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Player Ratings Inspired by ZiPS and OSFM

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Old 03-15-2015, 05:03 PM   #9
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Re: Player Ratings Inspired by ZiPS and OSFM

-ZiPS– The work of Dan Szymborski over at Baseball Think Factory, the ZiPS projections uses weighted averages of four years of data (three if a player is very old or very young), regresses pitchers based on DIPS theory and BABIP rates, and adjusts for aging by looking at similar players and their aging trends. It’s an effective projection system, and is displayed at FanGraphs for off-season and in-season projections.

– Oliver – This system was created by Brian Cartwright and is available over at The Hardball Times. It’s a comparatively simple projection system – using weighted averages of the past three seasons of data, and adjusting for aging and regression – but it calculates its major league equivalencies (MLEs) in a different way than most systems, taking the raw numbers and adjusting them based on park and league. Since most projection systems simply try to adjust for the transition between each minor-league level, Oliver’s projections are better when showing how young players will perform at the major league level. This is also the only projection system to include a fielding and WAR component.

For anyone that is not sure what ZiPS is or Olivers and stumbled upon this thread or just curious where it came from.

ZiPS Q&A


Q. What are ZiPS?
A. ZiPS is a projection system written by Dan Szymborski to project performance in individual baseball players.

Q. What does ZiPS stand for?
A. sZymborski Projection System

Q. That's lame.
A. That's not a question.

Q. OK, do you realize how lame that is?
A. Yes. It originates from the Defense-Independent Pitching Statistics that Voros McCracken developed in 1999. Originally, I was just going to do projections for pitchers, but the realization came that doing one without the other was really dumb. Since it was the first attempt at a non-Voros projection system utilizing some of the discoveries in DIPS theory, I decided to name it in honor of DIPS.

Q. Why is the 'I' in ZiPS lowercase?
A. Because ZIPS looks like some bad shoe at Wal-Mart for little kids while ZiPS totally reminds me of CHiPs. Which is way cooler for a reason I can't put my finger on. I actually meant to call it ZiPs but I typoed it the first time I said the term and didn’t feel like changing it.

Q. So, how is DIPS applied to your pitching projections?
A. I try to predict future BABIP based on a number of factors - the knowledge, demonstrated by Voros, that there's a very strong regression to a mean for this number plus information about the pitcher's tendencies to pitch above his team, his natural BABIP tendencies based on information like handedness, whether or not the pitcher is a knuckleballer, and G/F ratio.

Q. How's the rest come about?
A. I use 4 years of weighted statistics (8,5,4,3) for players between the ages of 24 and 38 and 3 years for younger and older players. This goes for hitter with 3 years mainly being used for pitchers.

Q. How does the aging coming about?
A. My ZiPS program generates growth and decline curves based on player type. I don't try to find particularly similar players but instead large groups with similar characteristics, such as K rate for pitchers, Speed Score for batters, BABIP for batters, handedness, and a lot of other stuff. I do list most similar players at times, but that’s mainly for interest.

Q. Oh my God, my favorite team is projected to get 15000 games! Are you the biggest idiot ever?
A. I'm projecting equivalent production. A player with a projection of 230/270/400 is projected to hit that in the majors if he got that estimated playing time in the majors. A correct projection could be 230/270/400 in the majors or 260/320/450 in AAA or 290/360/500 in AA, depending on the league levels of scoring and the park factors.

Q. How do you project league offensive levels?
A. Weighted recent years. Anything else is just too damn difficult and it usually does the job. It's either that or give all statistics in relative percentages from league average, which is kinda boring. I like projecting a guy to hit 270/330/450, not +1%/-3%/+3%.

Q. How much do these projections cost?
A. They're free for now and for the foreseeable future.

Q. Can I sell your projections?
A. No.

Q. How accurate are the projections?
A. About as accurate (or inaccurate, as is probably the case with projections) as any other commercially available projection system. The 2006 results can be found at

http://www.baseballthinkfactory.org/...ction_results/

Overall, I'd give PECOTA the gold for 2006, but I think ZiPS would deserve the silver, at least of the systems that Sean Smith had access to for 2006 (Ken Warren or Rotowire or someone could've waxed all of us - I don't know).

Q. How is playing time calculated?
A. Based solely on recent playing time. ZiPS, as a consequence, only projects injuries to the extent that the injuries were properly reflected by the previous playing time.

Q. Are platoon splits calculated?
A. ZiPS only projects platoon splits to the extent that the future platoon splits were properly reflected by the previous playing time.

Q. Is steroids included?
A. ZiPS only projects steroid play to the extent that past play reflects the same steroid use as future play.

Q. What about leadership? Paul Lo Duca's way too clutch to ever play badly!
A. ZiPS are computer projections and designed to do what computers do best. If one feels there's a truly compelling reason to ignore a projection, such as playing through an injury, or magic beans, or whatever, they should go with their gut and only use a computer projection as an initial objective evaluation, not a final prediction.

Q. What the hell? Where are save totals?
A. I don't project saves because it's way too much of an opportunity-based stat. RBIs might fluctuate based on hitting #3 or #6, for example, but nowhere near the degree that save totals would fluctuate between being the closer or the manager and setup.

Q. Why is such-and-such player listed with my favorite team? He’s a free agent!
A. When doing the offseason projections, I want to include everyone I can, so I use the most recent team to assign the player. Players will appear on their team with proper projections before the season.

Q. I heard from my mom’s friend at the whorehouse that Jon Switzer signed with the Red Sox but you have him with the Rays!
A. See previous question. To save time, I use MILB’s rosters for minor league depth while doing the initial run of projections and then get caught up on small minor league transactions after the bulk of the projecting is completed. I feel that fans of the last teams would prioritize seeing the projections before February over knowing the up-to-date Jeff Farnsworth projection.

Q. How dod you decide what players to project?
A. First, I do the 40-man rosters. Then the non-roster invitees if it’s late in the winter. Then unsigned free agents. Then the guys that Sickels looks at if I feel they’re anywhere near being relevant. Then random players that don’t fit any of these categories, like Andy Abad.

Q. Can you change so-and-so’s projection? I think he’s better than that.
A. No.

Q. Why don’t you project so-and-so? He may only be 17, but he’s already pitched 20 innings in the Gulf Coast League! And he pitched in high school too!
A. Go away.

Q. If Kris Bryant has a great season, would it be OK if I send you an e-mail every single day telling you how much you suck?
A. No, thank you, anonymous person who is most certainly not named Rich Billings and who uses Yahoo.

Last edited by Houston; 03-15-2015 at 05:07 PM.
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Old 03-15-2015, 05:44 PM   #10
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Re: Player Ratings Inspired by ZiPS and OSFM

Here are a few more examples with some guys we have had trouble rating in the past...

Code:
CC Sabathia 2015 ZiPS projections...

9.15 H/9
1.22 HR/9
8.08 K/9
2.29 BB/9

CC Sabathia sim stats using my ratings (avg of 5 sims)....

9.21 +/- 1.11 H/9
1.26 +/- 0.23 HR/9
7.04 +/- 0.31 K/9
2.16 +/- 0.38 BB/9


Code:
Chris Sale 2015 ZiPS projections...

7.64 H/9
0.85 HR/9
9.92 K/9
2.09 BB/9

Chris Sale sim stats using my ratings (avg of 5 sims)....

7.17 +/- 1.23 H/9
0.80 +/- 0.25 HR/9
9.13 +/- 0.25 K/9
2.20 +/- 0.51 BB/9


Code:
Cole Hamels 2015 ZiPS projections...

8.15 H/9
0.94 HR/9
8.64 K/9
2.32 BB/9

Cole Hamels sim stats using my ratings (avg of 5 sims)....

7.86 +/- 0.84 H/9
0.77 +/- 0.26 HR/9
8.69 +/- 0.59 K/9
2.24 +/- 0.59 BB/9


Code:
Jeff Samardzija 2015 ZiPS projections...

8.68 H/9
1.11 HR/9
9.14 K/9
2.41 BB/9

Jeff Samardzija sim stats using my ratings (avg of 5 sims)....

8.63 +/- 0.59 H/9
1.04 +/- 0.23 HR/9
9.11 +/- 0.73 K/9
2.31 +/- 0.25 BB/9


Code:
Andrew McCutchen 2015 ZiPS projections...

.293/.384/.501
.885 OPS
3.64 HR%
18.36 K%
11.84 BB%
71.4 SB%

Andrew McCutchen sim stats using my ratings (avg of 5 sims)....

.290 +/- .014 batting average
.371 +/- .019 OBP
.529 +/- .028 SLG
.900 +/- .047 OPS
4.03 +/- 0.38 HR%
19.59 +/- 1.79 K%
11.04 +/- 1.94 BB%
73.8 +/- 7.3 SB%


Code:
Bryce Harper 2015 ZiPS projections...

.280/.365/.494
.859 OPS
4.51 HR%
22.13 K%
11.27 BB%
66.7 SB%

Bryce Harper sim stats using my ratings (avg of 5 sims)....

.279 +/- .038 batting average
.365 +/- .030 OBP
.537 +/- .092 SLG
.902 +/- .122 OPS
4.86 +/- 1.28 HR%
22.92 +/- 1.84 K%
11.25 +/- 1.25 BB%
67.5 +/- 9.2 SB%


Code:
Javier Baez 2015 ZiPS projections...

.233/.283/.447
.730 OPS
4.62 HR%
32.62 K%
5.85 BB%
72.0 SB%

Javier Baez sim stats using my ratings (avg of 5 sims)....

.239 +/- .018 batting average
.299 +/- .014 OBP
.440 +/- .037 SLG
.739 +/- .051 OPS
4.07 +/- 0.24 HR%
30.22 +/- 0.95 K%
7.20 +/- 1.16 BB%
75.8 +/- 6.1 SB%


Code:
Giancarlo Stanton 2015 ZiPS projections...

.274/.373/.552
.925 OPS
6.03 HR%
27.69 K%
12.70 BB%
66.7 SB%

Giancarlo Stanton sim stats using my ratings (avg of 5 sims)....

.263 +/- .010 batting average
.353 +/- .016 OBP
.551 +/- .032 SLG
.904 +/- .048 OPS
6.40 +/- 1.18 HR%
29.30 +/- 1.04 K%
11.55 +/- 1.42 BB%
69.5 +/- 13.7 SB%
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Old 03-17-2015, 04:31 PM   #11
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Re: Player Ratings Inspired by ZiPS and OSFM

Loving the #'s... Especially the K & HR.

Also noticed... Missing Michael Taylor of the Nationals in the spreadsheet.
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Old 03-17-2015, 05:20 PM   #12
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Re: Player Ratings Inspired by ZiPS and OSFM

Quote:
Originally Posted by The Kid 24
Loving the #'s... Especially the K & HR.

Also noticed... Missing Michael Taylor of the Nationals in the spreadsheet.
Name goof while filtering players. He's been added to our "unpublished" splits sheet along with all the other missing players and we're currently transferring all of these new ratings over to the main hybrid spreadsheet that has been posted a few times on these boards.
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Old 03-20-2015, 10:51 AM   #13
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Re: Player Ratings Inspired by ZiPS and OSFM

These are great and if I can add in my opinion, I've noticed that the Reliever Endurance ratings seem a bit high. Back when I was into the Baseball Mogul crowd of modding roster sets, the one thing I found the game did very well was pitcher Endurance. The Endurance rating was the number at which the pitcher started to tire and then he could go on to throw another 20-25% pitches of his endurance rating. So, an 80 Endurance pitcher could go 96-100 pitches before being gassed. Granted, I used the actual player's performance and you guys are talking about projections, but it's all still relevant.

My formula...

Pitches Thrown / Games Pitched x .83333 = Endurance

.83333 being the inverse of 1.2 (adding on 20% to Endurance for total pitch count)



An alternative would be...

Batters Faced / Games Pitched x 3.8 x .83333 = Endurance

3.8 being the average pitches per at-bat league wide



In the spreadsheet the majority of Starters basically have an Endurance of 80-85 while Relievers have an Endurance that hovers around 30. Of course sliders can change of how a SP or RP has their Endurance effect performance, pure mathematics would mean the 80-85 Endurance SP going 6 innings is the same as the RP going 2 to 2.1 innings. Two examples of how my idea would look, depending on which you use (performance or projections)...

A.J. Burnett = Around 85
Craig Kimbrel = 11 to 13

I believe this would aid in the realism, CPU A.I., and overall game strategy.

Last edited by mattynokes; 03-20-2015 at 04:53 PM.
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Old 03-20-2015, 11:06 AM   #14
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Re: Player Ratings Inspired by ZiPS and OSFM

Quote:
Originally Posted by mattynokes
These are great and if I can add in my opinion, I've noticed that the Reliever Endurance ratings seem a bit high. Back when I was into the Baseball Mogul crowd of modding roster sets, the one thing I found the game did very well was pitcher Endurance. The Endurance rating was the number at which the pitcher started to tire and then he could go on to throw another 20-25% pitches of his endurance rating. So, an 80 Endurance pitcher could go 96-100 pitches before being gassed. Granted, I used the actual player's performance and you guys are talking about projections, but it's all still relevant.

My formula...

Pitches Thrown / Games Pitched x .83333 = Endurance

.83333 being the inverse of 1.2 (adding on 20% to Endurance for total pitch count)



An alternative would be...

Batters Faced / Games Pitched x 3.8 x .83333 = Endurance

3.8 being the average pitches per at-bat league wide



In the spreadsheet the majority of Starters basically have an Endurance of 80-85 while Relievers have an Endurance that hovers around 30. Of course sliders can change of a SP or RP has their Endurance effect performance, pure mathematics would mean the 80-85 Endurance SP going 6 innings is the same as the RP going 2 to 2.1 innings. Two examples of how my idea would look, depending on which you use (performance or projections)...

A.J. Burnett = Around 85
Craig Kimbrel = 11 to 13

I believe this would aid in the realism, CPU A.I., and overall game strategy.
This sounds very interesting. Would love to see how this plays out.

I've always had a problem (could be a slider problem) where my relief pitchers were getting wayyyy too many innings and way too many Wins/loses.

Wonder if this would have any impact on that.
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Old 03-20-2015, 05:47 PM   #15
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Re: Player Ratings Inspired by ZiPS and OSFM

Quote:
Originally Posted by mattynokes
I've noticed that the Reliever Endurance ratings seem a bit high.

...

In the spreadsheet the majority of Starters basically have an Endurance of 80-85 while Relievers have an Endurance that hovers around 30. Of course sliders can change of how a SP or RP has their Endurance effect performance, pure mathematics would mean the 80-85 Endurance SP going 6 innings is the same as the RP going 2 to 2.1 innings. Two examples of how my idea would look, depending on which you use (performance or projections)...

A.J. Burnett = Around 85
Craig Kimbrel = 11 to 13

I believe this would aid in the realism, CPU A.I., and overall game strategy.
I don't agree because this is an unfair comparison. With relievers, they are not given 4 days off before being trotted out there once again at full power. You are not taking progressive fatigue into account. If an RP goes 2-3 days in a row, that 30 STAM doesn't seen so big...in fact, it seems a bit low since you get the "pitcher is tiring" message after a single pitch at times.

tl;dr, I would agree with your math if SPs and RPs were deployed in the same way, but they aren't. I get good results with these STAM numbers. I also use metrics (IP/appearance) as the core of the STAM ratings, then scale it appropriately.

Quote:
Originally Posted by ghostofsparta15
This sounds very interesting. Would love to see how this plays out.

I've always had a problem (could be a slider problem) where my relief pitchers were getting wayyyy too many innings and way too many Wins/loses.

Wonder if this would have any impact on that.
You can adjust RP STAM through sliders, yes. That's a much safer route than adjusting the attributes.

Feel free to test it out if you want to, but I am quite happy with these STAM #'s and see no good, convincing reason to change them.
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Old 03-20-2015, 06:33 PM   #16
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Re: Player Ratings Inspired by ZiPS and OSFM

Quote:
Originally Posted by WaitTilNextYear
I don't agree because this is an unfair comparison. With relievers, they are not given 4 days off before being trotted out there once again at full power. You are not taking progressive fatigue into account. If an RP goes 2-3 days in a row, that 30 STAM doesn't seen so big...in fact, it seems a bit low since you get the "pitcher is tiring" message after a single pitch at times.

tl;dr, I would agree with your math if SPs and RPs were deployed in the same way, but they aren't. I get good results with these STAM numbers. I also use metrics (IP/appearance) as the core of the STAM ratings, then scale it appropriately.
The reason for this would be exactly that -- to lessen the RP's potency when pitching multiple days in a row. RPs aren't necessarily fresh for each appearance, so I'm not seeing how they are deployed should matter in their Endurance rating.

I would see a problem with using IP/G. That would assume that every pitcher gets through the inning at the same pace. When almost assuredly Doug Fister got through innings quicker than Travis Wood or A.J. Burnett.

Using their pitches per appearance and formula I have, you'd get...

Fister: 82.26
Burnett: 85.10
Wood: 81.85
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