Ranking 2013 Blue Jays Pitches With TIPS

TIPS is an ERA estimator that I have created and can be read about here. TIPS excels in small samples and works on a pitch-by-pitch level. This makes it the perfect tool to analyze different pitches. ERA, xFIP, SIERA, and FIP wouldn’t work for a specific pitch type since they only deal with the end result of a plate appearance. The pitch values displayed on FanGraphs work on a pitch level basis, but they are the ERA (RA9) version of pitch analysis. I have downloaded the Blue Jays 2013 PITCHf/x database (every single pitch!) and have applied TIPS to each pitch for each player.

You can find databases on Baseball Savant and run queries for PITCHf/x. There may be some issues with pitch classification, as an algorithm is used to classify pitches. For example, many say that Steve Delabar throws a splitter. PITCHf/x does not have Delabar throwing a single splitter, but instead splits it into changeups and two-seamers. So take all the classifications with a grain of salt. It is also important to note that the zone determination from the downloaded data from Baseball Savant differs from the one used on Fangraphs. The downloaded data has a smaller zone. This will cause differences in TIPS values (O-Swing%), but I tried to adjust it the best I could.

Here is the leaderboard for Blue Jays pitches in 2013 by TIPS (min 50 pitches):
Legend: FF – Fourseam, FC – Cutter, FT – Twoseam, FS – Splitter, SL – Slider, CU – Curve, SI – Sinker, KN – Knuckleball, EP – Eephus

Santos, SergioSL1290.46
Cecil, BrettSL530.76
Delabar, SteveSL1091.36
Janssen, CaseyCU1091.39
Loup, AaronCH1661.7
Delabar, SteveCH1232.18
Oliver, DarrenSL1802.21
McGowan, DustinSL1072.42
Johnson, JoshSL3012.48
Perez, JuanSL2382.53
Johnson, JoshCU1932.71
Cecil, BrettCU2492.76
Redmond, ToddSL3672.87
Buehrle, MarkCH7712.96
Rogers, EsmilSL6263
Dickey, R.A.EP1283.04
Delabar, SteveFF5863.06
Buehrle, MarkCU2353.14
Morrow, BrandonSL2463.23
Jenkins, ChadCH673.28
Jenkins, ChadSL763.31
Delabar, SteveFT1023.38
Jeffress, JeremyFT1413.4
Perez, JuanFT803.43
Happ, J.A.CU1283.44
Happ, J.A.FT1793.46
Happ, J.A.SL2013.52
Cecil, BrettCH523.61
Redmond, ToddSI6373.64
Happ, J.A.FF9613.71
Dickey, R.A.KN28573.75
Redmond, ToddCH753.8
Dickey, R.A.FF5033.97
Loup, AaronSL1094
Jenkins, ChadFT2044.04
Perez, JuanSI2234.07
Santos, SergioFF1614.1
Morrow, BrandonFS1254.11
Happ, J.A.CH2524.14
Johnson, JoshFF6674.17
Redmond, ToddFF1714.18
Janssen, CaseyFC2924.21
Cecil, BrettSI3144.23
Wagner, NeilFF4434.24
Rogers, EsmilCU2144.24
McGowan, DustinFT804.26
McGowan, DustinFF2344.27
Buehrle, MarkFC6434.35
Johnson, JoshFT1934.35
Loup, AaronFT7464.37
Johnson, JoshCH914.37
Cecil, BrettFF2044.44
Buehrle, MarkFF9824.57
Morrow, BrandonFF4804.64
Janssen, CaseyFF3754.75
Wagner, NeilSL1444.8
Rogers, EsmilFF9284.81
Rogers, EsmilFT4284.84
Jenkins, ChadFF1164.85
Buehrle, MarkFT6555.04
Oliver, DarrenFF3565.09
Oliver, DarrenFT1515.59
Wang, Chien-MingSI2995.72

Wow, Santos’s slider is something else! You may notice, however, that there are many sliders near the top of the list, and a lot of fastballs at the bottom. From this we can conclude that some pitch types are just better at getting results than others. It may also be due to usage. This means we can do some adjustment to see which pitches are best compared to an average pitch of that type. I only have the Blue Jays data currently, so I will use TIPS averages for the Blue Jays of each pitch to compare. Ideally, you would want to use league averages. Here are the Blue Jays averages for each pitch:

FF: 4.32
FT: 4.20
FC: 4.32
SI: 4.42
CH: 3.26
CU: 2.95
SL: 2.64 (this is probably better than league average with Delabar, Santos, and Cecil)

The next table has TIPSAA, which means TIPS Above Average. It’s calculated by subtracting the pitch’s TIPS from the average. It compares how good each pitch is to its specific class. This bumps up the fastball type pitches that would rank lower in the first table. The best example would be Delabar’s fastball. Minimum number of pitches still set to 50.

Santos, SergioSL1290.462.18
Cecil, BrettSL530.761.88
Janssen, CaseyCU1091.391.56
Loup, AaronCH1661.71.56
Delabar, SteveSL1091.361.28
Delabar, SteveFF5863.061.26
Delabar, SteveCH1232.181.08
Delabar, SteveFT1023.380.82
Jeffress, JeremyFT1413.40.8
Redmond, ToddSI6373.640.78
Perez, JuanFT803.430.77
Happ, J.A.FT1793.460.74
Happ, J.A.FF9613.710.61
Oliver, DarrenSL1802.210.43
Dickey, R.A.FF5033.970.35
Perez, JuanSI2234.070.35
Buehrle, MarkCH7712.960.3
Johnson, JoshCU1932.710.24
Santos, SergioFF1614.10.22
McGowan, DustinSL1072.420.22
Cecil, BrettCU2492.760.19
Cecil, BrettSI3144.230.19
Jenkins, ChadFT2044.040.16
Johnson, JoshSL3012.480.16
Johnson, JoshFF6674.170.15
Redmond, ToddFF1714.180.14
Janssen, CaseyFC2924.210.11
Perez, JuanSL2382.530.11
Morrow, BrandonFS1254.110.09
Wagner, NeilFF4434.240.08
McGowan, DustinFF2344.270.05
Dickey, R.A.KN28573.750
Dickey, R.A.EP1283.040
Jenkins, ChadCH673.28-0.02
Buehrle, MarkFC6434.35-0.03
McGowan, DustinFT804.26-0.06
Cecil, BrettFF2044.44-0.12
Johnson, JoshFT1934.35-0.15
Loup, AaronFT7464.37-0.17
Buehrle, MarkCU2353.14-0.19
Redmond, ToddSL3672.87-0.23
Buehrle, MarkFF9824.57-0.25
Morrow, BrandonFF4804.64-0.32
Cecil, BrettCH523.61-0.35
Rogers, EsmilSL6263-0.36
Janssen, CaseyFF3754.75-0.43
Rogers, EsmilFF9284.81-0.49
Happ, J.A.CU1283.44-0.49
Jenkins, ChadFF1164.85-0.53
Redmond, ToddCH753.8-0.54
Morrow, BrandonSL2463.23-0.59
Rogers, EsmilFT4284.84-0.64
Jenkins, ChadSL763.31-0.67
Oliver, DarrenFF3565.09-0.77
Buehrle, MarkFT6555.04-0.84
Happ, J.A.SL2013.52-0.88
Happ, J.A.CH2524.14-0.88
Johnson, JoshCH914.37-1.11
Rogers, EsmilCU2144.24-1.29
Wang, Chien-MingSI2995.72-1.3
Loup, AaronSL1094-1.36
Oliver, DarrenFT1515.59-1.39
Wagner, NeilSL1444.8-2.16

From this table you could bin pitches into minus minus, minus, average, plus, plus plus, or even plus plus plus for Santos’s slider.

Let’s say:
Minus minus: < -1.2
Minus: -1.2 to -0.4
Average: -0.4 to 0.4
Plus: 0.4 to 1.2
Plus plus: 1.2 to 2
Plus plus plus: > 2

So we could arbitrarily say Santos has a plus plus plus slider. Delabar has a plus plus fastball and slider, and a plus change and two seamer. Loup has an average two seamer, with a plus plus changeup, but minus minus slider. Obviously Loup’s slider isn’t that bad compared to a fastball, so the pitch grades are all very arbitrary, and could be subject to small sample size noise.

Here would be the 2013 Blue Jays awards for best pitch:

FF: Steve Delabar
FT: Steve Delabar (HM to Jeremy Jeffress)
SL: Sergio Santos
CU: Casey Janssen
CH: Aaron Loup
SI: Todd Redmond

Let’s focus in on Santos’ slider. The 0.46 TIPS value may seem very low and you might think it is an outlier. That would be incorrect! Santos’ career slider TIPS is 0.41! This is with a sample of 610 pitches, so there isn’t really sample size noise here.

Who are the guys with known plus plus sliders? Kimbrel, Chapman, Holland, Venters, Romo, and Gregerson come to mind. Let’s also throw in Uehara’s splitter, since it’s probably the only other pitch in baseball that can keep up with these sliders.

Here are the total numbers (since 2008) of each of these pitches:

Jonny VentersSL7780.4690.3010.5980.21
Sergio SantosSL6100.4910.2970.5370.41
Greg HollandSL13060.4670.2570.5360.96
Koji UeharaFS12210.4580.2490.5261.14
Craig KimbrelSL10730.4310.2160.5011.76
Aroldis ChapmanSL4910.3680.2360.5451.76
Luke GregersonSL30030.4560.2070.4721.82
Sergio RomoSL20950.4040.2110.4652.15

Venters’ slider is the only pitch ahead of Santos in this sample. (There may be a pitcher I am be excluding, if you want to know the TIPS of someone else’s pitch just let me know!) Venters and Santos are definitely the top tier in pitches. ¬†Looking at both velocity and movement, Santos just edges out Venters in both categories. There may be the added advantage of pitching in the National League that gives Venters a boost, but without a quality of competition comparison, we can’t make these assumptions.¬†It will be a true joy to watch Santos and his slider for a full season in 2014.

With the above table, it is also very important to note the usages of the pitch. Gregerson and Romo both use their slider as their primary pitch. This causes it to be more predictable, and therefore less likely to catch a batter off-guard. Having TIPS values that low when a batter is expecting a pitch, is very impressive. The effect of usage on a pitch’s effectiveness is something that needs to be closer examined (maybe by me in the future!)

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Author: Chris Carruthers

Chris has been a baseball (and Jays) fan for 15 years. He has also played since the age of 6, working his way through Little League and Babe Ruth Baseball as a catcher and first baseman. He got interested in sabermetrics after viewing the movie Moneyball. His continuous self-learning in sabermetrics and advanced stats is driven by his engineering background and love for numbers. Chris's go-to website is FanGraphs, where he has had a few previous community submissions. Chris also enjoys music and plays guitar in his sparse spare time from his studies. He also follows hockey and his favourite team, the Calgary Flames. Follow Chris on Twitter @CCBreakingBlue.

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  1. Nice Article.

    quite interesting.

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  2. Interesting stuff. Can you figure out which pitchers (starters and relievers) had the best TIPS for each pitch since 2008? I wonder who has the best four-seam fastball by this measure.

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