After having typically appeared in the hallowed pages of Baseball Think Factory, Dan Szymborski’s ZiPS projections have now been released at FanGraphs for half a decade. The exercise continues this offseason. Below are the projections for the San Francisco Giants. Szymborski can be found at ESPN and on Twitter at @DSzymborski.

ZiPS Projections 2018 2017 AL BAL CHW HOU BOS CLE LAA NYY DET OAK TBR KCR SEA TOR MIN TEX NL ATL CHC ARI MIA CIN COL NYM MIL LAD PHI PIT SDP WSN STL SFG AL BAL CHW HOU BOS CLE LAA NYY DET OAK TBR KCR SEA TOR MIN TEX NL ATL CHC ARI MIA CIN COL NYM MIL LAD PHI PIT SDP WSN STL SFG

Batters

“Baseball’s biggest disappointment,” is how Jeff Sullivan characterized the 2017 Giants back at the end of September. And not without reason: the club produced the league’s worst record relative to the preseason projections, a development expressed in graphic form just below.

On the one hand, that’s bad for the 2017 Giants. On the other, though, it’s probably good for the 2018 version of the club. The Giants are likely due — due perhaps more than any other team — for positive regression. Even if San Francisco were to field precisely the same roster this next season, that same precise roster would almost certainly outperform its disappointing predecessor.

The ZiPS projections appear to support this hypothesis. Here, for example, are the forecasts for San Francisco’s top-four returning hitters:

Positive Regression for Top Giants Hitters Player 2017 PA 2017 WAR 2018 zPA 2018 zWAR PA Diff WAR Diff Buster Posey 568 4.3 534 4.9 -34 0.6 Brandon Crawford 570 2.0 567 3.5 -3 1.5 Brandon Belt 451 2.3 503 3.3 52 1.0 Joe Panik 573 2.0 571 3.0 -2 1.0 Average 541 2.7 544 3.7 3 1.0 Headings marked with -z- represent ZiPS projections for 2018.

The core returning members of the Giants’ offense — Brandon Belt, Brandon Crawford, Joe Panik, and Buster Posey — are projected, on average, to produce an additional win each in 2018. That’s in roughly the same number of plate appearances as 2017, as well, meaning that ZiPS is calling for all four simply to play better this season.

This isn’t to say the club’s field-playing cohort is without flaw. No outfielder, for example, is projected even to produce an average season. Nevertheless, a combination of positive regression and Evan Longoria (645 PA, 3.1 zWAR) ought to facilitate easy improvement over last year’s performance.

Pitchers

Even with something more like a full season of Madison Bumgarner (166.1 IP, 2.8 zWAR), the prognosis for the pitching staff isn’t quite as encouraging. The left-hander recorded a 22.4% strikeout rate during his 17 healthy starts last year, his lowest mark since 2010, when the the league-average rate was three points lower than in 2017. ZiPS calls for only a minor rebound in that department, up to 24.7%. The overall forecast remains quite strong, of course, just not necessarily in the context of Bumgarner’s established levels.

Johnny Cueto (174.0, 2.7) and Jeff Samardzija (177.2, 2.4) join Bumgarner atop the rotation. After that triumvirate, however, there’s little substance. Ty Blach (153.0, 0.6) and Chris Stratton (127.1, 0.4) are forecast for just a win between them in something approaching a full complement of starter’s innings. Few, if any, legitimate alternatives exist at the moment.

In the bullpen, Mark Melancon (50.0 IP, 65 ERA-, 1.1 zWAR) returns to close games and, if Dan Szymborski’s computer is to be believed, ought to bear greater resemblance to the pitcher whom San Francisco signed last offseason than the one who posted a worse-than-average ERA in 2017. Hunter Strickland (60.1, 79 ERA-, 0.9), meanwhile, joins Melancon as one of two Giants relievers forecast to prevent runs at a rate that’s at least 20% better than average.

Bench/Prospects

While Gorkys Hernandez (413 PA, 0.7 zWAR) is denoted as the team’s starting center field in the depth-chart graphic below, that distinction could also fall to Steven Duggar (457, -0.3), although the projections favor the former at the moment. The Giants signed former Pittsburgh farmhand Alen Hanson (434, 1.1) to a minor-league deal in December. Hanson receives the top forecast of the likely non-starters.

Will Smith (39.2 IP, 77 ERA-, 0.6 zWAR) is omitted from the depth chart due to his rehab from Tommy John surgery. He would represent a formidable addition to the back end of the bullpen, however. He’s attempting to come back by Opening Day. Even an average return time, though, would place his likely return in May.

Depth Chart

Below is a rough depth chart for the present incarnation of the Giants, with rounded projected WAR totals for each player. For caveats regarding WAR values see disclaimer at bottom of post. Click to enlarge image.

Ballpark graphic courtesy Eephus League. Depth charts constructed by way of those listed here at site and author’s own haphazard reasoning.

***

***

***

***

***

***

Disclaimer: ZiPS projections are computer-based projections of performance. Performances have not been allocated to predicted playing time in the majors — many of the players listed above are unlikely to play in the majors at all in 2017. ZiPS is projecting equivalent production — a .240 ZiPS projection may end up being .280 in AAA or .300 in AA, for example. Whether or not a player will play is one of many non-statistical factors one has to take into account when predicting the future.

Players are listed with their most recent teams unless Dan has made a mistake. This is very possible as a lot of minor-league signings are generally unreported in the offseason.

ZiPS is projecting based on the AL having a 4.24 ERA and the NL having a 4.18 ERA.

Players that are expected to be out due to injury are still projected. More information is always better than less information and a computer isn’t what should be projecting the injury status of, for example, a pitcher with Tommy John surgery.

Regarding ERA+ vs. ERA- (and FIP+ vs. FIP-) and the differences therein: as Patriot notes here, they are not simply mirror images of each other. Writes Patriot: “ERA+ does not tell you that a pitcher’s ERA was X% less or more than the league’s ERA. It tells you that the league’s ERA was X% less or more than the pitcher’s ERA.”

Both hitters and pitchers are ranked by projected zWAR — which is to say, WAR values as calculated by Dan Szymborski, whose surname is spelled with a z. WAR values might differ slightly from those which appear in full release of ZiPS. Finally, Szymborski will advise anyone against — and might karate chop anyone guilty of — merely adding up WAR totals on depth chart to produce projected team WAR.