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Saturday, June 16, 2007

Where They Aint Redux

Responding to Tango's comments, here is the new table with a column added, totals at the bottom, and excluding bunts.


Year Type BIP H Non-HR TB %H %Non-HR SLUG %Non-HR2
2003 Fly 36744 9898 5390 27314 26.9% 14.7% 0.743 16.7%
2004 Fly 37052 10494 5786 28619 28.3% 15.6% 0.772 17.9%
2005 Fly 37268 10442 5913 28207 28.0% 15.9% 0.757 18.1%
2006 Fly 37712 10863 6034 29557 28.8% 16.0% 0.784 18.3%
----------------------------------------------------------------------------------
2003 Ground 60783 14355 14353 15687 23.6% 23.6% 0.258 23.6%
2004 Ground 60212 14267 14267 15623 23.7% 23.7% 0.259 23.7%
2005 Ground 60373 14092 14092 15388 23.3% 23.3% 0.255 23.3%
2006 Ground 59912 14367 14367 15690 24.0% 24.0% 0.262 24.0%
----------------------------------------------------------------------------------
2003 Line 25846 18985 18289 26505 73.5% 70.8% 1.025 72.7%
2004 Line 25663 18951 18208 26495 73.8% 71.0% 1.032 73.1%
2005 Line 25425 18649 18162 25240 73.3% 71.4% 0.993 72.8%
2006 Line 25902 19012 18456 26072 73.4% 71.3% 1.007 72.8%
----------------------------------------------------------------------------------
2003 Pop 10853 168 168 207 1.5% 1.5% 0.019 1.5%
2004 Pop 11007 226 226 268 2.1% 2.1% 0.024 2.1%
2005 Pop 11123 223 223 258 2.0% 2.0% 0.023 2.0%
2006 Pop 10656 238 238 309 2.2% 2.2% 0.029 2.2%
----------------------------------------------------------------------------------
2003 30639 15 14 18 0.0% 0.0% 0.001 0.0%
2004 31657 0 0 0 0.0% 0.0% 0.000 0.0%
2005 30463 1 0 4 0.0% 0.0% 0.000 0.0%
2006 31558 47 47 93 0.1% 0.1% 0.003 0.1%
----------------------------------------------------------------------------------
Totals 660848 175293 154233 281554 26.5% 23.3% 0.426 24.1%

Friday, June 15, 2007

Chat Transcript 06/15

Here's the link to the transcript. Thanks to everyone who participated. Great questions as always.

Hit 'em Where They Aint

I was running a few numbers for a colleague and so I thought I'd post them. Below is a table going back to 2003 that shows the number of balls put into play by vector and the numbers and percentages that went for hits and non-homerun hits. Finally we have the slugging percentage earned on those batted balls.


Year Type BIP H Non-HR TB %H %Non-HR SLUG
2003 Fly 36870 9898 5390 27314 26.8% 14.6% 0.741
2004 Fly 37168 10494 5786 28619 28.2% 15.6% 0.770
2005 Fly 37268 10442 5913 28207 28.0% 15.9% 0.757
2006 Fly 37856 10863 6034 29557 28.7% 15.9% 0.781
------------------------------------------------------------------------
2003 Ground 62253 14979 14977 16312 24.1% 24.1% 0.262
2004 Ground 61577 14841 14841 16198 24.1% 24.1% 0.263
2005 Ground 61809 14669 14669 15965 23.7% 23.7% 0.258
2006 Ground 61131 14910 14910 16233 24.4% 24.4% 0.266
------------------------------------------------------------------------
2003 Line 25852 18986 18290 26506 73.4% 70.7% 1.025
2004 Line 25666 18951 18208 26495 73.8% 70.9% 1.032
2005 Line 25425 18649 18162 25240 73.3% 71.4% 0.993
2006 Line 25909 19013 18457 26073 73.4% 71.2% 1.006
------------------------------------------------------------------------
2003 Pop 11124 173 173 212 1.6% 1.6% 0.019
2004 Pop 11285 236 236 278 2.1% 2.1% 0.025
2005 Pop 11370 230 230 265 2.0% 2.0% 0.023
2006 Pop 10886 239 239 310 2.2% 2.2% 0.028
------------------------------------------------------------------------
2003 30639 15 14 18 0.0% 0.0% 0.001
2004 31657 0 0 0 0.0% 0.0% 0.000
2005 30463 1 0 4 0.0% 0.0% 0.000
2006 31558 47 47 93 0.1% 0.1% 0.003


So from this you can see that just under 30% of fly balls go for hits although only 16% of non-homerun flyballs. About a quarter of ground balls and three quarters of fly balls fall in and 1 in 50 popups are hits. The remainder are not actually balls in place but rather strikeouts and unclassified plays in the data.

Thursday, June 14, 2007

Long Live the King


My column today focuses on creating pitcher profiles using the Gameday data with a case study on Felix Hernandez. It turns out that 415 of Hernandez's approximately 800 pitches in 2007 have been captured by PITCHf/x and so it's interesting to explore generating pitch profiles and various tables and graphs breaking down his pitches every which way from Sunday. For me, it was mostly an exercise in seeing how easy it would be to manipulate the data in various ways but it did quantify Felix's loss of movement and velocity following injury, his reluctance to throw the changeup against right-handed hitters, as well as his tendency to focus on the fastball in the first inning. Of course these are things that have been observed but it's nice to see the supporting evidence as well.

What I find most interesting (and piggy-backing off of the work of others) is that it shows the pitches can be identified and classified using the data (my algorithm was able to hit 95% agreement on his June 10th start based on David Cameron's charting). What I did was exceedingly simple, however, and requires customization for each pitcher. It'll be interesting to see if a system can be devised that classifies the pitches more broadly across a set of pitchers. Still, it seems human interaction will be required but hopefully it can be minimized.

Don't forget about the chat tomorrow!

Wednesday, June 13, 2007

Chat This Friday!

I'll be chatting on Baseball Prospectus on Friday morning/afternoon. Here are the transcripts from previous chats:

  • 4/27/2007

  • 3/16/2007

  • 2/06/2007

  • 11/21/2006
  • Sunday, June 10, 2007

    Squaring It Up

    In the comments on my post about plate discipline the question of "holes" was brought up. Specifically the idea is whether or not there are hitters who more consistently swing and miss on pitches that are in the strike zone. Well, with the data now becoming available we can add that to our list of things to look at.

    The metric is called Square and is defined as the percentage of balls made contact with that were swung at in the strike zone. So if Brian Giles swung at 105 pitches in the strike zone and made contact with 101 of them his Square would be .962. Now perhaps "Square" isn't the best term since I've also included foul balls here but you get the idea. In any case here are here are the percentages for all hitters (and keep in mind we don't have all hitters but only those who've batted in the nine parks in which the PITCHf/x system is running).


    Name Stand Pitches SinZ Square
    Derek Jeter R 188 52 1.000
    Chone Figgins L 144 42 1.000
    Placido Polanco R 117 31 1.000
    Esteban German R 126 27 1.000
    David Dejesus L 209 55 0.982
    David Ortiz L 224 50 0.980
    Dan Johnson L 411 75 0.973
    Jay Payton R 105 37 0.973
    Maicer Izturis L 179 32 0.969
    Coco Crisp L 168 31 0.968
    Rafael Furcal L 406 90 0.967
    Juan Pierre L 462 118 0.966
    Reggie Willits R 135 28 0.964
    Ichiro Suzuki L 552 109 0.963
    Trot Nixon L 111 27 0.963
    Brian Giles L 381 105 0.962
    Kevin Millar R 108 25 0.960
    Mark Grudzielanek R 186 48 0.958
    Barry Bonds L 122 24 0.958
    Ryan Sweeney L 126 22 0.955
    Casey Kotchman L 466 106 0.953
    Matt Murton R 101 21 0.952
    Kenny Lofton L 569 144 0.951
    Mike Lowell R 200 60 0.950
    Albert Pujols R 108 20 0.950
    John McDonald R 170 39 0.949
    Mark Ellis R 472 114 0.947
    Darin Erstad L 372 74 0.946
    Frank Thomas R 517 108 0.944
    Pablo Ozuna R 129 36 0.944
    Miguel Tejada R 148 36 0.944
    Ben Broussard L 126 36 0.944
    Ramon Martinez R 124 35 0.943
    David Dellucci L 111 34 0.941
    Johnny Damon L 190 49 0.939
    Lyle Overbay L 381 96 0.938
    Frank Catalanotto L 330 78 0.936
    Ramon Hernandez R 115 31 0.935
    Yuniesky Betancourt R 376 106 0.934
    Geoff Blum L 148 29 0.931
    Andre Ethier L 413 128 0.930
    Shannon Stewart R 464 126 0.929
    Jason Kendall R 423 112 0.929
    Ryan Zimmerman R 114 28 0.929
    Mike Sweeney R 131 41 0.927
    Alexis Rios R 467 108 0.926
    Brian Mccann L 280 53 0.925
    Hideki Matsui L 186 53 0.925
    Nick Markakis L 168 52 0.923
    Luis Gonzalez L 462 116 0.922
    Erick Aybar L 235 64 0.922
    Kevin Youkilis R 219 51 0.922
    Raul Ibanez L 514 126 0.921
    Melvin Mora R 189 50 0.920
    Orlando Cabrera R 518 137 0.920
    Mike Cuddyer R 155 37 0.919
    Brian Roberts L 134 37 0.919
    Jerry Hairston R 124 37 0.919
    Robinson Cano L 171 36 0.917
    Brendan Harris R 165 48 0.917
    Nick Swisher R 149 24 0.917
    Reggie Willits L 280 59 0.915
    Ramon Vazquez L 184 47 0.915
    Mark Derosa R 113 35 0.914
    Ian Kinsler R 630 163 0.914
    J.D. Drew L 184 46 0.913
    Jamie Burke R 107 23 0.913
    Jose Lopez R 382 102 0.912
    Dustin Pedroia R 158 45 0.911
    Ken Griffey Jr. L 109 22 0.909
    Jose Vidro L 349 87 0.908
    Julio Lugo R 226 65 0.908
    Gary Sheffield R 168 32 0.906
    Kenji Jojima R 284 95 0.905
    Sean Casey L 101 21 0.905
    Victor Martinez L 100 21 0.905
    A.J. Pierzynski L 376 115 0.904
    Marco Scutaro R 192 52 0.904
    Grady Sizemore L 143 31 0.903
    Bengie Molina R 106 31 0.903
    Jorge Posada L 136 41 0.902
    Gary Matthews Jr. L 449 102 0.902
    Jeff Kent R 453 142 0.901
    Garret Anderson L 262 50 0.900
    Luis Castillo L 121 30 0.900
    Tadahito Iguchi R 490 146 0.897
    Michael Young R 628 193 0.896
    Kelly Johnson L 427 85 0.894
    Jermaine Dye R 467 119 0.891
    Josh Bard L 308 91 0.890
    Adrian Beltre R 441 126 0.889
    Howie Kendrick R 165 45 0.889
    Curtis Granderson L 147 35 0.886
    Aaron Hill R 461 129 0.884
    Magglio Ordonez R 150 43 0.884
    Doug Mientkiewicz L 113 17 0.882
    Paul Konerko R 489 116 0.879
    Shea Hillenbrand R 330 91 0.879
    Justin Morneau L 137 33 0.879
    Edgar Renteria R 379 82 0.878
    Willie Harris L 208 49 0.878
    Nomar Garciaparra R 470 152 0.875
    Carlos Guillen L 112 24 0.875
    Scott Thorman L 230 47 0.872
    Hank Blalock L 332 78 0.872
    Brady Clark R 160 39 0.872
    Ivan Rodriguez R 118 31 0.871
    Matt Diaz R 191 53 0.868
    Alfonso Soriano R 127 30 0.867
    Jason Giambi L 130 30 0.867
    Marlon Byrd R 174 44 0.864
    Gerald Laird R 504 138 0.862
    Andy Laroche R 127 29 0.862
    Mark Teixeira R 169 43 0.860
    Derrek Lee R 146 43 0.860
    Chris Woodward R 154 49 0.857
    Joe Crede R 376 104 0.856
    Vladimir Guerrero R 408 97 0.856
    Adam Lind L 374 110 0.855
    Khalil Greene R 419 136 0.853
    Alex Cintron L 119 34 0.853
    Adrian Gonzalez L 641 163 0.853
    Juan Uribe R 353 101 0.851
    Jose Guillen R 423 121 0.851
    Joshua Barfield R 115 40 0.850
    Willie Bloomquist R 156 46 0.848
    Royce Clayton R 264 78 0.846
    Alex Gordon L 163 39 0.846
    Aubrey Huff L 123 39 0.846
    Robb Quinlan R 135 45 0.844
    Bobby Crosby R 489 127 0.843
    Chris Stewart R 103 38 0.842
    Jose Cruz Jr. L 303 82 0.841
    Russell Martin R 543 145 0.841
    Travis Buck L 393 88 0.841
    Marcus Giles R 504 156 0.840
    Vernon Wells R 461 124 0.839
    Wilson Betemit L 224 49 0.837
    Manny Ramirez R 227 61 0.836
    Brad Wilkerson L 263 60 0.833
    Bobby Abreu L 225 60 0.833
    Emil Brown R 153 36 0.833
    Elijah Dukes R 208 47 0.830
    Richie Sexson R 485 123 0.829
    Kevin Kouzmanoff R 393 117 0.829
    Ty Wigginton R 221 64 0.828
    Mike Cameron R 589 157 0.828
    Eric Chavez L 542 136 0.824
    Tony Pena R 130 34 0.824
    Jose Molina R 157 45 0.822
    Casey Blake R 167 42 0.810
    Delmon Young R 232 68 0.809
    Jason Phillips R 236 67 0.806
    Mark Teixeira L 517 102 0.804
    Jeffrey Francoeur R 381 98 0.796
    Jim Thome L 359 78 0.795
    Gary Matthews Jr. R 118 24 0.792
    Jose Cruz Jr. R 108 28 0.786
    Milton Bradley L 135 46 0.783
    Nick Swisher L 410 86 0.779
    Michael Napoli R 349 85 0.776
    Rob Mackowiak L 313 76 0.776
    Troy Glaus R 353 76 0.776
    Mark Teahen L 213 49 0.776
    Victor Diaz R 159 49 0.776
    Mike Piazza R 186 40 0.775
    Carl Crawford L 242 62 0.774
    Brandon Inge R 143 35 0.771
    Matt Stairs L 202 51 0.765
    Alex Rodriguez R 205 55 0.764
    Hiram Bocachica R 118 25 0.760
    Terrmel Sledge L 301 88 0.750
    Rocco Baldelli R 135 32 0.750
    Craig Monroe R 139 30 0.733
    Craig Wilson R 105 26 0.731
    Travis Hafner L 138 22 0.727
    Sammy Sosa R 588 164 0.726
    Andruw Jones R 433 112 0.723
    B.J. Upton R 263 75 0.720
    Chipper Jones L 194 39 0.718
    Olmedo Saenz R 149 39 0.718
    Carlos Pena L 184 46 0.717
    Nelson Cruz R 374 100 0.700
    Jack Cust L 318 66 0.697
    Jason Smith L 103 28 0.679
    Rob Bowen L 114 26 0.654
    Russ Branyan L 164 49 0.612


    Generally speaking the top of the list is populated with contact hitters while the bottom has more power hitters and free swingers as you might expect. A couple surprises to me anyway are David Ortiz and Dan Johnson so high in the list and Chipper Jones (batting left-handed) so low. The average is 87.2% which validates the feeling I always get, especially when attending a game in person, that when a pitch is in the strike zone a major league hitter usually takes advantage.

    Saturday, June 09, 2007

    A Soriano Trifecta

    Last night in Atlanta Alfonso Soriano homered in each of his first three plate appearances before being intentionally walked, grounding out, and then singling in the ninth inning. His four for five day led the Cubs to a 9-1 victory over the Braves. After a fairly slow start (.270/.392/.308 in April) he hit .302/.500/.362 in May and is 19 for 37 in June a double, 2 triples, and 6 homeruns giving him 10 homeruns for the season. This season he's as aggressive as ever seeing 3.69 pitches per plate appearance and in the metrics on plate discipline I discussed the other day he swings at the highest percentage of pitches (54.8%) that are out of the strike zone of anyone not named Ivan Rodriguez. However, he's just about average in terms of the percentage of strikes he lets by (23%). In any case everything is working for him at the moment and on Friday night he jumped on the first pitch three times. Here are his five plate appearances from Friday night along with a chart of all the pitches he saw.

    The number in the upper right hand corner indicate the pitch number along with the starting velocity, ending velocity, and break of the pitch. The pitches are color-coded and their shapes follow this key (you can click on any of the images to make them bigger):



















    Thursday, June 07, 2007

    Quantifying Plate Discipline

    In my column this morning on Baseball Prospectus (subscription required but well worth it) among other things I take another crack at the PITCHf/x Gameday data. In part, inspired by this fascinating article, I created a couple of metrics to quantify plate discipline. They are:

  • Swing (S) defined as the percentage of pitches the batter swung at and also available in many other places. Obviously high values here are indicative of aggressive hitters or hitters who see a greater percentage of pitches out of the strike zone.


  • Fish (F) defined as the percentage of pitches out of the strike zone that the hitter swung at. A higher percentage here indicates that the hitter may have trouble recognizing pitches since he is offering at pitches that would likely otherwise be called balls. It should be noted that the strike zone as defined for this analysis is 17 inches wide (the standard) and uses the actual height customized for the player. No buffer room was added as was done in the previous articles since here we're not concerned with giving the umpire the benefit of the doubt.


  • Bad Ball (BB) defined as the percentage of pitches out of the strike zone that were swung at and made contact with (including foul balls although there is an argument to be made that a foul ball is not the intended outcome and so should be discounted in some way). A higher value in this category indicates that the hitter, when swinging at bad pitches, is at least able to get the bat on the ball.


  • Eye (E) defined as the percentage of pitches in the strike zone on non-three and zero counts that were taken for strikes. A smaller value in this metric indicates a player who recognizes strikes and aggressively offers at them. Non three and zero counts were excluded since obviously a hitter is much more likely to let a strike go by in this situation and so we don’t want to penalize them for that behavior. Some readers will see, however, where this idea could be extended to each of the eight possible counts and a system devised where less penalty is credited to hitters who take at 3-1 than those that do so at 0-2.


  • Without further ado here's the list (with the big caveat that only 24% of all pitches in 2007 have been tracked in the system and there is a heavy bias to the AL West because of the parks that the system is installed in) of all players who have 200 or more pitches tracked this season sorted by "Fish".


    Name Stand Pitches Swing Fish BadBall Eye
    A.J. Pierzynski L 357 0.602 0.469 0.813 0.117
    Garret Anderson L 260 0.515 0.467 0.750 0.350
    Delmon Young R 200 0.550 0.454 0.630 0.228
    Rob Mackowiak L 297 0.525 0.438 0.738 0.240
    Hank Blalock L 332 0.521 0.430 0.632 0.183
    Erick Aybar L 235 0.532 0.430 0.869 0.217
    Carl Crawford L 216 0.519 0.427 0.738 0.171
    Jeffrey Francoeur R 337 0.546 0.425 0.775 0.094
    Vladimir Guerrero R 403 0.524 0.421 0.771 0.142
    Adrian Beltre R 430 0.512 0.403 0.694 0.234
    Michael Young R 585 0.523 0.403 0.766 0.284
    Eric Chavez L 519 0.503 0.394 0.736 0.225
    Kenji Jojima R 270 0.522 0.389 0.878 0.217
    Nomar Garciaparra R 436 0.557 0.388 0.800 0.132
    Juan Pierre L 431 0.480 0.385 0.916 0.302
    Yuniesky BetancourR 345 0.496 0.383 0.806 0.279
    Joe Crede R 376 0.503 0.381 0.729 0.238
    Jason Phillips R 203 0.493 0.381 0.721 0.303
    Vernon Wells R 417 0.501 0.380 0.713 0.216
    Jose Lopez R 347 0.478 0.375 0.853 0.288
    Ichiro Suzuki L 515 0.435 0.369 0.862 0.326
    Khalil Greene R 407 0.514 0.367 0.595 0.247
    Orlando Cabrera R 517 0.468 0.362 0.838 0.279
    Brian Mccann L 267 0.434 0.358 0.783 0.282
    Kevin Kouzmanoff R 363 0.499 0.350 0.724 0.167
    Lyle Overbay L 381 0.465 0.349 0.704 0.230
    Sammy Sosa R 532 0.492 0.349 0.625 0.205
    Royce Clayton R 227 0.515 0.348 0.457 0.194
    Adam Lind L 336 0.482 0.348 0.719 0.253
    Andruw Jones R 389 0.478 0.344 0.686 0.232
    Jose Guillen R 394 0.475 0.344 0.636 0.232
    Alexis Rios R 413 0.426 0.343 0.735 0.351
    Marcus Giles R 452 0.511 0.341 0.674 0.211
    Bobby Crosby R 474 0.451 0.338 0.652 0.327
    Casey Kotchman L 463 0.434 0.338 0.814 0.285
    Gary Matthews Jr. L 449 0.441 0.334 0.781 0.223
    David Dejesus L 209 0.445 0.333 0.816 0.340
    Nelson Cruz R 374 0.457 0.330 0.690 0.268
    Andre Ethier L 376 0.500 0.329 0.803 0.200
    Jose Vidro L 336 0.461 0.329 0.870 0.200
    Juan Uribe R 334 0.476 0.328 0.651 0.232
    Raul Ibanez L 474 0.456 0.328 0.760 0.229
    Gerald Laird R 484 0.459 0.326 0.698 0.290
    Jason Kendall R 405 0.432 0.325 0.870 0.373
    Jermaine Dye R 452 0.442 0.324 0.753 0.267
    Mark Teahen L 213 0.437 0.324 0.636 0.307
    Adrian Gonzalez L 590 0.453 0.322 0.767 0.225
    Darin Erstad L 372 0.398 0.318 0.797 0.413
    Shea Hillenbrand R 330 0.445 0.308 0.821 0.297
    Brad Wilkerson L 263 0.414 0.306 0.755 0.303
    Paul Konerko R 457 0.420 0.303 0.765 0.290
    Richie Sexson R 448 0.446 0.303 0.732 0.211
    Mark Ellis R 440 0.409 0.302 0.851 0.380
    Mark Teixeira L 501 0.399 0.302 0.657 0.276
    Kenny Lofton L 514 0.434 0.300 0.818 0.239
    Travis Buck L 377 0.416 0.300 0.662 0.255
    Michael Napoli R 346 0.419 0.299 0.683 0.322
    Kelly Johnson L 384 0.393 0.292 0.787 0.315
    Josh Bard L 283 0.470 0.292 0.878 0.177
    Edgar Renteria R 346 0.405 0.290 0.688 0.275
    Jeff Kent R 420 0.476 0.285 0.611 0.176
    Ian Kinsler R 591 0.423 0.280 0.784 0.268
    Terrmel Sledge L 285 0.446 0.272 0.609 0.217
    Rafael Furcal L 371 0.391 0.270 0.857 0.353
    Shannon Stewart R 437 0.410 0.269 0.810 0.327
    B.J. Upton R 225 0.431 0.269 0.528 0.227
    Frank Thomas R 478 0.377 0.267 0.838 0.335
    Troy Glaus R 306 0.376 0.264 0.706 0.330
    Jose Cruz Jr. L 285 0.428 0.262 0.591 0.216
    Aaron Hill R 417 0.415 0.253 0.729 0.302
    Willie Harris L 205 0.400 0.248 0.765 0.239
    Russell Martin R 506 0.401 0.241 0.757 0.290
    Luis Gonzalez L 428 0.395 0.236 0.889 0.256
    Nick Swisher L 384 0.365 0.232 0.559 0.307
    Tadahito Iguchi R 462 0.422 0.230 0.678 0.243
    Frank Catalanotto L 309 0.372 0.228 0.821 0.319
    Mike Cameron R 539 0.399 0.224 0.569 0.237
    Reggie Willits L 274 0.328 0.219 0.818 0.455
    Brian Giles L 381 0.396 0.218 0.804 0.269
    Jim Thome L 330 0.358 0.203 0.545 0.239
    Bobby Abreu L 203 0.374 0.185 0.545 0.274
    Jack Cust L 294 0.310 0.175 0.563 0.342
    Wilson Betemit L 208 0.327 0.155 0.700 0.282
    Dan Johnson L 387 0.282 0.148 0.737 0.346


    Of course the interesting thing is that you can then plot the Fish and Eye metrics on a graph and then split the graph into four quadrants. Each quadrant creates a little profile that can be used to characterize a hitter's plate discipline. Note that the bottom left is the sweet spot.

    Wednesday, June 06, 2007

    Fun at the Old Ballpark

    Last Sunday afternoon my daughter and I headed to Coors Field to see the Rockies take on the Reds in the rubber game of their three-game set. We arrived plenty early and had a good time watching batting practice and chatting about the routine the players perform before the game and how the two teams were doing this season. I was also able to throw in some physics in as we discussed the topic of my recent columns on Baseball Prospectus. She still had three more days of school to go at the time and so the "lecture" was received amiably but not deeply.


    My daughter isn't really a very big fan but does enjoy the experience and so I wanted her to be able to see Ken Griffey Jr. play.

    The conversation of course turned to his career and accomplishments and she was wowed when she learned he was eighth on the all-time list with 575. So she had to snap a few pictures and caught him coming in after BP and joking around with some folks on the sidelines.








    After a colossal lunch that included garlic fries and all manner of fried food we settled down for the game and were rewarded with a 10-9 Rockies victory in 10-innings complete with a six-run comeback by the Rox capped by a three-run triple by Kaz Matsui in the bottom of the eighth inning. Garrett Atkins drove home the winning run in the bottom of the 10th on a line-drive single to left. There were also several interesting baserunning plays in the game, interspersed with dippin' dots of course, that were fodder for discussion. As countless fathers can no doubt attest, most of all it was just a great time spent with my daughter.

    Tuesday, June 05, 2007

    The Nats and VORP

    I was tipped to this article by Will Carroll. The fascinating paragraph follows:

    The Nationals, too, are deploying more tools and ideas. Over the weekend, a group of the club's statistical analysts -- "I'll call them our 'Mod Squad,' " Kasten said -- made a presentation to scouts detailing trends in the draft, using such modern stats as "VORP" (Value Over Replacement Player), the kind of analysis that can make old-school scouts shudder.

    It would be interesting to see just how they're applying VORP to amateur players... In any case this is just the kind of thing I was thinking about when I wrote the following in an interview with Baseball Digest Daily last year.

    It seems to me that one of the ways in which a team could gain an advantage is to more tightly marry their statistical analysis to their scouting departments in a kind of Hegelian Synthesis. It's just my sense of things (being an outsider after all), but I would guess that most scouts still have little understanding of some of the core sabermetric principles and conclusions. For example, in a roundtable discussion Alan Schwarz had with Eddie Bane (Angels) and Gary Hughes (Cubs) published in 2005, it was clear that Hughes had never even heard of Defense Independent Pitching Statistics (DIPS). While I know that everybody can't know everything, and I'm not throwing Hughes under the bus, I can't imagine that it wouldn't help any team to have their staffs educated on the big picture items like this.

    Legos to the Rescue

    A couple of interesting tidbits this morning.

  • A co-worker sent me this link from the local Colorado Springs paper. Teenager Cameron Kruse, who works as a Sky Sox ball boy, built a machine to rub down baseballs in a uniform way. There's also a nice video on YouTube and although it doesn't mention it in the article, he might have used Lego Mindstorms for the programming.


  • Clay Davenport looks a little deeper into the number of minor league innings rookie pitchers have logged over time. The analysis is still incomplete but is suggestive that perhaps the number of innings accumulated in the minor leagues hasn't declined as has recently been discussed.
  • Friday, June 01, 2007

    Friday Night Links

    Well, the Rockies lost for the third straight night, this time to the Reds at Coors Field falling 4-2. Ken Griffey Jr. hit the 575th homerun of his career and Alex Gonzalez hit a three-run homer down the left field line. Those were the two big blows that Taylor Buchholz gave up - otherwise he pitched a pretty good game and was very efficient with his pitches.

    A couple of interesting links:

  • Bad Interview - An interview with Buzz Bissinger regarding an article that will come out this weekend in the New York Times magazine (update: the link is now active and the article is excellent with the caveat mentioned below) on pitching featuring Kerry Wood. In the interview Bissinger says that pitchers have been coming to the big leagues younger and younger. Turns out that's not true although in Bissinger's defense his underlying point was really more about the number of minor league innings today's pitchers throw which as far I know has not been studied. The questioning of the "younger and younger" statement then takes the interview on a bad turn (hat tip to Will Carroll). While I certainly agree with the interviewer's primary point that we needn't take someone's word for what is in the end an objective question for which there is data to definitively answer, it could have and should have been handled better. Bissinger seemed to lose control himself a little which hastened the badness.


  • Singular - A really well done article by Steve Treder on Steve Dalkowski on THT and one that befits the fact that "His performance profile is beyond question the most singular in the sport's long and meticulously detailed accounting."
  • Thursday, May 31, 2007

    The Physics of Drag

    My column today on Baseball Prospectus delves once again into the PITCHf/x data tracked by the new Gameday application. This time I take a look at the drag on a pitched ball and square the data with the description of the model discussed by Robert Adair in The Physics of Baseball.

    To answer the most frequently asked question thus far - no, I haven't looked at Tim Wakefield in any depth. I did see, however, that his average pitch (and I have 346 to look at) lost exactly 10% of its velocity. Overall though that percentage decrease is in line with the following chart (a version of this chart is also in the original article) since his average pFX (which is a measure of the break of the pitch) was 8.6 and his average start speed was 68.5 miles per hour as shown in the chart below.



    However, that percentage does not seem to differ by the break length (a different measure of break introduced this year) nor the pFX value. It's also interesting to note that all but one pitch came out of his hand at less than 79 miles per hour. I think it's likely that the Magnus force placed on a knuckler as it moves in various directions tends to slow it down more than one would other think based on the slow speed and lack of spin.

    Monday, May 28, 2007

    The 100 RBI Men

    A reader makes the following observation:

    "Carlos Delgado is currently on pace to get 100 RBIs for the Mets this year, despite sporting an abysmal .234 BA, 306 OBA and 359 SL%. This helps to make the case that RBIs are as much a team stat as an individual one, as the fellas hitting in front of Delgado (Jose Reyes, Carlos Beltran, and David Wright) are pretty adept at getting on base, which allows Delgado to make outs 7 times out of ten and still accumulate a decent number of RBIs. Simply put, he is getting a boatload of opportunities. Delgado also is lucky enough to bat cleanup on a team that is doing very well in the standings, so the manager is unlikely to move him out of the cleanup slot anytime soon."

    Well, assuming Delgago plays in 144 games this season as he did in both 2005 and 2006 he'll wind up with 91 RBI and won't break the 100 mark. And as of tonight Delgado's OPS is 665 and taking 2006 league norms for league OPS and the park effect of Shea Stadium that means that Delgado is on pace to have a league normalized and park adjusted OPS of 92. In any case, that doesn't directly bear on the question which follows...

    "So, anyways, my question: Who are the worst hitters in MLB history to get 100 RBIs in a season in MLB? And what are their stories? Were these players in similar situations to Delgado, or do they have some other tale to tell?"

    To answer the first part and take a crack at the second, here are the "top" 50 players with 100 or more RBI in a single season with the lowest normalized and park adjusted OPS. There are 1,543 players with 100 or more RBI in a single season since beginning in 1901.


    Name Year PA G RBI OPS NOPS/PF
    Joe Carter 1997 668 157 102 683 89
    Vinny Castilla 1999 674 158 102 809 92
    Ruben Sierra 1993 692 158 101 678 93
    Tony Armas 1983 613 145 107 707 94
    Paul O'Neill 2000 628 142 100 760 94
    Ray Pepper 1934 598 148 101 732 94
    Marv Owen 1936 655 154 105 750 96
    Joe Carter 1996 682 157 107 782 96
    Glenn Wright 1927 626 143 105 716 96
    Joe Carter 1990 697 162 115 681 97
    Travis Fryman 1996 688 157 100 766 97
    Joe Randa 2000 665 158 106 781 97
    Jeff Francoeur 2006 686 162 103 742 98
    Jeff Cirillo 2000 684 157 115 869 98
    Tony Batista 2004 650 157 110 728 98
    Torii Hunter 2003 642 154 102 762 99
    Ray Jablonski 1953 640 157 112 735 99
    Joe Pepitone 1964 647 160 100 698 100
    Ernie Banks 1969 629 155 106 725 100
    Carlos Beltran 1999 723 156 108 791 100
    Bill Buckner 1986 681 153 102 733 100
    Bill Brubaker 1936 620 145 102 736 101
    George Bell 1992 670 155 112 712 101
    Garret Anderson 2001 704 161 123 792 101
    Travis Fryman 1997 657 154 102 766 101
    Andres Galarraga 1995 604 143 106 842 101
    Chili Davis 1993 645 153 112 767 101
    Eddie Robinson 1953 685 156 102 735 101
    Wally Pipp 1923 634 144 108 749 101
    Willie McGee 1987 652 153 105 746 101
    Bing Miller 1930 654 154 100 795 101
    Pinky Higgins 1938 603 139 106 794 101
    Butch Hobson 1977 637 159 112 789 101
    Andruw Jones 2001 693 161 104 772 101
    George Kelly 1929 632 147 103 760 101
    Gee Walker 1939 645 149 111 773 101
    Moose Solters 1936 676 152 134 802 101
    Ed Sprague 1996 670 159 101 821 101
    Al Simmons 1924 644 152 102 774 102
    Ruben Sierra 1987 696 158 109 771 102
    Billy Rogell 1934 679 154 100 766 102
    Richie Sexson 1999 525 134 116 818 102
    Vernon Wells 2002 648 159 100 762 102
    Pinky Whitney 1930 662 149 117 849 102
    Pinky Whitney 1928 636 151 103 768 102
    Matt Williams 1997 636 151 105 795 102
    Glenn Wright 1924 662 153 111 744 102


    I know many of you had an inkling that Joe Carter would take the top spot. He also appears at numbers 8 and 10 (and number 53 for his 1987, 104 for his 1989 season, 110 for his 1993 season, and number 146 for his 1994 season...you get the idea). But given the poor light in which RBI have been cast in recent years, perhaps surprisingly only 17 times (a little over 1%) has a player ever driven in 100 runs while not being at least league average. So while getting to 100 RBI doesn't ensure that the hitter is an elite offensive performer, it is a pretty good proxy. Put in another way, one needn't be a great hitter to accrue 100 RBI but great hitters often get to 100 RBI. And so in the absence of better metrics it's not surprising that 100 RBI became shorthand for a great offensive performance. This is illustrated by the fact that the "average" 100 RBI man had NOPS/PF of 125 and the histogram belows which shows their distribution:



    Contributing to the idea that RBI equals greatness is the ongoing debate over the significance and prevalence of clutch hitting. A player with alot of RBI is often automatically assumed to be a clutch performer as Joe Carter was.

    That said, given that we now have much more granular means (with OPS actually being on the lower end) of estimating the run contribution of individual hitters, that usage should wane some although it may take generational turnover to bring about its demise. For a little deeper perspective on traditional and more modern methods of gauging a player's contribution see chapter 1 of Baseball Between the Numbers.

    But in getting back to the question at hand, perusing the list you see a few factors that certainly play into reaching the century mark:

  • Performance - As mentioned above there is no doubt that in large part getting to 100 RBI requires a strong performance. From the graph above (the pink cumulative line that uses the y-axis on the right) you can see that fully 75% of those who have driven in 100 runs were 15% or more above league average and 60% were 25% or more above average.


  • Park - Vinny Castilla and Jeff Cirillo in the top 20 show that playing in a park where lots of runs are scored certainly helps, and of course by adjusting for park we don't give them any benefit


  • Era - Twelve of the top 20 players either played in the 1930s or since 1993 which were the two highest scoring eras in modern baseball history. Just like playing in a park where runs are more plentiful allows lesser hitters to drive in more runs, playing in an expanding offensive environment devalues the 100-RBI mark.


  • Teammates - Certainly the reader makes a good point about teammates having to be on the bases. You could probably make a case that Paul O'Neil in 2000 with the Yankees, Marv Owen for the Tigers in 1936, Glenn Wright with the Pirates in 1927, and Bill Buckner with the 1986 Red Sox all fall into this category where the individual was part of a strong offensive team from top to bottom.


  • Lineup Position - It probably comes as no surprise that many of the players on this list and that accrue 100 RBI generally are middle-of-the-order hitters. It probably comes as a bit more of surprise that, as shown in the graph below, the number three position in order actually hits with relatively fewer runners on base than does any other lineups positions save the leadoff and second spots in the order.



  • Plate Appearances - More generally the latter two contributing factors as well as this one fall into the category of opportunity. A player has to come to the plate often enough to reach the 100 RBI mark. Probably no one in this list better exemplifies these is Ruben Sierra's 1993 performance with the Oakland A's. In that season Rickey Henderson hit leadoff for half the year and he hit third in an AL lineup which increases the opportunities for the third hitter and racked up almost 700 plate appearances. On the average, the 100 RBI men had 651 plate appearances. Yes Rudy York did drive in 103 runs in just 417 plate appearances for the 1937 Tigers but all told just 213 players (14%) have ever driven in 100 runs while not coming to the plate at least 600 times.


  • So will Carlos Delgado get to 100 RBI and if so what does it mean? Speaking only in generalties and knowing only that about this performance, we'd have to guess that he was a pretty good hitter. However, that doesn't completely rule out the possibility that his park, era, teammates, lineup position, and playing time all conspired to his breaking the 100 RBI barrier.

    Thursday, May 24, 2007

    Deep Data Dive

    As promised yesterday my column on Baseball Prospectus this morning dives deeper into the PITCHf/x data tracked by the 2007 version of Gameday (a new update was released on May 10th and is much more performant).

    In this article I take a look at the velocity and location data that includes over 40,000 pitches and discover that given a one-inch margin of error the system agrees with umpires to the tune of 90%. Not bad and very similar to the QuesTec results published by Robert Adair in an article titled "Cameras and Computers, or Umpires?" that was published in Volume 32 of SABR's The Baseball Research Journal.

    Wednesday, May 23, 2007

    A Little Light Reading

    Just a few things to chew on...

  • Interesting article by Paul Swydan on the Rockies use of information technology. There is more in the Rockies magazine that they sell at the ballpark with some excellent photos of the custom software they use.


  • Interesting quotes from Tony LaRussa on scoring in multiple innings increasing the probability of winning. As Phil points out, however, simply scoring more runs also increases the probability of winning dramatically and so the quesiton is really which is the more fundamental thing to strive for - scoring in multiple innings or putting together an offense that can score more runs in the aggregate. It seems to me that the former is just an effect or outgrowth of the latter.


  • Here are seven reasons why sabermetrics helps build a better ballgame by Nate Silver.


  • An excellent and succint analysis of this April's weather and it's impact on run scoring. It's all about the temperature. I'll have more to say about this in my Baseball Prospectus column tomorrow with regards to pitch velocity.


  • In my last chat I said:
    A couple weeks ago I overheard one beat writer mention repeatedly that so-and-so was a "four-A" player indicating that regardless of what he's doing in AAA (this guy has an OPS of 1.25 thus far and a pretty good track record) he'll never make it in the majors. One of the things that performance analysis has revealed is that for the most part there is no magical line between the minors and majors as evidenced by a certain measure of predictability as players cross that threshold. To me, the way we as fans and the industry itself views the minors versus the majors in terms of attention, compensation, media exposure etc. is responsible for that view.

    And the so-and-so was...this guy.


  • I had never seen this before but the British Library has a wonderful way of viewing some of their material. They also have a new beta that uses Microsoft Silverlight.
  • Thursday, May 17, 2007

    The Dismal Science?


    My column this morning on Baseball Prospectus is actually a review of the book The Baseball Economist: The Real Game Exposed by J.C. Bradbury. Like many others I've enjoyed Bradbury's commentary on his site Sabernomics.

    In short, I recommend the book and really appreciated both the wide range of sabermetric studies but more so how they're couched in economic concepts. That chapters on performance enhancing substances and baseball's monopoly power are especially strong. I did have a few quibbles with some of the studies but you can read more about that in the column...

    Wednesday, May 16, 2007

    Mad Dog

    Greg Maddux is off to a nice start in 2007 with a 3-2 record and 3.20 ERA in 50 2/3 innings having given up only 45 hits and 7 walks. It turns out that of his eight starts this season five have been recorded more or less completely by the Enhanced GameDay system. In all, that's 358 pitches, 164 to right-handers and 194 to left-handers. Just fiddling around with some of the data today here are some random observations.

  • The fastest pitch leaving his hand was 94 mph. He threw the pitch to Garrett Atkins on April 6th in the top of the third inning. The pitch was called a ball. That pitch was also the fastest when it reached the plate at 83 mph.


  • The slowest pitch he threw was 71.5 mph to Kazuo Matsui in the 6th inning of that April 6th start. That pitch crossed the plate at 62.6 mph before Matsui hit a ground ball to third for an infield single.


  • His average velocity out of the hand was 85 mph and crossing the plate was 75.2 mph. But what's most amazing is that the standard deviation of his muzzle velocity was just 2.86 mph. By comparison, of pitchers who have thrown 100 or more pitches in 2007 with GameDay watching his pitches have varied the least. Jason Schmidt was close at 2.95 mph and on the other end Randy Wolf was at 8.85 mph.


  • The breakdown of the outcomes of his pitches were:
    Ball                         102   28.5%
    Called Strike 79 22.1%
    In play, out(s) 61 17.0%
    Foul 50 14.0%
    Swinging Strike 24 6.7%
    In play, no out 19 5.3%
    In play, run(s) 6 1.7%
    Foul Bunt 5 1.4%
    Pitchout 4 1.1%
    Foul (Runner Going) 3 0.8%
    Ball In Dirt 2 0.6%
    Swinging Strike (Blocked 2 0.6%
    Missed Bunt 1 0.3%
    358
    Not Surprisingly he doesn't get many swinging strikes.


  • The break down of his pitches against lefties and righties is shown in the two graphs below (pictured from the perspective of the pitcher).


    Against lefties he clearly stays on the outer half and besides how few pitches he leaves in the middle of the plate, it would appear he gets a pretty good number of calls on balls that are actually outside the strike zone. Cory Schwartz was kind enough to answer a few questions on the system over at The Book blog recently and said that through testing they're confident that the tracking is within 2 inches with regards to a pitcher's release point and within 1" as the ball crosses the plate. Even with a 1" margin of error and remembering that the data points I'm using are much smaller than an actual baseball, that's still a fair number of pitches that Maddux seems to get the benefit of the doubt on.



    Against righthanders he seems to catch more of the plate and interestingly doesn't seem to pitch as much down in the zone.

  • Tuesday, May 15, 2007

    The Gospel of Pronation

    At last year's SABR convention I had the opportunity to listen to Mike Marshall, former Cy Young winner and PhD, preach the gospel of injury avoidance through his rather unique pitching mechanics and instruction. At the time I noted how he's not taken seriously by the industry and now Jeff Passan over at Yahoo Sports has written an excellent article on Marshall (or "Doc" as his disciples call him) and his Pitching Research and Training Center in Florida north of Tampa. What's particularly interesting is the accompanying video of Marshall protege Jeff Sparks who once pitched for Tampa Bay and who still travels to Marshall's complex in hopes of catching on somewhere.

    In the video you'll see the extreme pronation of the wrist in both the fastball and curveball motions as well the screwball which Marshall preaches will effectively eliminate elbow injuries requiring Tommy John surgery. The video is high speed and so shows the motion pretty clearly. You'll also want to check out Passan being interviewed by Will Carroll on BP Radio from last weekend.

    In the end it would be interesting if a team would send a few borderline pitchers Marshall's way in order to see if there's anything to his claims about injury avoidance and additional velocity. Those who attend his center are certainly true believers but the rest of us won't be until there are some documented successes.

    Monday, May 14, 2007

    Charting Sammy

    Along with the Mother's Day festivities I had a fun weekend collecting and analyzing Enhanced GameDay data. What that allows is for analysis of individual pitchers and hitters. For example, below is a graphic (click to make larger) of all 340 pitches that have been tracked for Sammy Sosa this season. Since Texas is one of the parks in which the system is running and since others where it has been running the longest include Chicago (AL), Oakland, Seattle, and Anaheim, the Rangers tend to have more of their games being tracked. New parks will be added as the season goes along and all told there are now 13 parks in which the system has collected some data with Detroit, St. Louis, Washington, and Colorado (yeah!) being add in the last few days.

    The strike zone that is drawn is an average of the strike zone for each plate appearance. Obviously these graphs can be broken down further by count, pitch type, and especially handedness of the pitcher but even so here you can see that when Sammy chases pitches they are often down and away and fouls off a fair number of pitches that inside.

    In any case, look for more of this in the future here and on Baseball Prospectus.

    Saturday, May 12, 2007

    The Proper Goal

    A well-reasoned article by George Will on Barry Bonds and his upcoming "achievement". He covers all the relevant bases in discussing why it is that baseball seems to be held to a higher standard than other sports, a little of their history in sports other than baseball, the difficulty in drawing the line, and the confluence of other factors in baseball that makes it difficult to detect performance enhancers, and of course the kind of circumstantial evidence that I discussed in my 2005 article on the heels of Bonds 704th homerun.

    But my favorite aspect I think is the reminder that Will provides as to just why it is that performance enhancing substances are bad for the game - actually any game. I've often heard talk show hosts and read columnists that argue that players have a right to do whatever it takes to feed their family etc. etc. and who are we to judge and why should we or they care? As an antidote to that kind of thinking Will offers the following:

    Athletes who are chemically propelled to victory do not merely overvalue winning, they misunderstand why winning is properly valued. Professional athletes stand at an apex of achievement, but their achievements are admirable primarily because they are the products of a lonely submission to a sustained discipline of exertion. Such submission is a manifestation of good character. The athlete's proper goal is to perform unusually well, not unnaturally well. Drugs that make sport exotic, by radical intrusions into the body, drain sport of its exemplary power by making it a display of chemistry rather than character. In fact, it becomes a display of some chemists' virtuosity and some athletes' bad character.

    Thursday, May 10, 2007

    Pitch by Pitch

    In my column today on Baseball Prospectus I take a pitch by pitch look at the almost no-hitter of Yankees rookie Phillip Hughes on May 1st using the enhanced GameDay data provided by MLBAM. Joe P. Sheehan over at Baseball Analysts has pioneered alot of the analysis and so you'll want to check out his work as well.

    To me, the interesting aspect of this is in how it will certainly be combined with bio mechanical analysis in order to provide quantitative support for what is today primarily observational. A synthesis of the two worlds will offer insights that neither could provide independently and that's exciting stuff.

    Update: My article actually was published after this one by John Beamer at THT where he looks at the consistency of the data between parks. Obviously, if I had seen this I would have mentioned it but interestingly, his research on Kevin Millwood, who has pitched at five of the eight parks in which the Enhanced GameDay system is installed, suggests that there may be some park bias in play. Particularly he sees this in speed and location (for example location of release point). Both of course become much more useful when you can compare them from game to game. If indeed the system has built-in biases, either adjustments will have to be made internal to the system (if possible since a variable like mound height may be a contributing factor as may atmospheric conditions although Beamer finds that unlikely) or those using the data will have to make the adjustments themselves. The second option is certainly not appealing.

    Saturday, May 05, 2007

    Lightning


    In the spring of 2004 my wife and eldest daughter had the chance to travel to England so that I could attend a conference. Since this was our first visit we planned to pack in as much as we could during the trip and in addition to a quick tour of London that included the British Museum, Westminster Abbey, Trafalgar Square, we headed up to the Yorkshire Dales where the real James Herriott (Alf Wright) practiced. Before making our way to the conference south of London we swung over to Oxford in order to get a look at where C.S. Lewis lived and worked. On a rainy Saturday, with the help of a local man who knows the pastor, we were able to visit the Anglican church near Lewis' home where he worshipped for all of his adult life and where he was buried in the small church cemetery. Inside the church there are several remembrances of Lewis including a very nice window depicting a scene from Narnia and a marker on the pew where Lewis and his brother Warnie regularly sat. That's my daughter sitting in the seat that Lewis typically occupied.



    All of this came to mind as I was reading Lewis' essay "On Church Music" published in Christian Reflections the other night. The essay attempts to navigate the controversy of "high" versus "low" church music with high meaning more serious music sung by a trained choir and low meaning hymns sung by the congregation. As Lewis often does he sees in both the opportunity for Christians to "humbly and charitably" sacrifice by either indulging the "lusty roar of the congregation" or remaining silent and respectful of that which one doesn't understand. In that way "Church Music will have been a means of grace; not the music they have liked but the music they have disliked." For his part Lewis was more skeptical that any music is very religiously relevant and even in this essay we find one of his famous quotes that "What I, like many other laymen, chiefly desire in church are fewer, better and shorter hymns; especially fewer."

    Given the admonition that at the very least music is a chance at sacrifice and a means of giving grace, I'm somewhat hesitant to proceed. And yet I'll share what I found to be my own interesting reaction to one of the praise songs we sometimes sing in our church. The song is called "Indescribable" by Chris Tomlin, the first two verses and the chorus of which go like so;

    From the highest of heights to the depths of the sea
    Creation's revealing Your majesty
    From the colors of fall to the fragrance of spring
    Every creature unique in the song that it sings
    All exclaiming

    Indescribable, uncontainable,
    You placed the stars in the sky and You know them by name.
    You are amazing God
    All powerful, untamable,
    Awestruck we fall to our knees as we humbly proclaim
    You are amazing God

    Who has told every lightning bolt where it should go
    Or seen heavenly storehouses laden with snow
    Who imagined the sun and gives source to its light
    Yet conceals it to bring us the coolness of night
    None can fathom


    Now, this song is clearly extolling the power and majesty of God and has a melody and cadence that heightens the emotions and from what I observe is clearly one of the favorites of the congregation. That said, each time the second verse beginning with "Who has told every lightning bolt where it should go..." begins I cringe just a little.

    To me, these lyrics that God has an interest in directing individual lightening bolts harkens back to the early 18th century when lightning was viewed as a means of God's displeasure and/or the work of demons which, along with good spirits, were thought to have filled the air. In those days as a storm approached church bells would be rung in order to ward off the bolts as in the words of St. Thomas Aquinas "The tones of the consecrated metal repel the demon and avert storm and lightning". As you can imagine this wasn't an effective strategy and as Walter Isaacson related in Benjamin Franklin: An American Life, "during one thirty-five year period in Germany alone during the mid-1700s alone, 386 churches were struck and over a hundred bell ringers killed." Of course Franklin's invention of the lightning rod in 1752 began to change this way of thinking although some theologians resisted its use fearing that it would be impious to resist the hand and judgment of God. In one particularly tragic event over 3,000 people were killed in 1767, some fifteen years after Franklin's invention when the church of San Nazaro in Venice was struck igniting gunpowder being stored in the church.

    What I find interesting in all of this is that in the praise song lightning is viewed as just another display of God's creativity and power along with the flowers and stars. And yet this is a power that has been tamed by the intervention of man and so in the song we can stand back and admire it without fear of consequences or judgement. While congregations 300 years ago may indeed have also looked at lightning as a display of God's power, they would additionally have looked at it as an instrument of God's judgement. The mention of lightning in a hymn would have conjured up far different notions to them than it does to us. One wonders whether including the other sentiments expressed in Tomlin's song would even have seemed appropriate. Beyond that it seems just silly to praise God in worship songs for directing lightning bolts when we do our darnedest to intercept and redirect them whenever possible. What if the word lightning in the song were replaced with "tornado"? Would we really sing "Who has told every tornado where it should go..."? I just don't think most modern Christians think God uses natural events to punish people and so I find it somewhat surprising that the concept is so blatant in a song that I've heard sung in more than one evangelical church in the last decade. Unless I'm wrong one would hope church leaders would do a better job of ensuring that what is sung and said in the service lines up with current Christian belief. To that end, I wonder what seekers attending services think when they see lyrics like this?

    The point was also hit home a few weeks ago when we also had a guest worship leader who sang a song he had written that included the line "to the God of lightning." Before the song he relayed the context of its writing which included sitting with his eight-year old daughter on the back porch watching the thunderstorms roll over the eastern Colorado plains. His daughter was awed by the display and before heading to bed asked to linger and then prayed that God would send another blast of lightning and thunder. Again, 300 years ago that would have been unfathomable.

    To me, remembering the terror and destruction that lightning has caused along with how the church viewed it historically, I find it anachronistic and intellectually vacuous to sing praise songs in which we in effect blame God for a natural phenomenon.