2022 Projections Thread

[sveumrules]

I believe the Steamer projections are already available for 2022 & FanGraphs just started publishing their team ZiPS articles with the DBacks dropping today...

 

https://blogs.fangraphs.com/2022-zips-projections-arizona-diamondbacks/

 

Possible trade target Ketel Marte comes in at 537 PAs | 119 OPS+ | 3.3 WAR, which seems a little light to me.

 

Over the last four years he is at 1777 PAs | 127 OPS+ | 14.0 WAR & heading into his age 28 season.

 

His 149/143 OPS+ marks in 2019/21 are probably a little over his skis, but I'd probably project him around a 130 OPS+.

 

Recent Arizona 40 man addition Cooper Hummel also clocks in with a 94 OPS+ projection.

[Mass Haas]

This 2022 offensive projection snapshot is pretty horrifying (and realistic).

[Devinep]

Both posts in this thread show how important it is for the Brewers to get at least 1 (IMO 2) middle of the order hitters. Ketel Marte makes a ton of sense as a target for one of those hitters.

[umphrey]

This 2022 offensive projection snapshot is pretty horrifying (and realistic).

 

Yeah, only ones that feel low to me are Jace (OBP) and Narvaez (AVG). I still think we should try Brosseau in RF unless we add someone else to play there.

[adambr2]

Man, that is a sad projection line to see for Yelich in just the first real year of his extension.

[brewers888]

Further proof that this team needs not one but two big time hitters if we are going to be a championship team. I am hopeful that we sign Castellanos and maybe trade Houser for the second bat. Looking at the desperation when it comes to pitching I think Houser can fetch a far higher return than many would expect.

[sveumrules]

This 2022 offensive projection snapshot is pretty horrifying (and realistic).

 

I think those projections are realistically closer to pretty average than pretty horrifying.

 

Not sure where Cream City Prospects pulled them from as I couldn't find any other 2022 Davenports elsewhere on the interwebs, but I'd imagine the offensive projections for teams like the Pirates, Marlins, Rangers, Orioles, DBacks, Royals, Cubs, Guardians & Nationals would provide a better proxy for horror.

 

With a couple additions at COF/1B/DH (typically the easiest positions to find offense at) the Brewers should be well positioned for another Top Ten position player group in 2022 like Stearns & company have assembled each of the last three full seasons...

 

2021: 22.2 WAR (10th)

2019: 24.2 WAR (10th)

2018: 27.3 WAR (6th)

[Eye Black]

Not sure where Cream City Prospects pulled them from as I couldn't find any other 2022 Davenports elsewhere on the interwebs

The individual player projections are available on Clay Davenport’s website, but you have to view each player’s page individually to see them.

 

For example here is Rowdy Tellez’s page, 2022 projections are the last line of the top grouping of player stats:

Rowdy Tellez projection on Clay Davenport

 

An easy way to navigate among player pages for those that were members of the 2021 Brewers is by clicking their name/player page using this link (again, 2022 projections are available once you click their individual player page):

2021 Brewers players on Clay Davenport

[sveumrules]

Not sure where Cream City Prospects pulled them from as I couldn't find any other 2022 Davenports elsewhere on the interwebs

 

The individual player projections are available on Clay Davenport’s website, but you have to view each player’s page individually to see them.

 

Ah, thanks EB. Went to his website, but the last update was September & there was no obvious link to 2022 projections I could see so I didn't really click around much beyond that.

[sveumrules]

The closer I look at the Clay Davenport projections, the more dubious & over-regressed they seem. The Steamer projections look a little more realistic to me...

 

Urias 2021 | 249/345/445

Urias CD22 | 231/320/414

Urias ST22 | 255/344/432

 

Willy 2021 | 262/337/481

Willy CD22 | 239/314/449

Willy ST22 | 253/330/438

 

Omar 2021 | 266/342/402

Omar CD22 | 245/318/376

Omar ST22 | 249/334/389

 

Kolten 2021 | 272/335/447

Kolten CD22 | 254/322/394

Kolten ST22 | 265/335/409

 

Rowdy 2021 | 242/305/414

Rowdy CD22 | 234/306/451

Rowdy ST22 | 258/328/482

 

Lorenzo 2021 | 257/329/401

Lorenzo CD22 | 232/299/352

Lorenzo ST22 | 265/336/397

 

Yelich 2021 | 248/362/373

Yelich CD22 | 239/348/430

Yelich ST22 | 258/369/458

[wntrtxn21]

The closer I look at the Clay Davenport projections, the more dubious & over-regressed they seem. The Steamer projections look a little more realistic to me...

 

Urias 2021 | 249/345/445

Urias CD22 | 231/320/414

Urias ST22 | 255/344/432

 

Willy 2021 | 262/337/481

Willy CD22 | 239/314/449

Willy ST22 | 253/330/438

 

Omar 2021 | 266/342/402

Omar CD22 | 245/318/376

Omar ST22 | 249/334/389

 

Kolten 2021 | 272/335/447

Kolten CD22 | 254/322/394

Kolten ST22 | 265/335/409

 

Rowdy 2021 | 242/305/414

Rowdy CD22 | 234/306/451

Rowdy ST22 | 258/328/482

 

Lorenzo 2021 | 257/329/401

Lorenzo CD22 | 232/299/352

Lorenzo ST22 | 265/336/397

 

Yelich 2021 | 248/362/373

Yelich CD22 | 239/348/430

Yelich ST22 | 258/369/458

 

B.R. projections:

Urias .247/.339/.411

Adames .257/.329/.451

Omar .254/.332/.400

Wong .265/.337/.416

Tellez .243/.310/.430

Cain .250/.318/.378

Yelich .261/.369/.467

[sveumrules]

All the projections appear to be underselling Adames quite a bit too due to his weird splits at the Trop...

 

TB home | 626 PAs | 219/277/347

TB road | 628 PAs | 291/363/495

Brewers | 413 PAs | 285/366/521

 

The strongest projection so far has him at a .780 OPS, but I'd peg him closer to .850 given his MIL/TB road numbers & placement on the aging curve.

[umphrey]

I guess the projections are still kind of a mess with bad 2020 data and half of 2021 with/without cheating pitchers.

[Eye Black]

Some Davenport and Steamer projections among free agent corner outfielders that can play right field…

 

Seiya Suzuki

Davenport: .303 / .386 / .489 (.875 OPS)

Steamer: N/A

 

Michael Conforto

Davenport: .268 / .361 / .424 (.785 OPS)

Steamer: .254 / .358 / .453 (.811 OPS)

 

Nick Castellanos

Davenport: .295 / .354 / .506 (.860 OPS)

Steamer: .270 / .330 / .485 (.815 OPS)

 

Avisail Garcia

Davenport: .275 / .343 / .449 (.792 OPS)

Steamer: .266 / .331 / .456 (.787 OPS)

 

Jorge Soler

Davenport: .257 / .346 / .464 (.810 OPS)

Steamer: .239 / .332 / .470 (.802 OPS)

 

Joc Pederson

Davenport: .254 / .328 / .435 (.763 OPS)

Steamer: .236 / .316 / .449 (.765 OPS)

 

Eddie Rosario

Davenport: .275 / .309 / .473 (.782 OPS)

Steamer: .264 / .309 / .466 (.775 OPS)

 

Odubel Herrera

Davenport: .280 / .338/ .423 (.761 OPS)

Steamer: .270 / .326 / .437 (.763 OPS)

 

 

As well as some potential corner/right field trade candidates…

 

Bryan Reynolds

Davenport: .294 / .374 / .478 (.852 OPS)

Steamer: .279 / .364 / .471 (.835 OPS)

 

Trey Mancini

Davenport: .271 / .345 / .489 (.834 OPS)

Steamer: .257 / .332 / .453 (.785 OPS)

 

Joey Gallo

Davenport: .222 / .351 / .494 (.845 OPS)

Steamer: .208 / .342 / .481 (.823 OPS)

 

Mitch Haniger

Davenport: .267 / .348 / .471 (.819 OPS)

Steamer: .245 / .321 / .457 (.778 OPS)

 

Max Kepler

Davenport: .242 / .331 / .477 (.808 OPS)

Steamer: .234 / .328 / .444 (.772 OPS)

 

Adam Duvall

Davenport: .236 / .298 / .492 (.790 OPS)

Steamer: .226 / .288 / .458 (.746 OPS)

[sveumrules]

Pirates are the first NLC team to have their ZiPS released...

 

https://blogs.fangraphs.com/2022-zips-projections-pittsburgh-pirates/

 

Bryan Reynolds (126 OPS+ | 3.9 WAR), Ke'Bryan Hayes (94 OPS+ | 2.5 WAR) and Oneil Cruz (117 OPS+ | 2.5 WAR) gives them a trio of interesting position players, but that's about it as the pitching staff looks like downright ugly.

 

Fourth straight fifth place finish likely incoming.

[TURBO]

Meh, I don't put much stock in projections to be honest.

 

We obviously are going to need some more bats, but we all know that without some projections website spitting out inaccurate information.

[Eye Black]

Meh, I don't put much stock in projections to be honest.

Thank you for the honesty.

[Eye Black]

Cubs projections are up in ZiPS today. Below are the snapshots of the two NL Central teams that have been released so far…

 

 

 

 

[Thurston Fluff]

Meh, I don't put much stock in projections to be honest.

 

We obviously are going to need some more bats, but we all know that without some projections website spitting out inaccurate information.

 

I'm with you on that. However given the lack of anything else going on in baseball it's more interesting than usual. What might make it more interesting is to go back and see how past projections turned out. At least then we'd know what to make of the projection systems themselves.

[sveumrules]

I guess for me projections are an interesting tool for a couple few reasons...

 

My puny brain can't process as much information as a computer.

In whatever amount of information my puny brain can process there exists some degree of bias.

As imperfect as the projections are, they still offer the most accurate view of future outcomes.

We know Stearns & company lean heavily on projections, so they're relevent to Brewers transactions.

 

I've posted this article Jeff Sullivan wrote at FanGraphs before the Rays hired him a few times over the years because it does a really good job of illustrating the usefulness of projections...

 

https://blogs.fangraphs.com/how-best-to-predict-the-seasons-second-half/

 

Now granted, its talking about midseason projections, which are a little different from preseason ones, but the overall point remains, if you want to know what's going to happen in baseball...that's impossible. But if you want to give yourself even a chance, you should give the most consideration to the projections because they're able to keep a cooler head.

[Lathund]

The best predictor of future results is past results, so projections are very useful. They help strip out the biases we all have. I think the best way to go about it is to use projections as the starting point, and then into that factor in the things that a projection can't; things like injuries affecting performance, swing changes etc. Also as far as team records go, it's worth keeping in mind that even if you were to project every single player perfectly, the team projections still wouldn't be perfect, due to things like playing time, injuries, different lineup philosophies or bullpen usage, mid-season trades and promotions, sequencing, schedules and probably more things besides.

[Thurston Fluff]

Shouldn't the claims of how useful they are be backed up with past results? I'm not against them as much as I've never actually seen a comparison of predictions to results. I did a little looking and saw some very good articles on why we use them. This one for instance does a very good job of that.

https://library.fangraphs.com/principles/projections/ But it doesn't tell show how accurate those systems have been in the past. It just asserts it's more accurate than the raw stats, the eye test or whatever. But given the nature of analytics it seems reasonable to show us that it actually IS better. It seems like it'd be very easy to actually show what they predicted vs what actually happened, so I looked a bit. While looking I found this article that demonstrates how hard it is to agree on accuracy. https://www.baseballhq.com/great-myths-projective-accuracy

While I could find a lot of stuff on projecting accuracy, I didn't find much on how accurate these systems have been. I did find stuff on fantasy including this one https://www.fantasypros.com/2021/03/most-accurate-fantasy-baseball-projections-2020/ but not on actual baseball outcomes.

Does anyone know where I can find something that shows the results compared to the projections? Or do I just have to manually go through each system for each player and compare the results with the projections individually?

[SRB]

The fact that there is never a more rigorous accounting of past performance (and this being a statistics-driven field) has always been a massive red flag to me about how accurate they actually are. Obviously lots of writers have a vested interest in trying to convince use they are useful, but who knows. I vaguely remember something from years ago suggesting that a simple three-year weighted average (is that what Marcel is/was, or am I misremembering?) was more accurate than most of the complex projection formulas.

[nate82]

The fact that there is never a more rigorous accounting of past performance (and this being a statistics-driven field) has always been a massive red flag to me about how accurate they actually are. Obviously lots of writers have a vested interest in trying to convince use they are useful, but who knows. I vaguely remember something from years ago suggesting that a simple three-year weighted average (is that what Marcel is/was, or am I misremembering?) was more accurate than most of the complex projection formulas.

 

Please define accurate.

 

If you are defining as accurate as being did x player get exactly within the stats? Then no it is not accurate and there really isn't an accurate system for this. If you are defining the predictions if they are within a margin of error then sure you could look at it that way. I think you would find that for the majority of the predictions they are within the margin of error or at least close enough for it to be negligible.

 

There really isn't a perfect system and the predictions should be taken as what to expect or at least minimum expectations for a team or a player to achieve. I think a better way to show the information would be to show a high mid and low range. From there you could then look at where the player fell on the projections scale if they are on the high side then you could determine it was a career year (positive) and if on the low range again it would be another career year (negative). Neutral would be anything close to the mid range.

 

Basically just use the projections as a basis to judge the player on what they did and forget the accuracy on the actual projections.

[Thurston Fluff]

Basically just use the projections as a basis to judge the player on what they did and forget the accuracy on the actual projections.

 

Why not just use basic stats to get the basis to judge from if accuracy isn't relevant? I get that defining accuracy is hard, not to mention subjective. One of the articles I posted outlines the difficulty. Which begs the question. Why should we simply believe it's true if we haven't, or can't, measure it?

As far as I can tell there is a lot of articles explaining why some of these in-depth predictors are better, but nothing showing they actually are better. If one claim's it's more accurate than something else, then it stands to reason it was shown to actually be so. But I can't find anything showing it is. Again, maybe I missed it since I'm not as big on that sort of thing. If anyone can point me to something actually showing it's better that would be helpful. I'm not talking about explanations of why it should be. I've found plenty of that. I'm also appreciative of posters here explaining why they like them. But that is not the same as SHOWING its superiority. Given how long these projection systems have been around it seems like a major oversight not to show it really is better.