Introduction to IFFB+ and IPO+: adjusting IFFB for park factors

With the recent murmurs that IFFB should be included in ERA estimators because of its similar run value to strikeouts -- many, including myself have found deficiencies in the notion of comparing K% to IFFB%.

For one, IFFB% is affected highly by foul area dimensions and catcher mobility behind the plate. Meanwhile, K% is mainly in the hands of the pitcher and can be viewed as a repeatable skill year-to-year that is not as dependent on park factors.

Not to mention, the year-to-year R^2 is very small at .19 and at an r of .40 for IFFB. We can assume because of the statistical noise year-to-year -- that when a pitcher moves from home park to away park -- his IFFB% would be highly affected by the move; more so than his ability to strike batters out. If we are to use IFFB% in ERA estimators, it would be wise to consider park factors and league averages so that we get beter insight of the pitcher's skill to "pop batters up".

Consider this: When we look at FIP we often look at it in a descriptive and predictive way.

In a descriptive frame of mind, including IFFB% makes sense -- as we are broadening the coverage of skills that the pitcher exhibited season-to-season. But due to the statistical noise year-to-year -- it does not make sense to include IFFB% because it will at least harm its predictability, and perhaps mar its accuracy.

One misnomer about IFFB% is that it is not the percentage of infield fly balls, but the percentage of infield flys per fly-balls. Even as simply as multiplying IFFB% by FB% would instantly create a better metric -- doubling the R^2 of the metric from 19% to 44% -- a very large and substantial improvement which was pointed out in this post by Steve Staude. IFFB%*FB% would yield the amount of infield fly-balls hit per balls in play.

Given this information, lets move on to creating a comprehensive IFFB+ and what we will call IPO+(Infield Pop-Outs) -- which is the statistic will will create from FB%*IFFB%.

Creation of IFFB+ and IPO+

To begin we will take all pitcher seasons since 2002 to 2012 with at least 150 IP, and at least 2 seasons with the team that they are with-- so to localize variations from park to park while creating the statistic:

(IFFB% / 10.4%)*100 = IFFB+

We will calculate the IFFB+ stat just like OBP+ but in order to account for park factors we will do something similar:

((IFFB+) / IFFBpf)*100

(Note: IFFBpf is the park factor)

Now with this park factor proportion we will take the IFFB+ and the park factor proportion and find the average of their sum. Instantly, we have a park-factored IFFB+:

((IFFB+) + IFFBpf)) / 2

Meanwhile we will create IPO+ in the same fashion -- however, we will use IFFB%*FB% instead of IFFB%.

((IFFB%*FB%)/3.7%))*100 = IPO+

The result is unadjusted IPO+, "infield pop up plus". Briefly we will adjust for park factors:

((IPO+) / (IFFBpf))*100

Lastly we add the sums of the park factor and the unadjusted:

((IPO+) + (IPO+pf))/2

Now we have the method to calculate IPO+ and IFFB + with park factors.

Results

Here are the 2012 leaders for IPO+ with the corresponding IFFB+:

Num	Name	IFFB	IFFBpf	IFFB+	IPO	IFFBpf	IPO+
1	Bruce Chen	169.63	184.38	177.00	213.10	231.63	222.37
2	Justin Verlander	148.43	144.10	146.26	148.17	143.86	146.02
3	Dan Haren	110.84	116.67	113.75	123.08	129.56	126.32
4	Matt Cain	104.09	106.22	105.15	121.72	124.20	122.96
5	Jason Vargas	108.91	103.72	106.32	123.69	117.80	120.74
6	Cliff Lee	113.73	114.88	114.30	117.68	118.87	118.28
7	Max Scherzer	102.16	99.19	100.68	118.89	115.43	117.16
8	Ian Kennedy	96.38	99.36	97.87	113.78	117.30	115.54
9	Ryan Vogelsong	106.98	109.17	108.07	114.00	116.33	115.16
10	Derek Holland	101.20	102.22	101.71	113.80	114.95	114.37
11	Cole Hamels	114.69	115.85	115.27	112.89	114.03	113.46
12	Gavin Floyd	117.58	115.28	116.43	114.42	112.17	113.29
13	R.A. Dickey	122.40	113.34	117.87	117.05	108.38	112.71
14	Jered Weaver	90.60	95.37	92.98	108.74	114.46	111.60
15	Jon Lester	138.79	136.07	137.43	112.09	109.89	110.99
16	Clayton Kershaw	117.58	113.06	115.32	112.11	107.80	109.95
17	Bronson Arroyo	98.31	94.53	96.42	103.38	99.40	101.39
18	Bud Norris	90.60	90.60	90.60	100.61	100.61	100.61
19	Ervin Santana	93.49	98.41	95.95	97.79	102.93	100.36
20	Jeremy Hellickson	100.24	91.12	95.68	104.56	95.06	99.81
21	Roy Halladay	108.91	110.01	109.46	98.65	99.64	99.14
22	Rick Porcello	152.28	147.85	150.06	96.51	93.70	95.10
23	Kyle Lohse	95.42	93.55	94.48	95.25	93.39	94.32
24	Matt Harrison	106.02	107.09	106.55	91.86	92.79	92.33
25	Jordan Zimmermann	93.49	96.38	94.93	87.56	90.27	88.92
26	CC Sabathia	98.31	96.38	97.34	84.63	82.97	83.80
27	Jon Niese	99.27	91.92	95.60	85.46	79.13	82.30
28	Madison Bumgarner	83.85	85.56	84.71	78.30	79.90	79.10
29	Luke Hochevar	77.10	83.81	80.46	75.68	82.26	78.97
30	Johnny Cueto	97.34	93.60	95.47	80.25	77.17	78.71
31	Felix Hernandez	100.24	95.46	97.85	80.39	76.56	78.48
32	Ricky Nolasco	82.89	79.70	81.29	73.68	70.85	72.26
33	Ivan Nova	74.21	72.76	73.49	67.43	66.10	66.77
34	David Price	88.67	80.61	84.64	67.14	61.03	64.08
35	Mike Leake	80.00	76.92	78.46	59.67	57.38	58.52
36	James Shields	72.29	65.71	69.00	58.78	53.44	56.11
37	Ricky Romero	69.39	71.54	70.47	51.37	52.96	52.17
38	Justin Masterson	67.47	67.47	67.47	47.30	47.30	47.30
39	James McDonald	41.44	43.17	42.31	45.79	47.70	46.74
40	Jake Westbrook	80.00	78.43	79.21	47.11	46.18	46.65
41	Kevin Correia	52.05	54.21	53.13	42.47	44.24	43.36
42	Yovani Gallardo	38.55	37.80	38.17	34.05	33.39	33.72
43	Tim Lincecum	36.62	37.37	37.00	31.12	31.75	31.44
44	Tim Hudson	39.52	41.16	40.34	27.92	29.09	28.51

Here we see that Bruce Chen, had the best IPO+ last year despite Kaufman Stadium being one of the worst IFFB parks with a factor of 92. For this reason, IPO+ recognizes Bruce Chen doing so in one of the hardest environments in the league and gave him a slight park adjustment boost.

Interestingly enough, Porcello was No. 2 in IFFB+ but 22nd in IPO+ given the 103 park factor at Comerica.

Also, check out R.A. Dickey -- given Citi Field's 108 park factor, Dickey's score was adjusted to match the high propensity of pop flys occurring in New York. The Blue Jays had a park factor of 97 last year for IFFB, so it will be interesting to see how his totals react north of the border.

Now let us look at the top IPO+ season's since 2002 in our data set:

Num	season	Name	Team	IFFB	IFFBpf	IFFB+	IPO	IPOpf	IPO+
1	2004	Tim Wakefield	Red Sox	211.07	213.21	212.14	67.54	237.35	236.17
2	2012	Bruce Chen	Royals	169.63	184.38	177.00	194.27	231.63	222.37
3	2011	Jered Weaver	Angels	151.32	159.28	155.30	124.59	217.08	211.65
4	2010	Matt Cain	Giants	158.06	161.29	159.68	109.11	210.77	208.66
5	2009	Johan Santana	Mets	158.06	146.36	152.21	113.30	194.94	202.74
6	2005	Jason Schmidt	Giants	171.56	180.59	176.07	103.64	204.59	199.47
7	2004	Ryan Franklin	Mariners	159.99	156.85	158.42	84.16	197.49	199.47
8	2009	Jered Weaver	Angels	134.93	142.03	138.48	113.28	200.74	195.72
9	2007	Chris Young	Padres	127.22	127.22	127.22	94.98	194.43	194.43
10	2009	Scott Baker	Twins	143.61	148.05	145.83	99.92	195.54	192.61
11	2003	Tim Wakefield	Red Sox	174.45	176.21	175.33	85.20	193.21	192.24
12	2007	Bronson Arroyo	Reds	148.43	148.43	148.43	81.79	182.30	182.30
13	2009	Jeremy Guthrie	Orioles	135.90	141.56	138.73	108.78	184.59	180.89
14	2008	Jered Weaver	Angels	136.86	144.06	140.46	108.31	185.02	180.40
15	2003	Hideo Nomo	Dodgers	167.70	164.41	166.06	75.87	178.43	180.21
16	2003	Barry Zito	Athletics	150.35	148.86	149.61	57.02	176.16	177.04
17	2006	Cliff Lee	Indians	128.19	129.48	128.83	110.84	175.74	174.86
18	2004	Barry Zito	Athletics	142.64	141.23	141.94	69.39	173.86	174.73
19	2008	Jake Peavy	Padres	164.81	166.48	165.64	106.79	175.53	174.65
20	2005	Cliff Lee	Indians	138.79	144.57	141.68	99.75	177.57	174.02
21	2007	Jarrod Washburn	Mariners	136.86	131.60	134.23	118.37	167.54	170.89
22	2005	Bronson Arroyo	Red Sox	134.93	137.69	136.31	82.10	168.34	166.66
23	2005	Tim Wakefield	Red Sox	141.68	144.57	143.12	114.27	167.84	166.16
24	2008	Ervin Santana	Angels	138.79	146.09	142.44	92.69	170.01	165.76
25	2011	John Lackey	Red Sox	159.03	155.91	157.47	126.61	163.51	165.15

No surprise here that Wakefield is at the top -- But Bruce Chen? Bruce Chen had a terrific IPO season last year, that most overlooked.

Findings

IPO+ showed a high year-to-year correlation of 43% -- while IFFB% and IFFB+ had a 19% correlation. Meanwhile, IPO was a better predictor of FIP in Year 2 with a p-score of 0.0328.

So, in conclusion it is better to use IPO+ and IFFB%*FB% in general, if we want to consider the predictive power of IFFB's in ERA estimators.

Being that we use peripherals as not only descriptive tools of how well a pitcher pitched independent of factors that he could not control -- we also use them to look to the future and predict success. In any case, it would seem foolish to mar the predictive power of ERA estimators without first adjusting IFFB's to park factors that affect their variability.

So what do the BtBS readers think about including IFFB in ERA estimators?

Should we include a IFFB metric that is adjusted for park factors and league averages like IPO+?

Or should we include the raw data as to map how the pitcher actually preformed?

You can contact Max Weinstein @MaxWeinstein21 on Twitter