Links: Tribe Report (CLE)
Here's a statement that shouldn't surprise you: I'm a fan of sabermetric analysis. Numbers are awesome. Logic and objectivity are preferable to soap boxes and subjectivity. Unfortunately, most mainstream writers and many online blogs don't provide me with the saber-friendly content I want to read. And I often wonder why so many people refuse to write with a sabermetric slant.
Thanks to chuckb over at viva el birdos, I now realize I've been making an an incorrect assumption. Writers aren't choosing not to take a sabermetric approach -- they often just don't know how (or what to write about).
Therefore, I'm going to start a new series here at Beyond the Box Score called Saber-Friendly Blogging 101. Under a yet-to-be-determined schedule, I'll be presenting a variety of article ideas (using sabermetric principles) that bloggers can adapt into posts for their team-specific blogs.
I'll provide the concept and background information. I'll point out where you can find the necessary data (or provide it myself). I'll answer questions in the comments. You simply provide the analysis for your favorite team.
As an added bonus, this project will hopefully end up serving as a home base for baseball fans who would like to read related saber-friendly content written by die-hard fans of many different teams. So if you use an article idea I suggest, let me know, and I'll provide a link to it from the original BtB post. (A link back to the BtB article in your piece will facilitate the sharing.)
Is this something you and your blog would be interested in doing? Do you have a way to make it better? Do you have a specific topic you'd like help tackling? If so, let me know in the comments, or email me.
And, because procrastination is for losers, here's the first installment, maybe a bit on the basic side, or maybe not...
BABIP -- batting average on balls in play. BABIP is just the percentage of batted balls that turn into hits, but those five letters are often interpreted as an instant argument for why a pitcher was lucky or unlucky in regards to his ERA. Why?
Pitchers have a lot of control over certain outcomes, namely strikeouts and walks. They have a modest amount of control over others, like allowing homeruns. But when the ball is put into the field of play, there isn't a strong difference in the abilities of MLB pitchers to induce outs versus hits. For established MLB pitchers, the range of talent levels on BABIP falls mostly between .290 and .310. Therefore, BABIPs below .290 help bring a pitcher's ERA below what it "should" be, thanks to good fielding, park effects, and luck. BABIPs above .310 inflate a pitcher's ERA.
Let's give this a quick test. Among pitchers with 120 innings in both 2007 and 2008, here are those with the highest BABIPs in 2007, along with their 2008 BABIPs, and 2007 and 2008 ERAs. See a pattern? (Hint: the high 2007 BABIPs regress strongly towards .300 in 2008, and the ERAs tend to come down significantly. Yes, there are exceptions, like Kevin Millwood and Scott Kazmir, but holding steady at worst is fine when most of the time the trend holds true.)
| Name | BABIP 07 | ERA 07 | BABIP 08 | ERA 08 |
| Scott M Olsen | .341 | 5.81 | .258 | 4.20 |
| Edwin Jackson | .341 | 5.76 | .302 | 4.42 |
| Kevin Millwood | .340 | 5.16 | .355 | 5.07 |
| Mike Mussina | .340 | 5.15 | .321 | 3.37 |
| Scott E Kazmir | .333 | 3.48 | .265 | 3.49 |
| Felix A Hernandez | .333 | 3.92 | .314 | 3.45 |
| Brian Burres | .333 | 5.95 | .322 | 6.04 |
| Odalis Perez | .332 | 5.57 | .316 | 4.34 |
| Jose Contreras | .326 | 5.57 | .294 | 4.54 |
| Andy Sonnanstine | .326 | 5.85 | .302 | 4.38 |
| Jorge A de la Rosa | .325 | 5.82 | .319 | 4.92 |
| Ervin R Santana | .324 | 5.76 | .289 | 3.49 |
So what does BABIP say about next year? Here are the twenty pitchers with the highest BABIPs in 2008 with at least 120 IP. You would expect these guys to post much better ERAs in 2009, all else being equal.
| Name | IP | ERA | BABIP |
| Kevin Millwood | 168.7 | 5.07 | .355 |
| Ian D Snell | 164.3 | 5.42 | .351 |
| Livan Hernandez | 139.7 | 5.48 | .345 |
| Carlos Silva | 153.3 | 6.46 | .342 |
| Nate Robertson | 168.7 | 6.35 | .341 |
| Garrett A Olson | 132.7 | 6.65 | .335 |
| Andy Pettitte | 204.0 | 4.54 | .333 |
| Manny Parra | 166.0 | 4.39 | .327 |
| Brandon Backe | 166.7 | 6.05 | .324 |
| Doug Davis | 146.0 | 4.32 | .322 |
| Brian Burres | 129.7 | 6.04 | .322 |
| Mike Mussina | 200.3 | 3.37 | .321 |
| Jorge A de la Rosa | 130.0 | 4.92 | .319 |
| Kenny Rogers | 173.7 | 5.70 | .318 |
| Jonathan O Sanchez | 158.0 | 5.01 | .317 |
| Javier Vazquez | 208.3 | 4.67 | .316 |
| Odalis Perez | 159.7 | 4.34 | .316 |
| Zach Duke | 185.0 | 4.82 | .315 |
| Josh Beckett | 174.3 | 4.03 | .315 |
| A.J. Burnett | 221.3 | 4.07 | .314 |
And here are the twenty pitchers with the lowest BABIPs in 2008 with at least 120 IP. These guys should see their ERAs rise in 2009, all else being equal.
| Name | IP | ERA | BABIP |
| Justin Duchscherer | 141.7 | 2.54 | .235 |
| David T Bush | 185.0 | 4.18 | .236 |
| Armando Galarraga | 178.7 | 3.73 | .236 |
| Tim Wakefield | 181.0 | 4.13 | .239 |
| Shaun M Marcum | 151.3 | 3.39 | .245 |
| Gavin C Floyd | 206.3 | 3.84 | .256 |
| Gregory Smith | 190.3 | 4.16 | .256 |
| Scott M Olsen | 201.7 | 4.20 | .258 |
| Daisuke Matsuzaka | 167.7 | 2.90 | .258 |
| Cole Hamels | 227.3 | 3.09 | .259 |
| Jeremy Guthrie | 190.7 | 3.63 | .259 |
| Tim Hudson | 142.0 | 3.17 | .262 |
| Todd Wellemeyer | 191.7 | 3.71 | .264 |
| Scott E Kazmir | 152.3 | 3.49 | .265 |
| Joe Saunders | 198.0 | 3.41 | .266 |
| John E Lannan | 182.0 | 3.91 | .266 |
| John Maine | 140.0 | 4.18 | .266 |
| Ted Lilly | 204.7 | 4.09 | .270 |
| Carlos Zambrano | 188.7 | 3.91 | .270 |
| Matt Garza | 184.7 | 3.70 | .270 |
All data taken from The Hardball Times. To get BABIP, simply subtract DER from 1.
Ideas for your team blog:
- Explain what BABIP measures and why it matters.
- Present 2008 BABIP data for pitchers with significant innings and discuss which of them should see their ERAs rise or fall in 2009.
- Present the team BABIP and if it's significantly different from .300, discuss possible explanations: park, defense, luck, etc.
- Get historical. Find some pitchers over the last ten years with large ERA swings from year to year and see if BABIP is the cause. BABIP can also often explain one-year wonders.
- Take a look at potential trade and free agent targets and see if their 2008 ERAs are inflated or deflated by BABIP.