SB Nation User Blog: Sandy Kazmir

I was wondering if you guys wanted anything for Henry Blanco? The Rays could use a solid backup...

Sandy Kazmir — Fri, 03 Jul 2009 14:27:25 -0000

I was wondering if you guys wanted anything for Henry Blanco? The Rays could use a solid backup catcher on the cheap and, well, I mean do you even want anything for him? Could we just like give you a handshake or a milkshake or maybe rake your yard for an hour? Anyways, not sure if anyone reads fanshots over here, but some kind of answer would be appreciated.

Sandy Kazmir

SOSH Auction to K ALS

Sandy Kazmir — Wed, 01 Jul 2009 15:59:28 -0000

Brooks Baseball provides some of the finest raw data you can find on pitch f/x completely free of charge. They ask only that you spread their name. They have a new request. Go to this LINK and see what you can do to help. I'm no fan of SOSH nor the Red Sox, but I do support Brooks in what they do. If anything, go there and see if you can help out in some way. Thanks for everything Brooks and good luck guys in helping people feel a little better.

A Look at Runs, By Inning Splits

Sandy Kazmir — Tue, 30 Jun 2009 16:37:47 -0000

More photos » by Steve Nesius - AP

2 Ninjas: Knuckle Up(AP Photo/Steve Nesius)

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The above image is the Rays, and their opponents', runs by inning. Look at that vast chasm from the 5th inning on. The only inning we have been outscored is the first (thanks Kaz & Sonny).

Here is the K, BB, HR, and R rates for the Rays and their opponents by inning. The rate is calculated by taking the quantity of each stat divided by PA. I was looking at this stuff today and thought you guys might find it interesting how we have dominated teams throughout a game, not just a good inning. This also shows how much better our middle relief has been versus opponent middle relief.

Updated Deserved Wins

Sandy Kazmir — Mon, 29 Jun 2009 02:58:07 -0000

More photos » by Steve Nesius - AP

If this Eagle didn't feast on marine wildlife, he would be a great analogy for our month of June (AP Photo/Steve Nesius)

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I've updated the FIP look I did the other day and thought you guys might find it interesting. I have made the workbooks more user friendly, though it is still a process. I now have the Red Sox and Yankees so here we go:

Pitcher	FIP	PROBw	Starts	Est. Wins
Sabathia	3.76	70.4%	16	11.27
Beckett	3.33	73.2%	15	10.99
Shields	3.79	64.4%	16	10.30
Pettitte	4.57	61.3%	15	9.20
Burnett	4.96	59.5%	15	8.93
Lester	3.85	56.8%	15	8.51
Wakefield	4.28	59.3%	14	8.30
Chamberlain	3.62	63.8%	13	8.30
Penny	4.72	58.6%	14	8.21
Garza	4.67	51.1%	15	7.67
Sonnanstine	5.63	46.1%	15	6.92
Niemann	4.81	44.4%	14	6.21
Kazmir	5.93	43.4%	10	4.34
Matsuzaka	3.75	68.0%	6	4.08
Hughes	6.25	49.4%	7	3.46
Masterson	6.23	38.2%	8	3.05
Wang	7.40	30.6%	7	2.14
Price	5.82	34.0%	6	2.04

Team x Team

Pitcher	FIP	PROBw	Starts	Est. Wins
Shields	3.79	64.4%	16	10.30
Garza	4.67	51.1%	15	7.67
Sonnanstine	5.63	46.1%	15	6.92
Niemann	4.81	44.4%	14	6.21
Kazmir	5.93	43.4%	10	4.34
Price	5.82	34.0%	6	2.04
Team	4.96	49.3%	76	37.49

Pitcher	FIP	PROBw	Starts	Est. Wins
Beckett	3.33	73.2%	15	10.99
Lester	3.85	56.8%	15	8.51
Wakefield	4.28	59.3%	14	8.30
Penny	4.72	58.6%	14	8.21
Masterson	6.23	38.2%	8	3.05
Matsuzaka	3.75	68.0%	6	4.08
Team	4.25	59.9%	72	43.14

Pitcher	FIP	PROBw	Starts	Est. Wins
Sabathia	3.76	70.4%	16	11.27
Pettitte	4.57	61.3%	15	9.20
Burnett	4.96	59.5%	15	8.93
Chamberlain	3.62	63.8%	13	8.30
Hughes	6.25	49.4%	7	3.46
Wang	7.40	30.6%	7	2.14
Team	4.74	59.3%	73	43.30

This does not include Price's fine start today, but it does factor in a start where Joba put up a .16 FIP due to only pitcher 2/3rds of an inning.

Google Docs

RAYS

RED SOX

YANKEES

Lastly, I wanted to break this down to show the average for what should be the various starter spots. It won't mean much quite yet, but as we get more data, it will become more meaningful, and hopefully end up with something like Graham or Matthew's (Sorry dudes I can't remember which) look last year, using tRA, to see the thresholds between the various starter spots.

Pitcher	FIP	PROBw	Starts	Est. Wins
1	3.63	69%	15.7	10.85
2	4.46	59%	15.0	8.88
3	4.21	61%	13.7	8.27
4	5.04	47%	14.7	6.93
5	5.31	54%	7.7	3.96
6	6.48	34%	7.0	2.41

Please God, Smite Steve Phillips

Sandy Kazmir — Mon, 29 Jun 2009 01:09:59 -0000

Anyone watching this Mets-Yankees game, knows what I mean.

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Please

Est. Wins using Fip for and Against

Sandy Kazmir — Sat, 27 Jun 2009 19:39:06 -0000

More photos » by Jim Mone - AP

Can we please get this man some runs? (AP Photo/Jim Mone)

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After reading Matthan's fanpost this morning, I wanted to see what my offseason analysis called Est. Wins looked like through this point in the season. This was a first look at how many wins a pitcher should have had. It was rough and rudimentary. Here is what it looks like updated through 75 games:

Pitcher	R	IP	R/IP	Starts	PROBw	Est. Wins
Shields	2.88	6.77	0.42	16	0.522	8.35
Garza	2.67	6.49	0.41	15	0.556	8.33
Niemann	2.71	5.17	0.53	14	0.477	6.68
Sonnanstine	4.07	5.44	0.75	15	0.354	5.31
Kazmir	4.56	5.07	0.90	9	0.314	2.83
Price	3.67	5.06	0.73	6	0.429	2.57
Team	3.31	5.81	0.57	75	0.454	34.07

After conversing back and forth with Matthan I wanted to see this in FIP format, first the data, then the explanation:

Pitcher	FIP	PROBw	Starts	Est. Wins
Shields	3.79	64.3%	16	10.29
Garza	4.67	50.8%	15	7.61
Sonnanstine	5.63	46.3%	15	6.95
Niemann	4.81	44.6%	14	6.24
Kazmir	6.11	41.9%	9	3.77
Price	5.82	34.2%	6	2.05
Team	4.96	49.2%	75	36.92

First off, check out the workbook on google docs or download the file FIP win% 75 games. I ask to do this so the process doesn't come across as complete gibberish. Using Baseball-reference's gamelogs I was able to come up with a game by game FIP for opposition pitchers (FIPa). It stands to reason that if our starter has a lower FIP (FIPrays) he should be credited with a win. From here I was able to create a matrix comparing each individual FIPa to the entire population of Rays starters FIPs. Using conditional formatting (green is >1, or that cell represents an event where the FIPrays > FIPa) I came up with a total number of events where our performance should be better than theirs. This yielded a probability of a win for each FIP that we have had this year (% of games on Matrix tab).

From here I moved on to the "Data" tab of the workbook. By comparing each actual game FIP to the probability of winning at that FIP (PROBw) I was able to get an idea of estimated wins. This was then totaled and put into the summary that you see before the jump. The team FIP is a weighted average based on Individual FIPs and games started. The PROBw is the likelihood of a starter winning any given starter, based on Est. Wins / Starts.

I used 3.15 as my FIP constant term. Our starter FIPs are based on actual Innings Pitched, while FIPa is based on all opposition pitchers, assuming 9 innings/game. Overall, I really like this, and in the future will make the matrix a little bit different so it is easier to update. It took a long time to do the matrix manually, so if anyone is any good at programming/macros it could be a lot easier in the future. Your thoughts?

A Look at Pitch Type & Value

Sandy Kazmir — Fri, 19 Jun 2009 16:43:42 -0000

More photos » by David Zalubowski - AP

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For a little while now I have wanted to take a look at the relationship between pitch type and value (as tracked by Fangraphs). Following the KISS method I wanted to see what it would look like when you compared each pitcher's pitch type % multiplied by their corresponding pitch value. One would think that a good pitcher would use his best pitch the most and each lesser pitch less. After all, what is the value of having a great pitch if you never use it. I looked at every pitcher with at least 10 IP this year (Sorry Randy Choate) and then broke this out by including anyone that has thrown an inning as a starter on the starter side and doing the same for relievers. As you can imagine there is some overlap, but I wanted to be as indiscriminate as possible. Here are your Rays.

Rank

Name

Team

Total

Matt Garza

Rays

0.17

0.58

0.16

(0.13)

0.77

James Shields

Rays

(0.25)

0.04

(0.07)

(0.06)

0.44

0.09

102

Jeff Niemann

Rays

0.15

(0.16)

(0.15)

(0.07)

0.04

(0.19)

127

David Price

Rays

0.03

(0.38)

(0.03)

0.00

(0.37)

167

Andy Sonnanstine

Rays

(0.34)

(0.32)

(0.03)

(0.33)

(0.01)

(1.03)

183

Scott Kazmir

Rays

(1.09)

(0.58)

0.18

(1.49)

There ended up being 206 pitchers that have thrown an inning as a starter with Chris Carpenter (2.68) being the best and Brandon Backe (-3.87) being the worst. You can Download the file by Pitcher Effectiveness
The averages came out to be

Rank

Name

Team

Total

Avg

Average

(0.29)

0.08

0.05

(0.01)

0.02

(0.11)

(0.23)

As you can see Garza, Shields, and Niemann have had above-average "stuff" so far this year with Price not too far behind. Sonny has been quite a bit below the average and bad Kaz has reared his ugly head for most of the season.

I think this passes the smell test when you see names like Carpenter, Haren, Greinke, Weaver, Halladay, Johnson, Lincecum and Vazquez in the top 10 and names like Backe, Wang, Benson, Olsen, and Matsuzaka in the bottom 10.

In the next installment, I will look at the relievers, hope that Choate gets 3 outs tonight.

So the AL East is kind of good

Sandy Kazmir — Mon, 15 Jun 2009 03:07:08 -0000

I was looking through the Fangraphs rankings today, and noticed how the same teams kept popping up at the top of important lists. So I thought that I would list the rankings for each offensive category that FG tracks to get an idea of how good this division has been. In the following document you can see where each team ranks. One caveat is that I did not want to inject my own personal ideas on positive and negative stats, so everything is listed as is. I.E. Having a low number for strikeouts is not good, having a high number for the HR category is equally not good. You can either DL the file ALE Rankings
or check it out on Google Docs. I think it is important to appreciate how good we have been offensively this year as it's been kind of sneaky, but we can hit.

Rays win 5-4, Everyone is Happy

Sandy Kazmir — Sun, 14 Jun 2009 20:44:48 -0000

via www.fangraphs.com

Beej's Slash by Batting Order Position 2007 - 09

Sandy Kazmir — Tue, 09 Jun 2009 17:55:46 -0000

More photos » by Steve Nesius - AP

about 1 month ago: Tampa Bay Rays' B.J. Upton looks up after he was tagged out trying to reach third base on Carl Crawford's grounder to Kansas City Royals shortstop Tony Pena during the third inning of a baseball game Tuesday, June 2, 2009 in St. Petersburg, Fla. (AP Photo/Steve Nesius)

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	Total
BOP	PA	AVG	OBP	SLG	OPS
1	288	0.235	0.328	0.371	0.698
2	289	0.268	0.383	0.389	0.772
3	453	0.277	0.376	0.424	0.800
4	239	0.269	0.377	0.433	0.809
5	47	0.262	0.340	0.452	0.793
6	26	0.526	0.615	0.737	1.352
7	16	0.467	0.500	1.000	1.500
8	6	0.333	0.333	0.333	0.667
9	65	0.328	0.391	0.621	1.011

I've been working on this this morning and thought I'd share it with you guys. Hard to read a whole lot into it since it includes his, so far, un-BJ-like numbers. Obviously, the 5-9 numbers are an even smaller sample size. I've been a pretty big proponent of Bartlett to leadoff, at the very least against lefties, and think that it wouldn't hurt to have Beej hitting 3rd with the protection of Longo behind him.

For comparison sakes here are his 2007 - 09 seasons, individually.

2007
PA	AVG	OBP	SLG	OPS
19	0.294	0.368	0.529	0.898
70	0.300	0.400	0.450	0.850
158	0.268	0.354	0.464	0.818
150	0.283	0.380	0.465	0.845
47	0.262	0.340	0.452	0.793
25	0.500	0.600	0.722	1.322
12	0.500	0.500	1.167	1.667
4	0.500	0.500	0.500	1.000
63	0.321	0.387	0.607	0.994

2008
PA	AVG	OBP	SLG	OPS
29	0.370	0.414	0.667	1.080
219	0.257	0.378	0.369	0.747
295	0.283	0.388	0.402	0.789
89	0.243	0.371	0.378	0.749
0
0
4	0.333	0.500	0.333	0.833
2	-	-	-	-
2	0.500	0.500	1.000	1.500

2009
PA	AVG	OBP	SLG	OPS
240	0.213	0.314	0.319	0.633
0
0
0
0
1	1.000	1.000	1.000	2.000
0
0
0

This might give you a better feel for how each year went from each spot. You can also view the entire workbook HERE.