 207.7 4.12 29 6 18 George_Winter_BOS PITCH

Christy ranks 143/175 in the league according to WAA, much of it to do with how many runs he gave up.  Maybe part of why he won so many games is through his above average batting.

112 0.2 0.264 0.330 103 14 6 Christy_Mathewson_SFN BAT

Usually pitchers are negative in this area.  Wins and losses are determined algorithmically by a rules committee to give prizes to pitchers for their participation in each game. Mathewson got lucky to win 22 games. He played for the Giants who finished with 96 wins,  second behind the Cubs’ 116  so Mathewson had a lot of hitting behind him to compensate for how many runs he cost his team.  It is extreme that a team with 96 wins finishes 20 games out of first in a 154 game season.   It might not have mattered how Mathewson pitched that year with such disparity between team talent.

WAA and Mathewson’s league ranking was appropriate after analyzing this oddity.