We’re going to kick off our annual projection series with Amed Rosario. This marks the sixth year that we’ve done projections here at Mets360. The idea has always been to see if the wisdom of the crowd of (mostly) Mets fans could do as good a job, or better, than the computer projection models. The hardest guys to project, for both the computers and the humans, are guys with little or no track record in the majors.
Rosario came to the majors last August with a ton of hype. Unfortunately, he did not pay immediate dividends, at least not with the bat. He didn’t hit for much of an AVG, he almost never walked and he struck out way too many times. He finished with a .665 OPS, nearly identical to the .658 OPS that fellow rookie Dominic Smith posted. The Mets went the recycled veteran route hoping that Smith could return to Triple-A at the start of the season. You can say the Mets went the recycled veteran route at shortstop, too, as they re-signed Jose Reyes. But the hope is that Reyes plays very few games at shortstop and that Rosario settles into the position for a decade or more with the Mets.
So, why the confidence in Rosario and not Smith?
If you squint, you can almost see a .665 OPS being acceptable for a good defensive shortstop. No one feels that way about a first baseman. Or at least they shouldn’t. Yet we see this offseason that’s not the case, either with the Mets’ front office or the fanbase. And Rosario, while not particularly great in the field after his promotion, looked a lot better than Smith defensively. Finally, Rosario came to the bigs looking like an athlete. Smith came up looking more like what we’d imagine a competitive eater would be, if we hadn’t seen the skinny Asian guy wolfing down the hot dogs.
Do we see more from Rosario in 2018? Here are our individual forecasts:
| PA | AVG | OBP | SLG | HR | RBI | Batting Order | |
|---|---|---|---|---|---|---|---|
| Dalton Allison | 410 | .260 | .280 | .410 | 20 | 63 | 1 |
| Joe Barbieri | 481 | .276 | .328 | .424 | 11 | 52 | 7 |
| John Fox | 490 | .261 | .320 | .420 | 9 | 47 | 8 |
| David Groveman | 575 | .269 | .298 | .350 | 11 | 51 | 8 |
| Charlie Hangley | 593 | .289 | .341 | .493 | 15 | 72 | 1 |
| Brian Joura | 620 | .268 | .306 | .428 | 12 | 55 | 8 |
| Mike Koehler | 500 | .270 | .315 | .370 | 5 | 50 | 7 |
| Matt Netter | 625 | .262 | .307 | .445 | 11 | 61 | 8 |
| Jim O’Malley | 660 | .270 | .310 | .410 | 12 | 65 | 8 |
| Rob Rogan | 580 | .265 | .320 | .410 | 11 | 50 | 7 |
| Mike Walczak | 480 | .261 | .310 | .418 | 11 | 47 | 8 |
Since we did not forecast all of the individual numbers that go into ERA and WHIP, we are going to use median for those numbers and average for the counting numbers to come up with our Mets360 forecast. Here is what our group as a whole projects for Rosario in 2018:
The wild card column for Rosario is a forecast of where he will bat most in the lineup. Ideally, he’ll develop into a leadoff man but the majority of us don’t see it happening in 2018. Most of us feel he’ll be batting right in front of the pitcher for the greatest part of the year while the next most popular answer has him hitting seventh.
As you would expect with a young player, our other forecasts are all over the map. In playing time, we have a swing of 250 PA from our low projection to our high one. In HR, we have a difference of 15 between low and high, with Dalton seeing the least amount of playing time yet the highest HR output. Interestingly, 10 of our 11 panelists see a very similar AVG, with a range of .260-.276 from the majority. Only Charlie deviates from this, with a .289 forecast.
Typically, the predictions from the fans are more optimistic than the ones from the computer models. Let’s compare our group forecast to ones by the projection systems. The good news here is that the ZiPS numbers from the Mets have already been released, so we can include those right away.
| PA | AVG | OBP | SLG | HR | RBI | |
|---|---|---|---|---|---|---|
| Marcel | 285 | .262 | .313 | .430 | 9 | 28 |
| Mets360 | 547 | .268 | .310 | .418 | 12 | 56 |
| Steamer | 541 | .257 | .297 | .374 | 9 | 49 |
| ZiPS | 594 | .259 | .295 | .380 | 9 | 51 |
Our group forecast is pretty much right in line with the computer models. Marcel will always project low on a rookie in terms of playing time. And our production numbers are higher than Steamer and ZiPS but slightly below Marcel. The biggest difference is 44 points of SLG between our high forecast and that of Steamer.
Check back Wednesday for the next entry in our projection series.
The Mets can survive him struggling,,,and I believe he will struggle. He’s a Chase and K Opportunity for a Good Pitcher at this point…and if He hits 8th, they will eat him up alive.
He can play at a low 600’s OPS and still participate with Positive D, Legs, and flashes of great ability….the question will be whether He can survive the struggle straight away at the MLB Level.
He’s going to be a very good player…they need to help him and protect him. That’s as good a reason as any to send Smith to AAA to start the Season…two young guys teething at the same time will make it hard to protect both…not to mention avoiding big lineup holes.
I think Rosario scared me more than Smith in his debut last year.Wild,wild swinger who no pitcher will bother throwing a strike too.I saw the talent though and hopefully the hitting coach can tame him somewhat.
My numbers: 525 PA, .260 Avg, (130 for 500). 25 BB for a .295 OBP. I’m throwing a guess of 95 singles, 20 doubles, 5 triples, and 10 homers giving him a slugging % of .380 for a .675 OPS. I would like to see the OPS closer to .700 – that is 20 more total bases – a couple additional homers, a few more doubles, and perhaps a couple triples would do it. He had 4 of each last year – he will not maintain that ratio. I expect his doubles to go up a bit. And if he can get to 25 walks, that will be a good next step.
Last point . . I’m wondering if hitting 9th might be the place to put him. Without a true leadoff hitter on the team, this could be his ‘training wheels’ for the top of the order and he would probably get more pitches to hit than in the 8 hole.
Thats not a bad idea, especially when pitchers who can hit, specifically when Syndergaard and Matz pitch
Rosario has wheels. Hopefully he learns to use it to beat out some infield hits, stretch singles into doubles, and doubles into triples.
“The hardest guys to project, for both the computers and the humans, are guys with little or no track record in the majors.”
–You gents need to up your game.
It has been understood for decades that properly examined, minor league numbers are just as predictive of major league numbers as prior major league play.
He!!uva thing not to know, when you’re running a baseball website and are into projecting. The source is Bill James, btw.
Run that quote by Dan S. or Brian C. or Sean S. or any of the guys who run the projection systems and see if they don’t tell you the same thing.
If they agree with the quoted paragraph, like i said, ‘up your game.’
Don’t take my word for it (or James’s), run your own sims / projections. Adjust for park and other contexts such as league, etc., adjust for age, the various factors commensurate with how you project using past major league performance. Do a thousand each and you’ll find minor league performance is just as projectable as major league performance.
This isn’t rocket science or buried treasure. Below is the link to one example that’s not behind a paywall. Among the things you’ll want to look to in developing your own system is which factors are more predictive of future performance, and which are less.
Scroll down to the fifth graf to start getting into specifics.
https://www.fangraphs.com/tht/katoh-forecasting-major-league-pitching-with-minor-league-stats/
It seems to me you’re confusing “hardest” with “impossible.” No one is saying it can’t be done. And I read both the KATOH and Bill James articles when they were released.
Anyway, you’re most likely aware that they grade the projection systems after the year is over. Put “grading the projection systems” into Google and look at the results. This is from the first item returned:
“Unsurprisingly, the average error goes up across the board; rookies are harder for each system to predict than their peers with major league experience.”
https://www.beyondtheboxscore.com/2017/1/8/14189138/pecota-zips-steamer-marcel-projection-systems-graded