Category Archives: MLB Posts

Ballpark Review: Camden Yards

photo (3)

Home of the Baltimore Orioles

Baltimore, MD

It’s been almost a year since I reviewed a ballpark for this series, but there’s a very good reason. I hadn’t been to an MLB stadium in a very long time. Sure, I’ve been to a handful about which I haven’t written, but I didn’t want to write about Progressive Field when I hadn’t been there in five years. Well, problem solved. I just spent three days at Oriole Park at Camden Yards.

Camden Yards is often thought of as the first of the new “old-style” parks that open out into a city and provide the comforts of modern life. U.S Cellular Field this is not. Part of Camden’s charm, in my opinion, is it’s cozy dimensions. While the concourses are spacious and only crowded when busloads of children are dumped into them, the seating is very close to the action. I sat in the last few rows of the lower deck all three games and was never very far from the action. Some parks have lots of foul territory, which Camden does not, but they are also built on a very gentle incline to maximize seating, meaning that you can end up quite a ways from the action. Not so in Baltimore.

The stadium features a three tiered design with the lower deck also divided into two parts. I sat in the rear sections of the lower deck and the only real problem was that the upper deck hangs over pretty significantly, obstructing some of the main scoreboard and high fly balls. You still have a great view of the pitcher, plate, and all of the fielders, but you can lose things from time to time. Pretty much everywhere else in the park avoids this type of issue. Overall, as long as you know what you’re getting, the sight-lines are quite good. It actually reminds me a lot of Great American in Cincinnati as far as the shape of the thing is concerned.

The food is pretty standard with the unique options being crabcake-seafood offerings and the Boog’s sandwich station out in right field. The basic offerings were good, but unspectacular and are priced pretty much in line with the average major league park. Ticket prices were reasonable all the way around, although I picked a Mon-Wed series in May, so I can’t be sure that it’s a typical experience.

The fans were a nice mix of enthusiastic and knowledgeable, and the staff was pretty attentive and welcoming as far as those things go. In a basic sense, Camden Yards is a very standard MLB stadium. There isn’t amazing food or really impressive amenities, but from a strict game-viewing perspective, it’s quite something. It’s cozy without being crammed and looks the part of a charming stadium in the heart of an old city.

I’ve been to 8 active MLB parks (Comerica, Wrigley, US Cellular, GABP, Progressive, PNC, Nationals, Camden) and two defunct ones (Tiger Stadium and Sun Life), and I would say that Camden comes out second behind PNC. I always excluded Comerica because I can’t be objective in that case. OPACY is great place to see a game, and even better when your team sweeps the O’s.

Stadium Rater (scale 1-10): 9 

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Wins Above Replacement (WAR) Calculator

Clip art illustration of a Cartoon Tiger with a Missing Tooth

One of the missions of New English D is to make sabermetrics more easily digestible. To that end, we have an extensive Stat Primer series that explains a lot of important concepts and stats. One of the most controversial, but important stats out there is Wins Above Replacement (WAR). I wrote about WAR over a year ago here, so feel free to read that as a primer for what WAR is trying to measure. I also apologize if it’s not perfectly written, as it was one of the first pieces I put out there and was still working to develop some expert internet-writing skills.

Calculate FIP, xFIP, and wOBA too!

That said, people often complain that WAR is really too complicated and it doesn’t make sense to them. Well, I’m going to give you the tools to calculate WAR right here and right now. I will make two quick points.

  1. This is an approximation of the FanGraphs version of WAR for position players, not pitchers.
  2. This is not perfect, mostly in the sense that it does not account for park factors. If your fake player plays in a hitter friendly park, this number will be too high. If they play in a pitcher friendly park, it will be too low. Not a huge amount, but some. This calculator isn’t perfect because in order for it to be perfect, I would have to ask you to input way more information and I would have to learn how to be a much better coder.
  3. This doesn’t account for league, which makes a small difference and it doesn’t break down by number of games played at different positions if your player plays more than one.

Here is how it works. Fill in the data from Cell B2 to Cell B11 with the basic statistics of your player. In Cell B17, type the number that corresponds with their position in the “H” column. In Cell B18, type the number of runs above or below average you player is on defense. A perfectly average defender at the position in question will be zero. Remember these are run values and generally range from -10 to +10. Do the same thing with baserunning runs in Cell B19. If you want more information on any of these numbers, visit our Stat Primer page for details.

If you’ve done everything correctly, you should have a WAR value in B20. Remember, this doesn’t adjust for park or league, so it won’t be perfect, but it should give you a pretty nice idea if you’re just looking to play around with some numbers. Essentially, this is a “what if WAR machine.”

Right now, these numbers reflect the 2013 regular season. Feel free to play around with the numbers in the blue box if you wish to calculate based on different seasons. All of the numbers can be found on this FG page with the exception of Lg R and Lg PA, which are simply the total number of runs and plate appearances in the league that season.

Enjoy and feel free to post if you catch any mistakes. This one was much harder to write than FIP, xFIP, and wOBA.

SOEFA Sunday: Reliever Rankings Update (September 29, 2013)

Clip art illustration of a Cartoon Tiger with a Missing Tooth

You’ll recall earlier this year we introduced our very own reliever rankings called SOEFA, which you can read about in detail here. For a brief refresher, it combines inherited runner strand rate, expected OBP against, ERA-, and FIP- into a deviation from league average. This is a measure of performance, not necessarily ability, and seeks to provide a single number to judge relievers that balances context neutral and context dependent numbers. Certain pitchers, such as Craig Kimbrel, cannot be credited for stranding runners because they are never put into those situations. They are not penalized either, however. Additionally, SOEFA penalizes pitchers like Joe Nathan and Mariano Rivera who have done a very poor job when they have been asked to strand runners this season despite great numbers in other categories.

Zero is average, and will generally range between -2.5 to 2.5 with -1 to 1 being most common. This includes all pitchers who have thrown at least 20 IP in relief as of this morning, so the average score on this list is closer to 0.08 and the inherited runner threshold has been increased from 5 to 8. SOEFA is a rate stat not a counting stat. Should you wish to know the SOEFA for any other reliever, or on a day that isn’t Sunday, hit us on Twitter or in the comments section. Also, as we look to improve SOEFA for next season, let us know if you have any suggestions! Hope you enjoyed this project and look for some analysis of its success this offseason.

Rank Name Team SOEFA
1 Sergio Santos Blue Jays 1.09
2 Koji Uehara Red Sox 0.97
3 Neal Cotts Rangers 0.95
4 Greg Holland Royals 0.93
5 Kenley Jansen Dodgers 0.92
6 Drew Smyly Tigers 0.82
7 Louis Coleman Royals 0.82
8 Kevin Siegrist Cardinals 0.80
9 Nick Vincent Padres 0.80
10 Jesse Crain White Sox 0.78
11 Mark Melancon Pirates 0.77
12 Craig Kimbrel Braves 0.76
13 Javier Lopez Giants 0.73
14 Joaquin Benoit Tigers 0.71
15 Sean Doolittle Athletics 0.68
16 Chris Withrow Dodgers 0.67
17 Luke Hochevar Royals 0.67
18 Trevor Rosenthal Cardinals 0.62
19 Jose Veras – – – 0.60
20 Jason Grilli Pirates 0.58
21 Alex Torres Rays 0.57
22 Casey Janssen Blue Jays 0.57
23 Sam LeCure Reds 0.57
24 Tanner Roark Nationals 0.57
25 Carlos Torres Mets 0.56
26 Glen Perkins Twins 0.55
27 Jake Diekman Phillies 0.55
28 Tommy Hunter Orioles 0.54
29 Will Smith Royals 0.53
30 Jim Henderson Brewers 0.52
31 Randy Choate Cardinals 0.52
32 Dan Otero Athletics 0.51
33 Carlos Villanueva Cubs 0.50
34 Casey Fien Twins 0.50
35 Antonio Bastardo Phillies 0.49
36 Brian Matusz Orioles 0.49
37 Juan Perez Blue Jays 0.49
38 Alex Wood Braves 0.48
39 Josh Collmenter Diamondbacks 0.48
40 Seth Maness Cardinals 0.48
41 Brett Cecil Blue Jays 0.47
42 Chad Qualls Marlins 0.47
43 Jordan Walden Braves 0.47
44 Kevin Gausman Orioles 0.47
45 Tanner Scheppers Rangers 0.47
46 Andrew Miller Red Sox 0.46
47 Brandon Kintzler Brewers 0.46
48 Paco Rodriguez Dodgers 0.46
49 Manny Parra Reds 0.45
50 Mariano Rivera Yankees 0.45
51 Bobby Parnell Mets 0.44
52 Edward Mujica Cardinals 0.44
53 J.P. Howell Dodgers 0.43
54 Jason Frasor Rangers 0.43
55 Joe Thatcher – – – 0.43
56 Steve Cishek Marlins 0.43
57 David Carpenter Braves 0.42
58 Matt Reynolds Diamondbacks 0.42
59 Ernesto Frieri Angels 0.40
60 Jean Machi Giants 0.40
61 Tony Watson Pirates 0.40
62 Sergio Romo Giants 0.39
63 Shawn Kelley Yankees 0.39
64 Aroldis Chapman Reds 0.38
65 Blake Parker Cubs 0.38
66 Luis Avilan Braves 0.38
67 Vin Mazzaro Pirates 0.38
68 Junichi Tazawa Red Sox 0.37
69 Will Harris Diamondbacks 0.36
70 Brad Ziegler Diamondbacks 0.34
71 Jonathan Papelbon Phillies 0.34
72 Luke Gregerson Padres 0.34
73 Robbie Ross Rangers 0.34
74 Joe Smith Indians 0.33
75 Darren O’Day Orioles 0.32
76 Joel Peralta Rays 0.32
77 Ross Ohlendorf Nationals 0.32
78 Caleb Thielbar Twins 0.31
79 Francisco Rodriguez – – – 0.31
80 Jerome Williams Angels 0.31
81 Tom Gorzelanny Brewers 0.31
82 Tyler Clippard Nationals 0.31
83 Kevin Chapman Astros 0.30
84 Matt Belisle Rockies 0.29
85 Cody Allen Indians 0.28
86 Nate Jones White Sox 0.28
87 Craig Breslow Red Sox 0.27
88 Craig Stammen Nationals 0.27
89 David Robertson Yankees 0.27
90 Josh Outman Rockies 0.27
91 Santiago Casilla Giants 0.27
92 Alfredo Simon Reds 0.26
93 David Huff – – – 0.26
94 Aaron Loup Blue Jays 0.25
95 Boone Logan Yankees 0.25
96 Bryan Shaw Indians 0.25
97 Grant Balfour Athletics 0.25
98 Luis Ayala – – – 0.25
99 Jared Burton Twins 0.24
100 Luke Putkonen Tigers 0.24
101 Anthony Varvaro Braves 0.23
102 Fernando Rodney Rays 0.23
103 Rex Brothers Rockies 0.23
104 Chad Gaudin Giants 0.22
105 Danny Farquhar Mariners 0.22
106 Joe Nathan Rangers 0.22
107 Mike Dunn Marlins 0.22
108 Scott Downs – – – 0.22
109 Tim Collins Royals 0.22
110 Addison Reed White Sox 0.21
111 J.J. Putz Diamondbacks 0.21
112 Neil Wagner Blue Jays 0.20
113 Adam Ottavino Rockies 0.18
114 Dan Jennings Marlins 0.18
115 Josh Zeid Astros 0.18
116 Steve Delabar Blue Jays 0.18
117 Dale Thayer Padres 0.17
118 Rafael Betancourt Rockies 0.17
119 Preston Claiborne Yankees 0.16
120 Donovan Hand Brewers 0.15
121 Dustin McGowan Blue Jays 0.15
122 LaTroy Hawkins Mets 0.15
123 Rafael Soriano Nationals 0.15
124 Brad Boxberger Padres 0.14
125 Charlie Furbush Mariners 0.14
126 Jim Johnson Orioles 0.14
127 Justin Wilson Pirates 0.14
128 Bruce Rondon Tigers 0.13
129 Gonzalez Germen Mets 0.13
130 Huston Street Padres 0.12
131 Jamey Wright Rays 0.12
132 Logan Ondrusek Reds 0.12
133 Ryan Webb Marlins 0.12
134 Anthony Swarzak Twins 0.11
135 Scott Rice Mets 0.11
136 Tim Stauffer Padres 0.11
137 Matt Lindstrom White Sox 0.10
138 Burke Badenhop Brewers 0.09
139 Darren Oliver Blue Jays 0.09
140 Oliver Perez Mariners 0.09
141 Wilton Lopez Rockies 0.09
142 Rob Scahill Rockies 0.08
143 Andrew Bailey Red Sox 0.07
144 Jesse Chavez Athletics 0.07
145 Kevin Gregg Cubs 0.07
146 Sandy Rosario Giants 0.07
147 Brian Duensing Twins 0.06
148 Heath Bell Diamondbacks 0.06
149 Jeanmar Gomez Pirates 0.06
150 Alfredo Figaro Brewers 0.05
151 Carlos Martinez Cardinals 0.05
152 Joe Kelly Cardinals 0.05
153 Matt Thornton – – – 0.05
154 Ryan Cook Athletics 0.05
155 Yoervis Medina Mariners 0.05
156 Kelvin Herrera Royals 0.04
157 Tyson Ross Padres 0.03
158 Fernando Abad Nationals 0.02
159 Jerry Blevins Athletics 0.02
160 Dane de la Rosa Angels 0.01
161 David Aardsma Mets 0.01
162 J.J. Hoover Reds 0.01
163 Matt Guerrier – – – 0.01
164 Brett Anderson Athletics 0.00
165 Donnie Veal White Sox 0.00
166 Ross Wolf Rangers 0.00
167 Joe Ortiz Rangers -0.01
168 Josh Edgin Mets -0.01
169 Edgmer Escalona Rockies -0.02
170 J.C. Gutierrez – – – -0.02
171 Manuel Corpas Rockies -0.02
172 Marc Rzepczynski – – – -0.03
173 Pat Neshek Athletics -0.03
174 Cesar Ramos Rays -0.04
175 Kevin Jepsen Angels -0.04
176 James Russell Cubs -0.05
177 Tyler Thornburg Brewers -0.05
178 Aaron Crow Royals -0.06
179 Darin Downs Tigers -0.06
180 Josh Fields Astros -0.06
181 Wesley Wright – – – -0.06
182 Evan Reed Tigers -0.07
183 Ryan Pressly Twins -0.07
184 Carter Capps Mariners -0.08
185 Evan Scribner Athletics -0.08
186 Brandon Workman Red Sox -0.09
187 Jake McGee Rays -0.09
188 Matt Albers Indians -0.09
189 Fernando Salas Cardinals -0.10
190 Michael Kohn Angels -0.10
191 Drew Storen Nationals -0.11
192 Troy Patton Orioles -0.12
193 David Hernandez Diamondbacks -0.13
194 Pedro Strop – – – -0.13
195 A.J. Ramos Marlins -0.14
196 Al Alburquerque Tigers -0.15
197 Bryan Morris Pirates -0.15
198 David Purcey White Sox -0.15
199 Ronald Belisario Dodgers -0.15
200 Adam Warren Yankees -0.16
201 Joakim Soria Rangers -0.16
202 Jake Dunning Giants -0.17
203 Jared Hughes Pirates -0.17
204 Chaz Roe Diamondbacks -0.18
205 Drake Britton Red Sox -0.18
206 Jose Mijares Giants -0.18
207 Cory Gearrin Braves -0.19
208 Raul Valdes Phillies -0.19
209 Zach Duke – – – -0.19
210 Brad Brach Padres -0.20
211 Justin De Fratus Phillies -0.20
212 Ramon Troncoso White Sox -0.22
213 Rob Wooten Brewers -0.23
214 Chris Perez Indians -0.24
215 Jonathan Broxton Reds -0.24
216 Tom Wilhelmsen Mariners -0.24
217 Kyle Farnsworth – – – -0.25
218 Mike Adams Phillies -0.26
219 Philip Humber Astros -0.26
220 Scott Atchison Mets -0.26
221 Blake Beavan Mariners -0.27
222 Rich Hill Indians -0.27
223 Vinnie Pestano Indians -0.27
224 Franklin Morales Red Sox -0.28
225 George Kontos Giants -0.29
226 Lucas Luetge Mariners -0.30
227 Nick Hagadone Indians -0.30
228 Rhiner Cruz Astros -0.30
229 Tony Sipp Diamondbacks -0.30
230 Brad Lincoln Blue Jays -0.31
231 Carlos Marmol – – – -0.31
232 Garrett Richards Angels -0.31
233 Phil Coke Tigers -0.31
234 John Axford – – – -0.32
235 Michael Bowden Cubs -0.33
236 T.J. McFarland Orioles -0.35
237 Ryan Mattheus Nationals -0.36
238 Josh Roenicke Twins -0.37
239 Dylan Axelrod White Sox -0.38
240 Paul Clemens Astros -0.38
241 Guillermo Moscoso Giants -0.39
242 Kameron Loe – – – -0.41
243 Travis Blackley – – – -0.41
244 Clayton Mortensen Red Sox -0.43
245 Esmil Rogers Blue Jays -0.43
246 Josh Lueke Rays -0.44
247 Alex Wilson Red Sox -0.46
248 Brandon Lyon Mets -0.49
249 Michael Gonzalez Brewers -0.50
250 Brandon Maurer Mariners -0.51
251 Greg Burke Mets -0.52
252 Lucas Harrell Astros -0.52
253 Luis Garcia Phillies -0.53
254 Bruce Chen Royals -0.54
255 Hector Rondon Cubs -0.57
256 Jeremy Horst Phillies -0.59
257 Jose Cisnero Astros -0.59
258 Joba Chamberlain Yankees -0.62
259 Dallas Keuchel Astros -0.64
260 Hector Ambriz Astros -0.64
261 Jeremy Affeldt Giants -0.67
262 Cory Rasmus – – – -0.69
263 Ian Krol Nationals -0.69
264 Henry Rodriguez – – – -0.71
265 Michael Kirkman Rangers -0.75
266 Brandon League Dodgers -0.76
267 J.C. Ramirez Phillies -0.90
268 Anthony Bass Padres -0.94
269 Shawn Camp Cubs -1.04
270 Mitchell Boggs – – – -1.37
271 Curtis Partch Reds -1.43

Dynamic Standings Projection (September 26, 2013)

In case you missed it, in April we launched our Dynamic Standings Projection feature on New English D. A full explanation of the methodology can be found here or by clicking the tab at the top of the page. This project seeks to provide a reasoned and cautious approach to updating our beliefs about the baseball future. You can find a summarization of the original projections here. You’ll notice a column on the far right that indicates the difference in projected wins from the preseason prediction. Positive numbers mean teams are now projected to win more games and negative numbers mean a team is now projected to win fewer games. You’ll notice a series of graphs below the standings section that track how the projections have evolved over the course of the year.

This Dynamic Standings Projection is updated through the September 25th games. Note that DSP posts have been moved to Thursday accommodate something that won’t interest you. 

26-Sep W L   PreDiff
BOS 97 65 0.599 20
TB 91 71 0.562 0
NYY 84 78 0.519 -1
BAL 84 78 0.519 2
TOR 74 88 0.457 -13
W L   PreDiff
DET 95 67 0.586 1
CLE 90 72 0.556 19
KC 85 77 0.525 9
MIN 66 96 0.407 1
CWS 64 98 0.395 -19
W L   PreDiff
OAK 96 66 0.593 12
TEX 89 73 0.549 -2
LAA 80 82 0.494 -8
SEA 71 91 0.438 -4
HOU 52 110 0.321 -8
W L   PreDiff
ATL 95 67 0.586 5
WSH 86 76 0.531 -9
NYM 75 87 0.463 -3
PHI 74 88 0.457 -10
MIA 60 102 0.370 -3
W L   PreDiff
STL 96 66 0.593 8
PIT 93 69 0.574 11
CIN 92 70 0.568 0
MIL 73 89 0.451 -6
CHC 67 95 0.414 -1
W L   PreDiff
LAD 93 69 0.574 5
ARZ 82 80 0.506 0
SD 76 86 0.469 -2
SF 75 87 0.463 -16
COL 73 89 0.451 10

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SOEFA Sunday: Reliever Rankings Update (September 22, 2013)

Clip art illustration of a Cartoon Tiger with a Missing Tooth

You’ll recall earlier this year we introduced our very own reliever rankings called SOEFA, which you can read about in detail here. For a brief refresher, it combines inherited runner strand rate, expected OBP against, ERA-, and FIP- into a deviation from league average. This is a measure of performance, not necessarily ability, and seeks to provide a single number to judge relievers that balances context neutral and context dependent numbers. Certain pitchers, such as Craig Kimbrel, cannot be credited for stranding runners because they are never put into those situations. They are not penalized either, however. Additionally, SOEFA penalizes pitchers like Joe Nathan and Mariano Rivera who have done a very poor job when they have been asked to strand runners this season despite great numbers in other categories.

Zero is average, and will generally range between -2.5 to 2.5 with -1 to 1 being most common. This includes all pitchers who have thrown at least 20 IP in relief as of this morning, so the average score on this list is closer to 0.09 and the inherited runner threshold has been increased from 5 to 8. SOEFA is a rate stat not a counting stat. Should you wish to know the SOEFA for any other reliever, or on a day that isn’t Sunday, hit us on Twitter or in the comments section. Also, as we look to improve SOEFA for next season, let us know if you have any suggestions!

Rank Player Team SOEFA
1 Sergio Santos Blue Jays 1.03
2 Koji Uehara Red Sox 0.97
3 Greg Holland Royals 0.94
4 Neal Cotts Rangers 0.94
5 Kenley Jansen Dodgers 0.89
6 Louis Coleman Royals 0.89
7 Kevin Siegrist Cardinals 0.80
8 Drew Smyly Tigers 0.79
9 Javier Lopez Giants 0.79
10 Will Smith Royals 0.78
11 Jesse Crain White Sox 0.78
12 Mark Melancon Pirates 0.78
13 Luke Hochevar Royals 0.72
14 Joaquin Benoit Tigers 0.72
15 Craig Kimbrel Braves 0.70
16 Nick Vincent Padres 0.68
17 Sean Doolittle Athletics 0.67
18 Chris Withrow Dodgers 0.66
19 Jose Veras – – – 0.62
20 Brian Matusz Orioles 0.59
21 Jason Grilli Pirates 0.59
22 Tommy Hunter Orioles 0.58
23 Tanner Roark Nationals 0.57
24 Trevor Rosenthal Cardinals 0.57
25 Jake Diekman Phillies 0.57
26 David Huff – – – 0.57
27 Glen Perkins Twins 0.56
28 Sam LeCure Reds 0.56
29 Casey Janssen Blue Jays 0.56
30 Carlos Torres Mets 0.56
31 Casey Fien Twins 0.55
32 Josh Collmenter Diamondbacks 0.54
33 Jim Henderson Brewers 0.53
34 Alex Torres Rays 0.52
35 Edward Mujica Cardinals 0.51
36 Randy Choate Cardinals 0.51
37 Antonio Bastardo Phillies 0.50
38 Paco Rodriguez Dodgers 0.49
39 Dan Otero Athletics 0.49
40 Juan Perez Blue Jays 0.49
41 Jordan Walden Braves 0.48
42 Brett Cecil Blue Jays 0.47
43 Andrew Miller Red Sox 0.47
44 Seth Maness Cardinals 0.47
45 Chad Qualls Marlins 0.45
46 Bobby Parnell Mets 0.44
47 Kevin Gausman Orioles 0.44
48 Shawn Kelley Yankees 0.43
49 Matt Reynolds Diamondbacks 0.42
50 Brandon Kintzler Brewers 0.41
51 Joe Thatcher – – – 0.41
52 J.P. Howell Dodgers 0.40
53 Vin Mazzaro Pirates 0.40
54 Jonathan Papelbon Phillies 0.40
55 Tanner Scheppers Rangers 0.40
56 Carlos Villanueva Cubs 0.40
57 Jason Frasor Rangers 0.39
58 David Carpenter Braves 0.39
59 Tony Watson Pirates 0.39
60 Manny Parra Reds 0.39
61 Junichi Tazawa Red Sox 0.39
62 Steve Cishek Marlins 0.38
63 Brad Ziegler Diamondbacks 0.38
64 Ernesto Frieri Angels 0.38
65 Darren O’Day Orioles 0.37
66 Donovan Hand Brewers 0.37
67 Luis Avilan Braves 0.37
68 Sergio Romo Giants 0.36
69 Aroldis Chapman Reds 0.35
70 Francisco Rodriguez – – – 0.35
71 Robbie Ross Rangers 0.33
72 Blake Parker Cubs 0.33
73 Ross Ohlendorf Nationals 0.32
74 Will Harris Diamondbacks 0.32
75 Josh Outman Rockies 0.32
76 Jean Machi Giants 0.32
77 Luke Gregerson Padres 0.32
78 David Robertson Yankees 0.32
79 Mariano Rivera Yankees 0.31
80 Tom Gorzelanny Brewers 0.31
81 Jerome Williams Angels 0.31
82 Joel Peralta Rays 0.31
83 Tim Collins Royals 0.30
84 Tyler Clippard Nationals 0.30
85 Aaron Loup Blue Jays 0.30
86 Joe Smith Indians 0.29
87 Dan Jennings Marlins 0.28
88 Craig Stammen Nationals 0.28
89 Anthony Varvaro Braves 0.27
90 Scott Downs – – – 0.27
91 Luis Ayala – – – 0.27
92 Craig Breslow Red Sox 0.26
93 Matt Belisle Rockies 0.26
94 Addison Reed White Sox 0.26
95 Nate Jones White Sox 0.26
96 Cody Allen Indians 0.26
97 Jamey Wright Rays 0.25
98 Luke Putkonen Tigers 0.25
99 Fernando Rodney Rays 0.24
100 Grant Balfour Athletics 0.24
101 Santiago Casilla Giants 0.23
102 Alfredo Simon Reds 0.23
103 Boone Logan Yankees 0.23
104 Jared Burton Twins 0.22
105 Chad Gaudin Giants 0.22
106 Mike Dunn Marlins 0.21
107 Neil Wagner Blue Jays 0.20
108 Joakim Soria Rangers 0.20
109 Charlie Furbush Mariners 0.20
110 Caleb Thielbar Twins 0.20
111 Rex Brothers Rockies 0.20
112 Rob Scahill Rockies 0.19
113 Danny Farquhar Mariners 0.19
114 Preston Claiborne Yankees 0.19
115 Bryan Shaw Indians 0.18
116 J.C. Gutierrez – – – 0.18
117 Rafael Betancourt Rockies 0.17
118 Dale Thayer Padres 0.16
119 Steve Delabar Blue Jays 0.16
120 J.J. Putz Diamondbacks 0.14
121 Rafael Soriano Nationals 0.13
122 Matt Lindstrom White Sox 0.13
123 Justin Wilson Pirates 0.13
124 LaTroy Hawkins Mets 0.12
125 Brandon Workman Red Sox 0.12
126 Oliver Perez Mariners 0.12
127 Tim Stauffer Padres 0.12
128 Ryan Webb Marlins 0.11
129 Adam Ottavino Rockies 0.11
130 Scott Rice Mets 0.11
131 Anthony Swarzak Twins 0.11
132 Wilton Lopez Rockies 0.11
133 Jim Johnson Orioles 0.09
134 Darren Oliver Blue Jays 0.09
135 Heath Bell Diamondbacks 0.09
136 Brian Duensing Twins 0.09
137 Jesse Chavez Athletics 0.08
138 Joe Nathan Rangers 0.08
139 Gonzalez Germen Mets 0.08
140 Andrew Bailey Red Sox 0.08
141 Jeanmar Gomez Pirates 0.08
142 Sandy Rosario Giants 0.07
143 Bruce Rondon Tigers 0.06
144 Fernando Abad Nationals 0.06
145 Burke Badenhop Brewers 0.06
146 Joe Kelly Cardinals 0.06
147 Kevin Gregg Cubs 0.05
148 Yoervis Medina Mariners 0.05
149 Huston Street Padres 0.05
150 Tyson Ross Padres 0.04
151 Logan Ondrusek Reds 0.04
152 Matt Thornton – – – 0.03
153 Dustin McGowan Blue Jays 0.03
154 Kelvin Herrera Royals 0.02
155 Matt Guerrier – – – 0.01
156 Alfredo Figaro Brewers 0.01
157 Ryan Cook Athletics 0.01
158 Brad Boxberger Padres 0.01
159 David Aardsma Mets 0.01
160 Ross Wolf Rangers 0.00
161 J.J. Hoover Reds -0.01
162 Josh Edgin Mets -0.01
163 Dane de la Rosa Angels -0.01
164 Joe Ortiz Rangers -0.01
165 Jerry Blevins Athletics -0.01
166 Edgmer Escalona Rockies -0.02
167 Josh Zeid Astros -0.03
168 Marc Rzepczynski – – – -0.03
169 Kevin Jepsen Angels -0.03
170 Manuel Corpas Rockies -0.03
171 Tyler Thornburg Brewers -0.05
172 Evan Scribner Athletics -0.05
173 Tom Wilhelmsen Mariners -0.05
174 Chris Perez Indians -0.05
175 Donnie Veal White Sox -0.05
176 Pat Neshek Athletics -0.06
177 Michael Kohn Angels -0.07
178 James Russell Cubs -0.07
179 Carter Capps Mariners -0.08
180 Carlos Martinez Cardinals -0.09
181 Jared Hughes Pirates -0.10
182 Fernando Salas Cardinals -0.10
183 Darin Downs Tigers -0.10
184 Aaron Crow Royals -0.11
185 Jake McGee Rays -0.11
186 Drake Britton Red Sox -0.12
187 Wesley Wright – – – -0.12
188 Cesar Ramos Rays -0.13
189 Matt Albers Indians -0.13
190 Troy Patton Orioles -0.14
191 Ryan Pressly Twins -0.14
192 Jake Dunning Giants -0.14
193 Pedro Strop – – – -0.15
194 Ronald Belisario Dodgers -0.15
195 A.J. Ramos Marlins -0.15
196 Brad Brach Padres -0.15
197 David Purcey White Sox -0.15
198 Drew Storen Nationals -0.17
199 Josh Fields Astros -0.17
200 Bryan Morris Pirates -0.17
201 David Hernandez Diamondbacks -0.17
202 Raul Valdes Phillies -0.19
203 Cory Gearrin Braves -0.19
204 Adam Warren Yankees -0.19
205 Scott Atchison Mets -0.20
206 Jose Mijares Giants -0.21
207 Lucas Luetge Mariners -0.21
208 Jonathan Broxton Reds -0.24
209 Rich Hill Indians -0.24
210 Justin De Fratus Phillies -0.24
211 Ramon Troncoso White Sox -0.25
212 Mike Adams Phillies -0.26
213 Tony Sipp Diamondbacks -0.26
214 Kyle Farnsworth – – – -0.26
215 Blake Beavan Mariners -0.27
216 Vinnie Pestano Indians -0.27
217 Al Alburquerque Tigers -0.28
218 Rob Wooten Brewers -0.28
219 Josh Roenicke Twins -0.30
220 Nick Hagadone Indians -0.30
221 Garrett Richards Angels -0.31
222 Brad Lincoln Blue Jays -0.31
223 Phil Coke Tigers -0.32
224 Michael Bowden Cubs -0.33
225 T.J. McFarland Orioles -0.33
226 Ryan Mattheus Nationals -0.33
227 Carlos Marmol – – – -0.34
228 George Kontos Giants -0.34
229 Zach Duke – – – -0.35
230 John Axford – – – -0.36
231 Paul Clemens Astros -0.37
232 Dylan Axelrod White Sox -0.38
233 Guillermo Moscoso Giants -0.38
234 Travis Blackley – – – -0.41
235 Clayton Mortensen Red Sox -0.42
236 Esmil Rogers Blue Jays -0.43
237 Alex Wilson Red Sox -0.45
238 Brandon Lyon Mets -0.49
239 Greg Burke Mets -0.49
240 Brandon Maurer Mariners -0.51
241 Michael Gonzalez Brewers -0.51
242 Joba Chamberlain Yankees -0.52
243 Lucas Harrell Astros -0.52
244 Josh Lueke Rays -0.53
245 Bruce Chen Royals -0.54
246 Jose Cisnero Astros -0.58
247 Jeremy Horst Phillies -0.59
248 Hector Ambriz Astros -0.63
249 Hector Rondon Cubs -0.63
250 Dallas Keuchel Astros -0.64
251 Luis Garcia Phillies -0.66
252 Jeremy Affeldt Giants -0.67
253 Ian Krol Nationals -0.69
254 Cory Rasmus – – – -0.69
255 Henry Rodriguez – – – -0.70
256 Michael Kirkman Rangers -0.75
257 Brandon League Dodgers -0.85
258 Anthony Bass Padres -0.93
259 Shawn Camp Cubs -1.03
260 Mitchell Boggs – – – -1.40
261 Curtis Partch Reds -1.42

The Nine Worst Sacrifice Bunts of 2013

Clip art illustration of a Cartoon Tiger with a Missing Tooth

So now that we have sufficiently killed the win, bunting seems to be the topic of the day. Last week there were many examples of managers employing the sacrifice bunt at silly times and it seemed to set off a fervor among those wishing to debate new ideas and old tradition. I got into some debates with followers – and you all know Brian Kenny did the same.

The basic argument against the sacrifice bunt is that giving up and out to gain a base is a bad percentage play. The facts are pretty clear on the matter. You have to consider who is batting and the exact situation of the game, but it’s usually always a bad idea to bunt with a reasonably competent position player. Below I’ve presented The Nine Worst Sacrifice Bunt Attempts of 2013. This requires some definition, but first I want to lay out the basic argument for when bunting might be a good idea because some often taking anti-bunting comments as absolute:

When To Bunt

  1. When a pitcher is batting OR
  2. When a very low quality hitter is up AND
  3. There are zero outs AND
  4. There are men on first and second AND
  5. The batter has a high probability of striking out based on his skills or the opposing pitcher AND
  6. One run is sufficient (i.e., you’re down one run late or tied)

The Odds Against Bunting

Here’s my post from earlier this year that outlines Run Expectancy. If you don’t like the way I explain it, just Google it. Lots of smart people have explained it.

The Rules

So the following are The Nine Worst Bunt Attempts of the year as defined like this. First, these are all bunts that have been put in play. I can’t examine the times a batter failed to get a bunt down and then the bunt sign was taken off. Second, this does not include bunts that went for hits. Bunting for a hit is great, this is about bunts in which an out was made – which is the goal of a bunt. Get on base and we don’t have a problem. Third, this is judged by Win Probability Added (WPA), which considers the game situation and the result of the play. So, if you call a bunt in a 10-0 game, who cares. If you call for a bunt in a 5-3 game with your two hitter, that’s probably silly. Finally, no pitchers. Pitchers can’t hit, so it’s fine to use them to bunt. Let’s see what happens!

There have been 1,192 sacrifice bunt attempts this season by non-pitchers. 174 have gone for hits and 39 have been turned into errors, so that’s 979 bunt attempts that resulted in at least one out. In sum, they have been worth -2.7 WPA. Here are the worst.

Let’s start with some data that sets the stage.

Rank Date Batter Tm
9 9/16/2013 Juan Uribe LAD
8 8/14/2013 Alberto Callaspo OAK
7 8/14/2013 Martin Prado ARI
6 8/10/2013 Stephen Vogt OAK
5 9/9/2013 Jonathan Herrera COL
4 9/18/2013 Munenori Kawasaki TOR
3 4/25/2013 Juan Pierre MIA
2 4/11/2013 Brendan Ryan SEA
1 4/9/2013 Rob Brantly MIA

There we have the date and hitters. Now the opponent and situation:

Rank Opp Pitcher Score Inn RoB Out
9 @ARI Brad Ziegler down 2-1 t9 -12 0
8 HOU Josh Fields down 2-1 b11 -2- 0
7 BAL Jim Johnson down 4-3 b9 -2- 0
6 @TOR Casey Janssen down 5-4 t9 -12 0
5 @SFG Javier Lopez tied 2-2 t10 1– 0
4 NYY Mariano Rivera down 4-3 b9 -12 0
3 CHC Carlos Marmol down 4-3 b9 -12 0
2 TEX Robbie Ross down 4-3 b8 3 1
1 ATL Craig Kimbrel down 3-2 b9 1– 0

All but one feature no outs and the hitting team has been trailing late or tied in each.

Rank Batter WPA RE24 LI Play Description
9 Juan Uribe -0.16 -0.56 5.6 Bunt Groundout: P-3B/Forceout at 3B (Front of Home); Schumaker to 2B
8 Alberto Callaspo -0.16 -0.42 4.38 Bunt Popfly: P (Front of Home)
7 Martin Prado -0.16 -0.42 4.38 Bunt Groundout: P-1B (Front of Home)
6 Stephen Vogt -0.16 -0.58 5.48 Bunt Groundout: P-3B/Forceout at 3B (Front of Home); Crisp to 2B
5 Jonathan Herrera -0.17 -0.68 3.51 Bunt Ground Ball Double Play: Bunt C-SS-2B (Front of Home)
4 Munenori Kawasaki -0.18 -0.58 6.13 Bunt Groundout: 1B-3B/Forceout at 3B (Front of Home); Rasmus to 2B
3 Juan Pierre -0.18 -0.56 6.21 Bunt Groundout: C-3B/Forceout at 3B (Front of Home); Kearns to 2B
2 Brendan Ryan -0.22 -0.69 4.33 Fielder’s Choice P; Chavez out at Hm/P-C; Ryan to 1B
1 Rob Brantly -0.28 -0.74 5.4 Bunt Pop Fly Double Play: Bunt 3B (Short 3B Line); Solano out at 1B/3B-1B

Alright, so a few notes. The very worst bunts are almost always the ones that include double plays or a runner getting thrown out at home somehow. Which makes sense, any time a bunt goes horribly wrong, it’s going to be more costly than a normal bunt. Martin Prado’s at #7 is the worst true sac bunt of the lot because the runner didn’t advance and Prado made an out.

So it’s perfectly reasonable to say these are poorly executed bunts. That’s true. But it’s not interesting to show you 9 very similar bunts that are all in the -4% range in the same situations. There are just so many of them. But, let me provide some summary stats to give you a better idea about the whole dataset. Of the 979 bunts that didn’t result in a hit or error, 722 resulted in a decrease in WPA, 160 resulted in no change, and 97 increased the team’s odds of winning. In other words, only 26% of sac bunts in the sample are good for the team.

So 18% of the time a batter attempts to sac bunt, he gets a hit or induces and error. That’s good. And 26% of the remaining 82% helps anyway.  All told, about one quarter of position player bunts turn out to be a good idea based on WPA. Let’s go further.

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Even including all of the bunts that ended in hits and errors, 276 resulted in more than one run, 339 resulted in one run exactly, and 577 resulted in zero runs. There are good bunts, but bunting is usually a bad idea. There are bunts that mess up the defense and open the door, but they are rare. Usually when you bunt, you don’t score.

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You’re welcome to keep bunting, but the odds are not in your favor.

Dynamic Standings Projection (September 19, 2013)

In case you missed it, in April we launched our Dynamic Standings Projection feature on New English D. A full explanation of the methodology can be found here or by clicking the tab at the top of the page. This project seeks to provide a reasoned and cautious approach to updating our beliefs about the baseball future. You can find a summarization of the original projections here. You’ll notice a column on the far right that indicates the difference in projected wins from the preseason prediction. Positive numbers mean teams are now projected to win more games and negative numbers mean a team is now projected to win fewer games. You’ll notice a series of graphs below the standings section that track how the projections have evolved over the course of the year.

This Dynamic Standings Projection is updated through the September 18th games. Note that DSP posts have been moved to Thursday accommodate something that won’t interest you. 

19-Sep W L   PreDiff
BOS 96 66 0.593 19
TB 89 73 0.549 -2
BAL 87 75 0.537 5
NYY 85 77 0.525 0
TOR 75 87 0.463 -12
W L   PreDiff
DET 94 68 0.580 0
CLE 86 76 0.531 15
KC 85 77 0.525 9
MIN 69 93 0.426 4
CWS 65 97 0.401 -18
W L   PreDiff
OAK 94 68 0.580 10
TEX 88 74 0.543 -3
LAA 79 83 0.488 -9
SEA 72 90 0.444 -3
HOU 55 107 0.340 -5
W L   PreDiff
ATL 96 66 0.593 6
WSH 87 75 0.537 -8
PHI 76 86 0.469 -8
NYM 73 89 0.451 -5
MIA 60 102 0.370 -3
W L   PreDiff
STL 94 68 0.580 6
CIN 92 70 0.568 0
PIT 92 70 0.568 10
MIL 73 89 0.451 -6
CHC 67 95 0.414 -1
W L   PreDiff
LAD 92 70 0.568 4
ARZ 83 79 0.512 1
SF 76 86 0.469 -15
SD 76 86 0.469 -2
COL 73 89 0.451 10

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SOEFA Sunday: Reliever Rankings Update (September 15, 2013)

Clip art illustration of a Cartoon Tiger with a Missing Tooth

You’ll recall earlier this year we introduced our very own reliever rankings called SOEFA, which you can read about in detail here. For a brief refresher, it combines inherited runner strand rate, expected OBP against, ERA-, and FIP- into a deviation from league average. This is a measure of performance, not necessarily ability, and seeks to provide a single number to judge relievers that balances context neutral and context dependent numbers. Certain pitchers, such as Craig Kimbrel, cannot be credited for stranding runners because they are never put into those situations. They are not penalized either, however. Additionally, SOEFA penalizes pitchers like Joe Nathan and Mariano Rivera who have done a very poor job when they have been asked to strand runners this season despite great numbers in other categories.

Zero is average, and will generally range between -2.5 to 2.5 with -1 to 1 being most common. This includes all pitchers who have thrown at least 20 IP in relief as of this morning, so the average score on this list is closer to 0.10 and the inherited runner threshold has been increased from 5 to 8. SOEFA is a rate stat not a counting stat. Should you wish to know the SOEFA for any other reliever, or on a day that isn’t Sunday, hit us on Twitter or in the comments section. Also, as we look to improve SOEFA for next season, let us know if you have any suggestions!

Rank Player Team SOEFA
1 Koji Uehara Red Sox 0.95
2 Greg Holland Royals 0.94
3 Kenley Jansen Dodgers 0.91
4 Neal Cotts Rangers 0.89
5 Kevin Siegrist Cardinals 0.80
6 Mark Melancon Pirates 0.80
7 Drew Smyly Tigers 0.78
8 Jesse Crain White Sox 0.78
9 Craig Kimbrel Braves 0.77
10 Javier Lopez Giants 0.77
11 Will Smith Royals 0.76
12 Louis Coleman Royals 0.73
13 Luke Hochevar Royals 0.73
14 Joaquin Benoit Tigers 0.70
15 Sergio Romo Giants 0.70
16 Chris Withrow Dodgers 0.66
17 Alex Torres Rays 0.65
18 Nick Vincent Padres 0.64
19 Sean Doolittle Athletics 0.63
20 Sam LeCure Reds 0.62
21 Edward Mujica Cardinals 0.61
22 Jose Veras – – – 0.61
23 Jordan Walden Braves 0.59
24 Trevor Rosenthal Cardinals 0.59
25 Tanner Roark Nationals 0.57
26 Jason Grilli Pirates 0.56
27 David Huff – – – 0.54
28 Glen Perkins Twins 0.54
29 Jim Henderson Brewers 0.54
30 Paco Rodriguez Dodgers 0.54
31 Brian Matusz Orioles 0.53
32 Casey Fien Twins 0.52
33 Carlos Torres Mets 0.51
34 Jake Diekman Phillies 0.51
35 Tommy Hunter Orioles 0.51
36 Antonio Bastardo Phillies 0.50
37 Dan Otero Athletics 0.50
38 Juan Perez Blue Jays 0.50
39 Josh Collmenter Diamondbacks 0.48
40 Shawn Kelley Yankees 0.48
41 Andrew Miller Red Sox 0.47
42 Brett Cecil Blue Jays 0.47
43 Jason Frasor Rangers 0.47
44 Manny Parra Reds 0.47
45 Randy Choate Cardinals 0.46
46 Brandon Kintzler Brewers 0.45
47 Bobby Parnell Mets 0.44
48 Seth Maness Cardinals 0.43
49 Chad Qualls Marlins 0.42
50 J.P. Howell Dodgers 0.42
51 Junichi Tazawa Red Sox 0.42
52 Matt Reynolds Diamondbacks 0.42
53 Jonathan Papelbon Phillies 0.41
54 Luis Avilan Braves 0.41
55 Francisco Rodriguez – – – 0.40
56 Joel Peralta Rays 0.40
57 Brad Ziegler Diamondbacks 0.39
58 Steve Cishek Marlins 0.39
59 Tanner Scheppers Rangers 0.39
60 Aroldis Chapman Reds 0.38
61 Donovan Hand Brewers 0.38
62 Joe Thatcher – – – 0.38
63 Vin Mazzaro Pirates 0.38
64 David Carpenter Braves 0.37
65 Rob Scahill Rockies 0.37
66 Tony Watson Pirates 0.37
67 Tyler Clippard Nationals 0.37
68 Darren O’Day Orioles 0.36
69 Casey Janssen Blue Jays 0.35
70 Will Harris Diamondbacks 0.35
71 Ernesto Frieri Angels 0.34
72 Joe Smith Indians 0.34
73 Scott Downs – – – 0.34
74 Addison Reed White Sox 0.32
75 Carlos Villanueva Cubs 0.32
76 Jean Machi Giants 0.32
77 Josh Outman Rockies 0.32
78 Nate Jones White Sox 0.32
79 Ross Ohlendorf Nationals 0.32
80 Jerome Williams Angels 0.31
81 Tom Gorzelanny Brewers 0.31
82 Luke Gregerson Padres 0.30
83 Neil Wagner Blue Jays 0.30
84 Santiago Casilla Giants 0.30
85 Aaron Loup Blue Jays 0.29
86 Robbie Ross Rangers 0.29
87 Grant Balfour Athletics 0.27
88 Jamey Wright Rays 0.27
89 Luke Putkonen Tigers 0.27
90 Steve Delabar Blue Jays 0.27
91 Tim Collins Royals 0.27
92 Anthony Varvaro Braves 0.26
93 Caleb Thielbar Twins 0.26
94 Craig Stammen Nationals 0.26
95 Jared Burton Twins 0.25
96 David Robertson Yankees 0.24
97 Luis Ayala – – – 0.24
98 Mariano Rivera Yankees 0.24
99 Boone Logan Yankees 0.23
100 Matt Belisle Rockies 0.23
101 Chad Gaudin Giants 0.22
102 Charlie Furbush Mariners 0.22
103 Craig Breslow Red Sox 0.22
104 Dan Jennings Marlins 0.22
105 Alfredo Simon Reds 0.20
106 Blake Parker Cubs 0.20
107 Fernando Rodney Rays 0.20
108 Mike Dunn Marlins 0.20
109 Cody Allen Indians 0.19
110 Danny Farquhar Mariners 0.19
111 David Purcey White Sox 0.19
112 Preston Claiborne Yankees 0.19
113 Rafael Betancourt Rockies 0.17
114 Anthony Swarzak Twins 0.16
115 Dale Thayer Padres 0.16
116 J.C. Gutierrez – – – 0.16
117 Rex Brothers Rockies 0.16
118 J.J. Putz Diamondbacks 0.15
119 Tim Stauffer Padres 0.15
120 Rafael Soriano Nationals 0.14
121 Carter Capps Mariners 0.13
122 Kevin Gregg Cubs 0.12
123 Sandy Rosario Giants 0.12
124 Alfredo Figaro Brewers 0.11
125 Matt Lindstrom White Sox 0.11
126 Scott Rice Mets 0.11
127 Bryan Shaw Indians 0.10
128 Justin Wilson Pirates 0.10
129 LaTroy Hawkins Mets 0.10
130 Oliver Perez Mariners 0.10
131 Adam Ottavino Rockies 0.09
132 Ryan Cook Athletics 0.09
133 Andrew Bailey Red Sox 0.08
134 Brian Duensing Twins 0.08
135 Brandon Workman Red Sox 0.07
136 Bruce Rondon Tigers 0.07
137 Joe Nathan Rangers 0.07
138 Matt Thornton – – – 0.07
139 Ryan Webb Marlins 0.07
140 Wilton Lopez Rockies 0.07
141 Fernando Abad Nationals 0.06
142 Heath Bell Diamondbacks 0.06
143 J.J. Hoover Reds 0.06
144 Jesse Chavez Athletics 0.06
145 Joe Kelly Cardinals 0.06
146 Kelvin Herrera Royals 0.06
147 Burke Badenhop Brewers 0.05
148 Gonzalez Germen Mets 0.05
149 Jim Johnson Orioles 0.05
150 Yoervis Medina Mariners 0.05
151 Darren Oliver Blue Jays 0.04
152 Jeanmar Gomez Pirates 0.04
153 Tyson Ross Padres 0.04
154 Dane de la Rosa Angels 0.02
155 Matt Guerrier – – – 0.01
156 Michael Kohn Angels 0.01
157 Ross Wolf Rangers 0.00
158 Josh Edgin Mets -0.01
159 Ronald Belisario Dodgers -0.01
160 Edgmer Escalona Rockies -0.02
161 Huston Street Padres -0.02
162 Manuel Corpas Rockies -0.02
163 Kevin Jepsen Angels -0.03
164 Jerry Blevins Athletics -0.04
165 Pat Neshek Athletics -0.04
166 Ryan Pressly Twins -0.04
167 Jake McGee Rays -0.05
168 Tyler Thornburg Brewers -0.05
169 Dustin McGowan Blue Jays -0.06
170 Logan Ondrusek Reds -0.06
171 James Russell Cubs -0.07
172 Chris Perez Indians -0.08
173 David Aardsma Mets -0.08
174 Rob Wooten Brewers -0.09
175 Tom Wilhelmsen Mariners -0.10
176 Darin Downs Tigers -0.12
177 Joe Ortiz Rangers -0.12
178 Marc Rzepczynski – – – -0.12
179 Matt Albers Indians -0.12
180 Jared Hughes Pirates -0.13
181 Josh Fields Astros -0.13
182 Tony Sipp Diamondbacks -0.13
183 Troy Patton Orioles -0.13
184 Aaron Crow Royals -0.14
185 Cesar Ramos Rays -0.14
186 Wesley Wright – – – -0.14
187 Drew Storen Nationals -0.15
188 Josh Zeid Astros -0.15
189 Kyle Farnsworth – – – -0.15
190 Nick Hagadone Indians -0.16
191 Phil Coke Tigers -0.16
192 Brad Brach Padres -0.18
193 Fernando Salas Cardinals -0.18
194 Zach Duke – – – -0.18
195 Cory Gearrin Braves -0.19
196 Donnie Veal White Sox -0.19
197 Raul Valdes Phillies -0.19
198 A.J. Ramos Marlins -0.20
199 Jake Dunning Giants -0.20
200 Ramon Troncoso White Sox -0.20
201 Evan Scribner Athletics -0.21
202 George Kontos Giants -0.21
203 Jose Mijares Giants -0.21
204 Bryan Morris Pirates -0.22
205 David Hernandez Diamondbacks -0.22
206 Pedro Strop – – – -0.23
207 Rich Hill Indians -0.23
208 Jonathan Broxton Reds -0.24
209 Blake Beavan Mariners -0.26
210 Mike Adams Phillies -0.26
211 Josh Roenicke Twins -0.27
212 Vinnie Pestano Indians -0.27
213 Brad Lincoln Blue Jays -0.30
214 Justin De Fratus Phillies -0.30
215 Lucas Luetge Mariners -0.30
216 Garrett Richards Angels -0.31
217 Michael Bowden Cubs -0.33
218 T.J. McFarland Orioles -0.33
219 Al Alburquerque Tigers -0.35
220 John Axford – – – -0.35
221 Scott Atchison Mets -0.36
222 Adam Warren Yankees -0.37
223 Dylan Axelrod White Sox -0.37
224 Paul Clemens Astros -0.37
225 Ryan Mattheus Nationals -0.39
226 Travis Blackley – – – -0.40
227 Clayton Mortensen Red Sox -0.41
228 Esmil Rogers Blue Jays -0.42
229 Alex Wilson Red Sox -0.45
230 Brandon Lyon Mets -0.48
231 Carlos Marmol – – – -0.49
232 Greg Burke Mets -0.49
233 Joba Chamberlain Yankees -0.49
234 Michael Gonzalez Brewers -0.49
235 Brandon Maurer Mariners -0.50
236 Bruce Chen Royals -0.54
237 Jose Cisnero Astros -0.58
238 Jeremy Horst Phillies -0.59
239 Dallas Keuchel Astros -0.63
240 Hector Ambriz Astros -0.63
241 Ian Krol Nationals -0.67
242 Jeremy Affeldt Giants -0.67
243 Hector Rondon Cubs -0.71
244 Henry Rodriguez – – – -0.71
245 Michael Kirkman Rangers -0.74
246 Lucas Harrell Astros -0.81
247 Luis Garcia Phillies -0.83
248 Anthony Bass Padres -0.87
249 Brandon League Dodgers -0.93
250 Shawn Camp Cubs -1.03
251 Curtis Partch Reds -1.42

The Nine Worst Wins of 2013

Clip art illustration of a Cartoon Tiger with a Missing Tooth

If you’re here, you’ve likely been exposed to our series on pitcher wins and why we want to kill them. It’s become a pretty big topic of conversation around baseball and some people are calling for a cease fire because the win has been repeatedly slaughtered to the point that we’ve probably violated the Geneva Convention. So, I’ll make sure to avoid overdoing it because apparently #KillTheWin is sabr-bullying. If you’re new to the cause, check out the groundwork for why wins are a terrible statistic and then enjoy The Nine Worst Wins from 2013 (as of Sept 13th).

So the methodology is quite simple. Below are the pitchers in 2013 who have earned a “win” sorted by the lowest Win Probability Added (WPA). What WPA does is measure how much the team’s likelihood of winning changed as a result of every play and assigns that value to the pitcher and batter who took part. It’s not a perfect stat for measuring a player’s performance but it works for our purposes here for a simple reason. If a pitcher’s team scores 10 runs in the first inning, that pitcher can pitch poorly and get a win, but most of the pro-win alliance thinks that’s okay. They believe in something called “pitching to the score” which has been shown to be fiction. So in order to make the point clearly, I’ll use WPA which is entirely dependent on context. If you’re up 10, you’re allowed to give up 5. If you’re up 1, you better not give up two.

There are other ways to do this, but I think this is the most valuable way to do it given the audience still in need of persuasion.

Rk Player Date Tm Opp Rslt App,Dec
9 Randall Delgado 2-Aug ARI BOS W 7-6 GS-6 ,W
8 Brandon League 31-May LAD COL W 7-5 9-9 ,BW
7 CC Sabathia 18-Aug NYY BOS W 9-6 GS-6 ,W
6 Alfredo Simon 22-Apr CIN CHC W 5-4 13-13f,W
5 Rafael Soriano 17-May WSN SDP W 6-5 9-9 ,BW
4 Matt Belisle 28-Jul COL MIL W 6-5 8-8 ,BW
3 Joe Smith 26-Jun CLE BAL W 4-3 8-8 ,BW
2 Michael Wacha 19-Aug STL MIL W 8-5 7-7 ,BW
1 Kyuji Fujikawa 12-Apr CHC SFG W 4-3 9-9f ,BW

 

Rk Player IP H R ER BB SO HR Pit
9 Randall Delgado 6 6 6 4 1 7 2 97
8 Brandon League 1 2 2 2 0 1 1 26
7 CC Sabathia 5.1 7 6 6 5 5 1 103
6 Alfredo Simon 1 1 2 1 0 1 1 15
5 Rafael Soriano 1 4 2 2 0 0 0 19
4 Matt Belisle 1 2 2 2 0 2 1 23
3 Joe Smith 1 3 2 2 1 0 0 21
2 Michael Wacha 1 4 3 3 0 1 1 30
1 Kyuji Fujikawa 1 3 3 3 0 0 0 30

 

Rk Player ERA RE24 WPA
9 Randall Delgado 6.00 -2.939 -0.392
8 Brandon League 18.00 -1.479 -0.404
7 CC Sabathia 10.12 -3.472 -0.410
6 Alfredo Simon 9.00 -1.537 -0.417
5 Rafael Soriano 18.00 -1.594 -0.430
4 Matt Belisle 18.00 -1.479 -0.431
3 Joe Smith 18.00 -1.490 -0.528
2 Michael Wacha 27.00 -2.537 -0.557
1 Kyuji Fujikawa 27.00 -2.537 -0.745

To date, there have been 282 wins in which the pitcher had a negative WPA in 2013. Above you’ve seen the nine worst including Fujikawa having just about the worst performance I could imagine in a win using this method. In fact, as far back as we have WPA data, it’s the 14th worst such win.

It looked like this! That’s pretty bad.

chart

This is all by way of saying that wins aren’t a useful statistic and that even if we allow for the idea of pitching to the score, we still have a ton of ridiculous wins every season. If every win was handed out perfectly the rest of the season, we would still have seen 11.6% of the wins in 2013 go to pitchers who hurt their team’s chance to win.

#KillTheWinButDoItWithoutBeingSoDramatic

Dynamic Standings Projection (September 12, 2013)

In case you missed it, in April we launched our Dynamic Standings Projection feature on New English D. A full explanation of the methodology can be found here or by clicking the tab at the top of the page. This project seeks to provide a reasoned and cautious approach to updating our beliefs about the baseball future. You can find a summarization of the original projections here. You’ll notice a column on the far right that indicates the difference in projected wins from the preseason prediction. Positive numbers mean teams are now projected to win more games and negative numbers mean a team is now projected to win fewer games. You’ll notice a series of graphs below the standings section that track how the projections have evolved over the course of the year.

This Dynamic Standings Projection is updated through the September 11th games. Note that DSP posts have been moved to Thursday accommodate something that won’t interest you. 

12-Sep W L   PreDiff
BOS 96 66 0.593 19
TB 88 74 0.543 -3
NYY 86 76 0.531 1
BAL 86 76 0.531 4
TOR 76 86 0.469 -11
W L   PreDiff
DET 93 69 0.574 -1
KC 85 77 0.525 9
CLE 84 78 0.519 13
MIN 70 92 0.432 5
CWS 67 95 0.414 -16
W L   PreDiff
OAK 93 69 0.574 9
TEX 91 71 0.562 0
LAA 78 84 0.481 -10
SEA 72 90 0.444 -3
HOU 56 106 0.346 -4
W L   PreDiff
ATL 96 66 0.593 6
WSH 86 76 0.531 -9
PHI 76 86 0.469 -8
NYM 73 89 0.451 -5
MIA 61 101 0.377 -2
W L   PreDiff
STL 94 68 0.580 6
PIT 93 69 0.574 11
CIN 92 70 0.568 0
MIL 71 91 0.438 -8
CHC 69 93 0.426 1
W L   PreDiff
LAD 94 68 0.580 6
ARZ 82 80 0.506 0
SF 75 87 0.463 -16
SD 75 87 0.463 -3
COL 73 89 0.451 10

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