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Monday, March 11, 2019

In Baseball’s Game of Numbers, Yankees Differ on Which Ones Count - The New York Times

Ottavino, though, is on his own level. During the season, he checks two statistics he believes reflect how he is throwing: first-strike and walk percentages. At the end of the season, he dives deeply into how he threw the ball, using advanced statistics such as xwOBA (expected weight on-base average), which in layman’s terms, essentially measures the quality of the contact made against him.

He labeled other statistics, such as E.R.A. or the scoring percentage of inherited base runners, as faulty.

“We’re trying to strip away all the luck factors so you can be as real with yourself as possible,” he said. “If you’re not doing that, you’re going to ride the roller coaster really bad, and you’re lying to yourself.”

Even if some of Ottavino’s teammates are not quite there yet in terms of the game’s advanced numbers, the Yankees’ robust analytics department is there to help them all break down the multitude of statistics in the game. The players just have to ask.

Jim Furtado Posted: March 11, 2019 at 09:46 AM | 14 comment(s) Login to Bookmark
  Tags: statistics

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   1. bobm Posted: March 11, 2019 at 11:28 AM (#5821828)
He labeled other statistics, such as E.R.A. or the scoring percentage of inherited base runners, as faulty. [Bold added]


Spanning Multiple Seasons or entire Careers, From 2012 to 2018, (requiring IP>=100.0 and At least 80% games in relief), sorted by smallest IS%

                                                                             
Rk                    Player    IS%    IP From   To   G GS  GF ERA+   BF OPS+
1                 David Huff  8.57% 134.2 2012 2016  71  9  21   86  585  118
2                Josh Outman 12.82% 123.0 2012 2014 128  7  17   84  545  105
3                Zach Putnam 13.16% 144.2 2012 2017 137  0  36  130  595   81
4               Zack Britton 13.43% 387.1 2012 2018 303 18 221  158 1574   67
5              Casey Janssen 13.51% 202.0 2012 2015 216  0 145  122  810   71
6                 Josh Osich 14.14% 120.1 2015 2018 160  0  29   82  542  119
7               Shane Greene 15.07% 353.2 2014 2018 220 33  89   85 1536  106
8               Jared Burton 15.22% 192.0 2012 2014 203  0  47  117  798   79
9               Javier Lopez 15.33% 179.0 2012 2016 349  0  67  146  746   77
10              Randy Choate 15.84% 137.1 2012 2015 276  0  23  113  574   70
[...]
169           Ryan Yarbrough 29.17% 147.1 2018 2018  38  6   3  106  628  101
170             Jason Grilli 29.27% 295.1 2012 2017 329  0 136  105 1256   95
[...]                                                                         
Rk                 Player    IS%    IP From   To   G GS  GF ERA+   BF OPS+
222         Adam Ottavino 31.51% 390.2 2012 2018 361  0  78  136 1640   73
[...]
330       Warwick Saupold 43.08% 106.2 2016 2018  82  0  25   89  487  119
331        T.J. McFarland 43.56% 324.1 2013 2018 211  3  74  108 1419  101
332           Paul Sewald 44.00% 121.2 2017 2018 103  0  21   75  528  112
333        Brandon Maurer 44.44% 371.0 2013 2018 289 21 105   73 1636  118
334            Joe Nathan 45.83% 193.2 2012 2016 206  0 179  147  795   67
335     Jonathan Papelbon 45.83% 296.1 2012 2016 293  0 251  150 1209   73
336        Sam Tuivailala 47.37% 104.0 2014 2018 101  0  33  116  458  101
337          Anthony Bass 48.10% 251.0 2012 2018 120 15  33   76 1088  117
338         Michael Feliz 49.15% 168.2 2015 2018 145  0  42   75  743  110
339       Chien-Ming Wang 63.64% 112.2 2012 2016  54 11  24   73  512  142


Provided by Baseball-Reference.com: View Play Index Tool Used
Generated 3/11/2019.
   2. bobm Posted: March 11, 2019 at 11:41 AM (#5821836)
No surprise to see Hansel Robles at the bottom of this list...

Spanning Multiple Seasons or entire Careers, From 2012 to 2018, (requiring IP>=100.0, IR>=100, IP<=3*IR and At least 80% games in relief), sorted by smallest IS%

                                                                  
Rk                    Player    IS%    IP  IR From   To   G GS  GF
1               Javier Lopez 15.33% 179.0 261 2012 2016 349  0  67
2               Randy Choate 15.84% 137.1 221 2012 2015 276  0  23
3                 Sam LeCure 17.65% 195.0 102 2012 2015 192  0  44
4              Andrew Miller 18.68% 366.0 182 2012 2018 387  0 117
5              Nick Hagadone 19.61% 107.1 102 2012 2015 134  0  21
6               Joe Thatcher 20.22% 124.0 183 2012 2015 223  0  41
7     Fernando Rodriguez Jr. 20.56% 178.2 107 2012 2016 168  0  28
8                  Zach Duke 20.67% 295.2 208 2012 2018 359  1  58
9                Luis Avilan 20.83% 308.2 264 2012 2018 399  0  48
10               Darren ODay 20.83% 374.1 168 2012 2018 391  0  97
11                Neal Cotts 21.24% 187.0 113 2013 2015 199  0  34
12               Tommy Layne 21.53% 149.2 144 2012 2017 216  0  39
13              Jose Alvarez 21.97% 275.1 173 2013 2018 284  6  48
14              Oliver Perez 22.06% 287.2 272 2012 2018 397  0  70
15           Charlie Furbush 22.30% 175.1 139 2012 2015 219  0  30
16             Edward Mujica 22.33% 243.2 103 2012 2017 253  0 110
17              Brian Matusz 22.67% 258.2 150 2012 2016 228 17  40
18            Brad Boxberger 23.08% 284.1 117 2012 2018 291  0 131
19                Mike Morin 23.14% 174.0 121 2014 2018 186  0  37
20               Cesar Ramos 23.14% 280.0 121 2012 2016 189 12  71
21             Jerry Blevins 23.19% 321.1 276 2012 2018 413  1  77
22               Seth Maness 23.23% 247.0 198 2013 2017 252  0  48
23                Josh Edgin 23.49% 129.0 149 2012 2017 177  0  29
24              Blake Parker 23.58% 224.1 106 2012 2018 229  0  91
25              Jared Hughes 23.60% 436.2 267 2012 2018 440  0 111
26               J.P. Howell 23.63% 267.0 182 2012 2017 335  0  59
27              Brad Ziegler 23.66% 465.1 224 2012 2018 493  0 192
28              Shawn Kelley 23.76% 333.2 202 2012 2018 370  0 111
29          Antonio Bastardo 24.04% 292.2 104 2012 2017 324  0  76
30                Casey Fien 24.06% 275.0 133 2012 2017 292  0  59
31            Brian Duensing 24.11% 386.1 253 2012 2018 375 11  59
32                Cody Allen 24.12% 440.2 170 2012 2018 456  0 278
33          Santiago Casilla 24.16% 378.0 149 2012 2018 402  0 224
34               Scott Downs 24.32% 127.0 111 2012 2014 180  0  25
35               Josh Fields 24.37% 276.1 119 2013 2018 288  0  86
36             Justin Wilson 24.47% 370.2 188 2012 2018 412  0  81
37              Joel Peralta 24.75% 258.0 101 2012 2016 289  0  45
38          Marc Rzepczynski 25.15% 247.2 330 2012 2018 410  0  61
39                 Tony Sipp 25.24% 317.1 206 2012 2018 395  0  76
40            Kevin Siegrist 26.00% 245.2 100 2013 2017 276  0  51
41                Pat Neshek 26.11% 315.2 157 2012 2018 367  0  71
42               Manny Parra 26.13% 173.2 111 2012 2015 212  0  29
43              Justin Grimm 26.24% 356.0 141 2012 2018 306 19  65
44              Matt Belisle 26.25% 392.0 160 2012 2018 387  1  93
45                 Mike Dunn 26.32% 332.1 228 2012 2018 426  0  68
46              Peter Moylan 26.51% 163.0 166 2012 2018 212  0  36
47                Aaron Loup 26.67% 322.2 240 2012 2018 378  0  54
48             Chasen Shreve 26.83% 201.2 123 2014 2018 215  0  63
49             Craig Stammen 26.90% 406.0 171 2012 2018 301  0  60
50                Brad Brach 27.32% 449.0 183 2012 2018 415  0 123
51               Tony Watson 27.32% 478.0 194 2012 2018 503  0  91
52           Dellin Betances 27.41% 378.1 135 2013 2018 355  0  84
53               Robbie Ross 27.62% 330.2 181 2012 2017 266 12  56
54               Brett Cecil 27.92% 366.1 197 2012 2018 377  9  82
55                Will Smith 28.28% 345.1 145 2012 2018 296 17  52
56         Hunter Strickland 28.30% 226.0 106 2014 2018 253  0  82
57            Fernando Salas 28.72% 381.1 195 2012 2018 398  0 108
58               Sergio Romo 28.73% 384.2 181 2012 2018 436  5 192
59          Brandon Kintzler 28.81% 345.1 118 2012 2018 352  0 125
60                 Joe Smith 28.82% 421.2 170 2012 2018 457  0 106
61             Andrew Chafin 28.85% 212.1 156 2014 2018 249  3  32
62              Jamey Wright 29.00% 208.0 100 2012 2014 193  2  59
63                Bryan Shaw 29.11% 472.2 237 2012 2018 503  0 104
64             Xavier Cedeno 29.30% 174.0 157 2012 2018 246  0  40
65              Steve Cishek 29.30% 433.0 157 2012 2018 454  0 237
66            Dustin McGowan 29.31% 275.2 116 2013 2017 210  9  57
67            Scott Atchison 29.31% 188.1 116 2012 2015 185  0  35
68            Michael Tonkin 29.52% 146.1 105 2013 2017 141  0  55
69              Blaine Hardy 29.60% 245.1 125 2014 2018 194 13  42
70               Ryan Tepera 29.70% 193.2 101 2015 2018 193  0  56
71               Boone Logan 29.83% 232.2 238 2012 2018 356  0  54
72             Louis Coleman 29.85% 217.0 134 2012 2018 216  0  58
73             Matt Thornton 29.88% 202.2 164 2012 2016 276  0  52
74             Fernando Abad 30.00% 279.0 190 2012 2017 312  6  89
75             James Russell 30.00% 218.0 140 2012 2016 273  1  50
76              Jason Frasor 30.00% 168.0 130 2012 2015 204  0  41
77             Wesley Wright 30.08% 161.2 133 2012 2015 216  0  49
78               Tim Collins 30.23% 166.2 129 2012 2018 198  0  31
79                Pedro Baez 30.25% 269.1 119 2014 2018 266  0  40
80               Luis Garcia 30.28% 244.2 109 2013 2018 251  0  55
81                Jean Machi 30.28% 191.2 109 2012 2017 194  0  44
82                Jake McGee 30.32% 381.0 188 2012 2018 432  0 103
83               Adam Warren 30.32% 463.2 155 2012 2018 298 21  57
84             Mychal Givens 30.37% 260.0 135 2015 2018 226  0  53
85            Jeremy Affeldt 30.63% 187.2 111 2012 2015 220  0  37
86             Jake Petricka 31.03% 223.2 145 2013 2018 222  0  67
87               Scott Oberg 31.11% 201.1 135 2015 2018 210  0  39
88               Sam Freeman 31.16% 226.2 138 2012 2018 263  0  41
89              Jake Diekman 31.18% 312.0 170 2012 2018 365  0  75
90              Kevin Jepsen 31.40% 281.2 121 2012 2018 322  0  78
91             Adam Ottavino 31.51% 390.2 146 2012 2018 361  0  78
92                 Phil Coke 31.51% 173.0 146 2012 2016 201  0  55
93                 Dan Otero 31.53% 374.0 203 2012 2018 333  0  85
94              Nick Vincent 31.63% 332.0 196 2012 2018 352  1  55
95                Nate Jones 31.68% 281.0 161 2012 2018 271  0  58
96            Burke Badenhop 31.74% 261.2 167 2012 2015 267  0  65
97              Ryan Pressly 31.76% 340.1 170 2013 2018 307  0  60
98              Alexi Ogando 32.08% 293.2 106 2012 2018 209 19  48
99                Aaron Crow 32.48% 171.2 117 2012 2014 197  0  54
100              Chad Qualls 33.03% 264.1 109 2012 2017 307  0 108
101             Alex Claudio 33.33% 230.2 141 2014 2018 208  2  84
102             Dan Jennings 33.33% 344.0 255 2012 2018 382  1  77
103            Blake Treinen 33.33% 341.1 135 2014 2018 288  7 133
104                Ryan Webb 33.55% 258.0 152 2012 2016 240  0  71
105          Jeremy Jeffress 33.58% 323.2 134 2012 2018 320  1 106
106            George Kontos 33.81% 351.0 210 2012 2018 343  0  80
107           Danny Farquhar 33.87% 270.1 124 2013 2018 250  0  90
108            Dominic Leone 33.87% 202.2 124 2014 2018 190  0  31
109          Al Alburquerque 34.03% 201.2 144 2012 2017 223  0  47
110              Will Harris 34.06% 336.1 138 2012 2018 351  0  82
111              Pedro Strop 34.30% 420.0 172 2012 2018 460  0 100
112             Cory Gearrin 34.78% 228.1 161 2012 2018 252  0  62
113             Rex Brothers 34.82% 225.1 112 2012 2018 266  0  74
114                Sam Dyson 34.86% 324.1 109 2012 2018 315  1 132
115             Jose Mijares 35.64% 105.1 101 2012 2013 138  0  25
116            Craig Breslow 35.76% 291.2 151 2012 2017 281  2  76
117                 Ian Krol 35.86% 190.0 145 2013 2018 225  0  43
118            Chris Hatcher 35.92% 255.0 103 2012 2018 239  0  77
119             Bryan Morris 36.36% 236.0 121 2012 2017 231  0  59
120         Ronald Belisario 36.36% 213.1 110 2012 2015 213  0  47
121         Justin De Fratus 36.36% 190.0 110 2012 2015 186  0  47
122           Tom Wilhelmsen 36.44% 352.1 118 2012 2017 319  2 141
123            Cam Bedrosian 37.00% 201.2 100 2014 2018 215  0  43
124            Heath Hembree 37.39% 216.0 115 2013 2018 204  0  40
125           Junichi Tazawa 37.43% 367.0 171 2012 2018 379  0  71
126              J.J. Hoover 38.02% 285.0 121 2012 2018 290  0  81
127          Anthony Swarzak 38.51% 426.2 161 2012 2018 277  9  55
128              Alex Wilson 40.00% 320.2 180 2013 2018 290  1  58
129              Matt Albers 40.54% 317.1 222 2012 2018 312  1  83
130            Hansel Robles 41.04% 244.1 134 2015 2018 224  0  45


Provided by Baseball-Reference.com: View Play Index Tool Used
Generated 3/11/2019.
   3. Man o' Schwar Posted: March 11, 2019 at 11:41 AM (#5821837)
Warwick Saupold

This is made up. These are made up people. You can't fool me.
   4. Man o' Schwar Posted: March 11, 2019 at 11:43 AM (#5821838)
No surprise to see Hansel Robles at the bottom of this list...

I'm not surprised to see Pedro Strop near the bottom either. I know he's been relatively effective overall, but man I hate seeing him come into games when there are men on base. He's like a big broken screen door, just letting everyone come through.
   5. BrianBrianson Posted: March 11, 2019 at 11:48 AM (#5821843)
If you break down inherited runners scored by how many were out, and what bases runners were on, when the reliever came in, it would probably have non-zero value as a stat. But just as a percentage, it's a lot of noise for very little signal.
   6. Jose Needs an Absurd Ukulele Concert Posted: March 11, 2019 at 11:56 AM (#5821848)
To Brian’s point in number 5 the top of that list is going to be skewed toward LOOGYs, they only face one batter, usually with a platoon advantage and unlike a guy who may face a few batters really can only give up multiple inherited runs by giving up an XBH.
   7. Crispix Attacksel Rios Posted: March 11, 2019 at 12:17 PM (#5821859)
Warwick Saupold, a household name among baseball fans in his hometown of Perth, Australia. During his first of three seasons shuttling between the Tigers and Mud Hens, he was arrested for an altercation outside the Bronze Boar public house in the historic Toledo Warehouse District. He has signed with the Hanwha Tigers for 2019.

Now someone explain this "Dominic Leone" who has apparently been in the majors for FIVE years.
   8. Man o' Schwar Posted: March 11, 2019 at 01:53 PM (#5821890)
Now someone explain this "Dominic Leone" who has apparently been in the majors for FIVE years.

There are at least 20 names in the list in #2 I have never heard of. I guess that's the 13 man pitching staff environment we live in now.
   9. KronicFatigue Posted: March 11, 2019 at 02:18 PM (#5821901)
If you break down inherited runners scored by how many were out, and what bases runners were on, when the reliever came in, it would probably have non-zero value as a stat. But just as a percentage, it's a lot of noise for very little signal.


Not that people care too much about ERA anymore, but I always felt that a runner on third with less than two outs should be charged to the vacating pitcher. Runner on 1st with two outs should be charged to the reliever. Maybe anything in-between gets split in half.
   10. Pat Rapper's Delight (as quoted on MLB Network) Posted: March 11, 2019 at 02:24 PM (#5821905)
I thought the only numbers the Yankees counted were ringzz.
   11. Walt Davis Posted: March 11, 2019 at 04:59 PM (#5821944)
And dollars.
   12. Walt Davis Posted: March 11, 2019 at 05:12 PM (#5821947)
Dominant relievers (high Ks, low Hs) would have excellent IS% numbers except they're rarely used in those situations these days. But sure, on average, all a reliever (starter, batter) can do is their usual and if there happen to be men on base at the time then their usual is gonna result in some runs. There's no reason to think a reliever will do better with somebody else's runner on second and 1 out than with his own runner on second and one out ... or with nobody on, nobody out. And tying run on 3rd, one out ... not a good time for Hansel Robles. But the ideal reliever for basically every situation is Mariano Rivera so just have 8 of him.

The question is more whether there are things managers could be doing to better leverage the matchup between pitcher and situation. I've long wondered whether a couple of runners, on, less than two outs, bring in your groundball ROOGy hoping for a DP ... does that actually happen often enough to justify bringing that guy in? When they get a DP that's obvously great but htose guys also tend to give up a good bit more contact than other relievers ... but then probably a lot fewer XBH. Do you avoid that pitcher if it's two on with two outs?
   13. Never Give an Inge (Dave) Posted: March 11, 2019 at 06:36 PM (#5821958)

#12, right, all else being equal, with a runner on third, less than 2 outs, you'd rather bring in the high K guy than the equally good reliever who gives up a lot of fly balls. But I'm not sure how often "equally good" happens.
   14. Walt Davis Posted: March 12, 2019 at 05:42 PM (#5822224)
#13 ... there's really no way of knowing how good any reliever is ... small past sample sizes, projecting to a small future sample size and, of course, in any given PA, anything can happen.

But that's not really the question. Even if we know that lowish-K reliever A is better than high-K reliever B in some absolute sense, is man on 3rd <2 outs, 1 run lead (or tied) a situation where the value of a K is sufficiently high that the difference in K-rates overpowers the difference in overall effectiveness? I suspect the answer to that is no for any realistic pair of K-rates but that's the question to answer. If it is no (and the answer to the GB pitcher question is also no) then the answer to all situations basically reduces to "bring in your best available reliever, adjusting for batter handedness, reliever tiredness, leverage, inning, potential future need, etc."

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