Lonnie Chisenhall has been very good at hitting baseballs. Whether he is good at hitting baseballs (i.e.: whether ‘being good at hitting baseballs’ defines his physis) is very slightly more debatable, but we have statistics that tell us that Lonnie has been, since the start of the season, good at hitting. His .451 wOBA, his .385 batting average, his wRC+ of 195 – all of these statistics are important, central in asserting the controversial claim that Lonnie is kinda good at this.
But there comes a time during the adolescent years of Microsoft Excel 2000 (it’s already 15!) when they tire of computing real and important stats like xFIP and instead take to computing frivolous and useless stats. Judging by the Avenged Sevenfold blaring from my Excel 2000 (?), it seems that, like any other teenager, it has created a tremendously stupid statistic.
Fielding-Independent Pitching, or FIP, is unambiguously a very useful stat. Given how many strikeouts, walks, and home runs a pitcher has allowed, it tells a complete narrative of what that pitcher’s ERA should look like given a reasonable defense behind that same pitcher. It’s not the most useful pitching predictor – that would go to either SIERA, kwERA, or xFIP – but it’s good at explaining what the pitcher, rather than the defense (or to a lesser degree, the batter) did right or wrong. FIP is better than Game Score, and sure as hell better than WHIP or any other new HyperCalvinist metrics that, with all the farcical self-importance of a Congressional session, believe that raw hits allowed are substantially influenced by the pitcher beyond strikeout rates.
(They’re not. If you were wondering.)
Contrasted to the usefulness of pitcher FIP, Batter FIP is not a useful evaluative tool. Whereas a pitcher cannot seriously control BABIP against or extra base hits against, these traits are much more within the control of the batter. There are real, sustainable differences between major-league quality batters in each of these. Carlos Santana will not have the same career BABIP as a Michael Bourn. There are tangible skill differences that effect this difference.
What follows is a table of Batter FIP. It would have been called Fielding Independent Batting, but FIB is at least a semi-serious evaluative tool for hitters. This term, Batter FIP, is a very clunky phrase, which same clumsiness represents the haphazard and whimsical nature of this made-up statistic. Innings Pitches are (PA-OBP*PA)/3, or Outs/3. This does not account for occasions in which a batter reached on an error. Such are the sacrifices made.
| Batter | PA | HR | BB | SO | OBP | HBP | IP | Batter FIP |
| George Kottaras | 13 | 3 | 3 | 2 | 0.583 | 0 | 1.81 | 27.40 |
| Michael Brantley | 268 | 10 | 23 | 25 | 0.373 | 3 | 56 | 5.87 |
| Carlos Santana | 237 | 7 | 47 | 48 | 0.338 | 1 | 52.3 | 5.71 |
| Lonnie Chisenhall | 181 | 7 | 9 | 25 | 0.429 | 5 | 34.5 | 5.46 |
| Nyjer Morgan | 52 | 1 | 7 | 6 | 0.429 | 0 | 9.9 | 5.27 |
| Jason Giambi | 48 | 2 | 4 | 8 | 0.229 | 1 | 12.3 | 5.08 |
| Jason Kipnis | 159 | 3 | 21 | 23 | 0.352 | 1 | 34.3 | 4.77 |
| David Murphy | 229 | 5 | 20 | 29 | 0.345 | 0 | 50 | 4.39 |
| Asdrubal Cabrera | 257 | 6 | 20 | 45 | 0.327 | 5 | 57.7 | 4.14 |
| Yan Gomes | 207 | 7 | 14 | 45 | 0.324 | 1 | 46.6 | 4.04 |
| Nick Swisher | 218 | 3 | 29 | 49 | 0.312 | 0 | 50 | 3.61 |
| Justin Sellers | 21 | 0 | 3 | 4 | 0.316 | 0 | 4.79 | 3.26 |
| Mike Aviles | 174 | 3 | 6 | 25 | 0.29 | 0 | 41.2 | 3.22 |
| Ryan Raburn | 127 | 1 | 10 | 30 | 0.268 | 0 | 31 | 2.50 |
| Michael Bourn | 209 | 2 | 14 | 49 | 0.329 | 0 | 46.7 | 2.41 |
| Jesus Aguilar | 20 | 0 | 3 | 6 | 0.3 | 0 | 4.67 | 2.41 |
| Jose Ramirez | 25 | 0 | 0 | 3 | 0.08 | 0 | 7.67 | 2.27 |
| Elliot Johnson | 20 | 0 | 0 | 7 | 0.105 | 0 | 5.97 | 0.70 |
Source: FanGraphs
There might be some interest in comparing these numbers to the numbers of real pitchers. Elliot Johnson, per Batter FIP, is Koji Uehara at his most frightening. Jose Ramirez, with his 2.27 Batter FIP, is Zack Greinke during the latter’s unhittable 2009 campaign. Mike Aviles is Danny Salazar last year. Conversely, Jason Kipnis is Danny Salazar this year. At the final extreme, George Kottaras is a very, very homer-prone pitcher on a very, very bad day – or, in other words, Zach McAllister’s home outing against Oakland. It was a very rough outing.
As has been noted, this statistic isn’t particularly serious, but that doesn’t mean there aren’t interesting tales to be drawn. Michael Bourn’s Batter FIP of 2.41 would indicate that he’s being dominated at the plate – yet he’s batting .281. Ultimately, this quite faithfully reflects Bourn’s career – a low walk, low power, high strikeout batter whose value as an offensive player is not derived from the two beneficial True Outcomes. His offensive value comes from his BABIP, which over his career has been substantially higher than league average. Even his 2014 BABIP, at a well-above-average .366, is still not the highest of his career. On the opposite end of the spectrum, we see a player like Santana, whose value is drawn largely from his elite ability to draw walks and his rather-good home run power. An average BABIP for Santana would make him an excellent offensive player, but, of course, that’s precisely the challenge.
Batter FIP confirms what we knew about Bourn and Santana – nothing new was revealed, but Batter FIP offers a different articulation of the same. On the other hand, Jason Kipnis is an extremely interesting case. His Batter FIP of 4.77 indicates that his Three True Outcome profile is quite favorable even despite (predictably) depressed 2014 power. It’s true that Kipnis drew walks well in 2013, but his strikeout rate was below average. In 2014, however, we’ve seen an unambiguously positive shift for Kipnis in 2014; he’s seen his already impressive walk rate increase and his strikeout rate decrease, the latter to an quite-low 14%. These facts are incredibly compelling, given that in 2013, his offensive value was driven largely by his .345 BABIP that carried with it some good power; Kipnis’s BABIP in 2014, however, is substantially below average at .279, and his Isolated Power is almost identical to that of Brantley.
Kipnis’s Batter FIP should be extremely encouraging in this sense. His batting profile in 2013 was that of a high-average, high-power batter who had occasional strikeout problems, and Kipnis’s ability to hit line drives to the whole field suggested that, while his BABIP was high, it could quite easily be sustainably above-average. Kipnis’s BABIP is not hampered in the same sense as Santana’s; Santana, for better or worse, is a dead pull hitter from the left side of the plate. The fact that Kipnis has been able to sustain a high Batter FIP indicates that when Kipnis’s BABIP does bounce back to either average or above (and it will), his offensive ceiling could be quite high.
Whimsical statistics are just that. They’re synthesized for amusement and don’t tell the whole story of a player. Batter FIP, particularly, gives a decisively non-holistic narrative. Yet it’s always possible that, when faced with the distortion of reality, one can see things from a completely new perspective.
Cleveland Sports Insiders 