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Among the Rays top prospects set to debut in 2018, Jake Bauers looks to be a possible (if not probable) long term solution for the Rays at first base, but one concern that you might have while reviewing Triple-A performance is his batted ball profile and, in particular, his extreme infield fly ball rates.
Watching games it never seemed that he hit weak fly balls in the infield, but looking at the data the statistic IFFB% really stands out:
Jake Bauers Flyball Profile
| Year | Level | PA | FB% | IFFB% | True IFFB% |
|---|---|---|---|---|---|
| Year | Level | PA | FB% | IFFB% | True IFFB% |
| 2015 | A+ | 249 | 42.5% | 16.9% | 7.2% |
| 2015 | AA | 285 | 32.9% | 25.0% | 8.2% |
| 2016 | AA | 581 | 37.9% | 22.2% | 8.4% |
| 2017 | AAA | 575 | 33.7% | 20.6% | 6.9% |
IFFB% is a percentage of flyballs, and True IFFB% is a percentage of balls in play. In 2017 the major league average was 35.5% flyball rate, 9.6% IFFB%, and 3.4% True IFFB%.
Importantly, infield fly balls are a killer to BABIP. According to the Statcast data at baseballsavant.mlb.com a popup results in a .023 batting average and .028 slugging percentage. Infield fly balls have to be well placed to land and do almost no damage. The outcome is better than a strikeout, but over 97% of the time it’s the same result.
At first glance, the Bauers infield fly ball rate looks concerning. It is tough to put up an effective batting average when around 20% of your balls in the air are almost automatic outs.
In the context of MLB IFFB% rates, this would be very extreme, as only one player (White Sox outfielder Adam Engel) received over 300 plate appearances with an IFFB% rate over 20% in 2017 (21.3% IFFB%). He produced a 37 wRC+ on the season.
However, any concerns about IFFB% can be assuaged. Bauers rates have to be taken in the context of minor league data, which Alex Chamberlain wrote about yesterday in his article on MiLB IFFB% rates in the high minors at rotographs.
Chamberlain found the rate when translated to the majors was a little lower than half, coming in at a multiplier of 44-49%. Over 174 qualified batters that he back-tested, Chamberlain found the average difference was only 0.4% higher than expected when adjusted to the MLB rate.
Chamberlain’s Findings
| Season | MLB | AAA | AA |
|---|---|---|---|
| Season | MLB | AAA | AA |
| 2013 | 9.7% | 19.8% | 20.7% |
| 2014 | 9.6% | 19.5% | 19.4% |
| 2015 | 9.5% | 20.3% | 21.5% |
| 2016 | 9.7% | 20.6% | 20.9% |
| 2017 | 9.6% | 20.2% | 21.2% |
Using his research, the expected IFFB% of Bauers in 2017 drops to 10-11% In the majors, which is slightly above average but nothing to be overly concerned about (this also lowers his True IFFB% from 6.9% to an expected 3.5%).
It is unknown what the cause of this discrepancy between major league performance and minor league IFFB% rates, but I suspect it likely comes down to two different sources using different definitions of what an IFFB really is.
So should you be perusing Fangraphs and wondering how much trouble the Rays’ likely longterm answer at first base will facein his transition to the majors this season, fear not the popup.