Giants Top Prospects, Spring 2017

Hello all. I didn’t have the time to put together a top 50-100 Giants list this year, and my knowledge of the system isn’t as deep as it once was. But it still didn’t feel right to start the year without posting my thoughts on the top prospects in the system. That was one of the reasons I began this blog in the first place! Better late than never, I suppose.

Without further ado, here are the 20 best prospects in the organization – according to yours truly.

#1(a): Christian Arroyo, Inf, Age 21 = His “doubles, not homers” power in AA last year dropped his stock in some eyes. Not mine. He’ll be in AAA with the potential to do some real damage.

#1(b): Tyler Beede, RHP, Age 23 = Beede & Arroyo are very different prospects, but both will be in Sacramento, and both are future cornerstone pieces for the franchise. Tyler will likely make his MLB debut this season.

#3: Bryan Reynolds, OF, Age 22 = The Giants didn’t have a 1st round pick last summer, but they snagged a legitimate 1st round talent in Reynolds. He’s an all-around hitter who swings from both sides. Can he stick in CF?

#4: Ty Blach, LHP, Age 26 = We saw the best of Blach last September when he mowed down the Dodgers and outpitched Clayton Kershaw. Where he starts the season I don’t know, but he should get his shot at some point this year. Will he settle into the rotation?  

#5: Steven Duggar, CF, Age 23 = Athletic; great arm; solid plate discipline; chance to stay in CF. He surprised a lot of people last year, surging to AA in his first professional season.

#6: Chris Shaw, 1B, Age 23 = The jump to AA took some of the sting out of his bat last summer, but it was still a great debut season for one of the premier power hitters in the organization.

#7: Heath Quinn, OF, Age 21 = One of my favorite players in last year’s draft class. I was ecstatic when the Giants called his name. He roasted NWL pitching, and I believe he has the bat to continue that trend moving forward.

#8: Steven Okert, LHP, Age 25 = I know ranking relievers is a tricky deal, but Okert has shown flashes of being an impact arm throughout his pro career. He pitched well in his opportunity late last season and has had a spring that could see him land on the opening day MLB roster.

#9: Andrew Suarez, LHP, Age 24 = He’s a Ty Blach type, but with better fastball velocity. There’s a good chance he spends some time in Sacramento this summer. How will he handle the jump?

#10: Sandro Fabian, OF, Age 19 = I’ll admit I don’t know as much about this kid, but he torched the AZL as an 18 year-old, and is consistently getting mentions among the system’s top 10. Currently projects as a solid all-around RF, but still has a long way to go to get there.

#11: CJ Hinojosa, SS, Age 22 = A sneaky upside pick in the 11th round, he turned heads almost immediately in his first full season. Most projections have him as a below average SS, more of a utility type.

#12: Austin Slater, OF, Age 24 = Athletic IF/OF had a power uptick last season, and might just be the super utility type the Giants have been longing for. He’s got a real shot to see big league time this year.

#13: Aramis Garcia, C, Age 24 = Injuries have slowed his development, but his arm and defensive chops still make him a significant prospect in the system for me. Will his bat catch up?

#14: Joan Gregorio, RHP, Age 25 = 6-ft-7 arm has been around a long time. AAA batters hit him hard, but his K rates were some of the best of his career. I envision a future power arm out of the bullpen.

#15: Sam Coonrod, RHP, Age 24 = Another guy with velocity, but concerns about whether he’ll remain a starter. I haven’t seen him this spring, but thought his stuff looked pretty electric at times last year.

#16: Chris Stratton, RHP, Age 26 = Hasn’t lived up to his 1st round pedigree, but he did take a step forward last year and should see more time in Bruce Bochy’s bullpen this season.

#17: Reyes Moronta, RHP, Age 24 =  He took over the closer’s role in San Jose when Rodolfo Martinez moved to AA last summer and had a huge season for the Giants. He’s a smaller guy, but his fastball sure isn’t.

#18: Dan Slania, RHP, Age 24 = Big Dan became a starter last season and had himself a nice season. I could have put just about anyone in this spot, but I’ve always envisioned Slania as a big league arm. If he can start, that sure ups the ante.

#19: Ryder Jones, 3B/1B, Age 22 = Ryder takes his fair share of heat, but he also showed pretty good pop in Richmond last year. More importantly, the Giants believe in him.

#20: Miguel Gomez, Inf, Age 24 = Let me put it this way. Gomez can flat out hit. Now he’s hitting for power too? I’m sure someone will find a spot for him one of these years (he’s on the Giants’ 40-man now too).

Honorable Mention: Matt Krook, Rodolfo Martinez, Clayton Blackburn, Ray Black, Jonah Arenado

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Game Score Plus Part 2: Some Context

Morning all. If you missed my introduction post last night, here is the link. In a nutshell, I explained that my calculations of Game Score “Advantage” failed me in that they didn’t hold up well between generations. A pitcher who started 40 games might regularly accumulate an Advantage score between 600 & 700, where today’s best pitchers often don’t even make it to 500 (Max Scherzer was #1 in 2016 with a 459).

Another major downfall of Advantage was the fact that nobody had any idea what it meant. Whenever I posted scores on my Cove Chatter Twitter page (which admittedly isn’t the best place for this kind of information), I was almost always prompted to provide an explanation of what those scores actually meant, how they were calculated, etc. Tip: if you’re going to come up with some cool, new metric to evaluate something, it better be easy for the general public to understand. As I learned, Game Score Advantage wasn’t.

If I was going to find the most dominant pitching seasons of all time (using Game Score), I needed a better way to compare pitchers across the decades.

That line of thinking led me to Game Score Plus, a simple metric that puts a pitcher’s Game Score Average in direct comparison with his peers that season, 100 being the league average.

Continue reading “Game Score Plus Part 2: Some Context”

Game Score Plus: An Introduction

It’s been feeling a little dull around here since WordPress nixed the MLB-themed blog pages, so I finally made it feel a little more like home. Now, what say we do a little “blogging?”

Game Score is simply another way to look at a starting pitcher’s performance, be it an individual start, a month, season, or career. It’s not perfect, and Tom Tango has altered the original Bill James model (used on Baseball-Reference). Tango’s new GmSc formula is listed in the pitcher game logs at Fangraphs. I have a BB-Ref play index subscription – which is not only time saving but also unbelievably deep –  so I always refer to the original Game Score.

I have used GmSc to look at pitcher performance from a number of different angles. I categorized every start from 2016 as either a win, loss, or no decision, with qualifying scores set for each league. That was a serious undertaking, one which I probably won’t do again, but it did, in my opinion, make a pitcher’s win-loss record actually mean something.

Continue reading “Game Score Plus: An Introduction”

2016 Giants Rotation: A Game Score Breakdown

Last winter, I discovered and fell in love with Bill James’ Game Score metric. In hopes that you’ve read some of my previous posts on the subject, I’m going to spare the basics this time around and jump right into my analysis of the Giants rotation this year.

First, a few quick things to note. With the immense help of a Play Index subscription via Baseball-Reference.com, I spent the majority of the 2016 season not only tracking Game Scores on a day-to-day basis, but also diving into the all-time greats (both individual seasons and careers), comparing different generations and adjusting what I had previously thought to be the benchmark scores for Game Score decisions (W-L-ND). I wanted to provide insights to a few of those adjustments here.

The cheat sheet:

In the current MLB Game Score era (roughly 2012-present), the pitching decisions are as follows.

National League

Win = 58 GmSc or higher | Loss = 46 GmSc or lower | ND = GmSc 47-57

American League

W = 56 or higher | L = 43 or lower | ND = 44-54

Continue reading “2016 Giants Rotation: A Game Score Breakdown”

Top of the 9th: A Fitting End

Has it really been six months since my last post? Man. For the few folks out there who actually dedicated their time to following this site, I really am sorry. I could have at least put out some dead-end signs to warn you. Just one of those seasons, I suppose.

And boy, was it one of those years. The slow start, the torrid June, the murky waters for the Shark, the injuries, the inept second-half offense, Cueto & Bumgarner, the trade deadline, losing Duffy, losing the division, losing leads… And that bullpen. Damn that bullpen. This season wasn’t without its great moments (like absolutely owning the Dodgers in the early going, and again on the final weekend), but it sure was a trying one, wasn’t it?

About two weeks into September, I reached my breaking point. I had such high hopes for this team, especially with the revamped rotation (which was still one of the best in baseball, as Game Score will prove – more on that in a future post), but we were two weeks from October ball, and this just wasn’t a playoff team. Not to me, anyway.

And somehow, they still found a way. It doesn’t matter how many championships you see, there’s still nothing like the postseason. Just ask Conor Gillaspie.

Continue reading “Top of the 9th: A Fitting End”

The Beauty of Game Score

Happy weekend… and welcome to San Francisco, Shark Samardzija! The Giants are finally off the shneid (for one day at least), and I thought today would be a good day to check in.

Ok folks, here’s the harsh reality. Cove Chatter is no longer a day to day blog – it hasn’t been for quite some time.  At this rate, it’s not even really a weekly blog anymore. I do feel guilty about that sometimes, but that’s why I have a Twitter account where I’m active nearly every day.

If you’re looking for that kind of coverage, the Giants beat writers are some of the best in baseball as far as I’m concerned. On the minor league front, there are so many places now to get your fill of prospect information. DrB’s is always a daily stopping point for me, as are Roger Munter’s daily recaps on McCovey Chronicles (I’m not sure I’ve ever given a plug for MCC, but Roger does an awesome job over there).

If you didn’t know, Conner P is back in the mix over at Giant Potential as well. He too does a much better job of covering the organization day-to-day than I could dream of. He’s asking for a small subscription commitment this year to help him keep things going. It’s far less than any other paid baseball site out there, and it’s highly recommended coverage.

As for me, I’ve been ready to take on something different a while now. I’ve been intrigued by baseball stats since my childhood card-collecting days. I was good at math all through school, though I didn’t take any stats classes in high school or college. I’m not into 95% of the advanced metrics, and I probably won’t ever be. But I have always played around a little with numbers and (very) simple formulas, in hopes of finding a new way to look at a baseball player.

Though I certainly didn’t create it, game score has really changed the way I look at baseball. There are three main reasons, I think, for why I have fallen in love with it. First, it reads more like a fantasy baseball number than any stat on the back of a baseball card – I’ve always loved fantasy, especially the head-to-head points leagues. Second, game score, though created by Bill James himself, has never caught on as a favored method of evaluating starting pitchers. It’s that “something different” I’ve been searching for. Finally, game score makes evaluating a pitcher so much easier to me. It literally takes all of those “counting stats” from the back of baseball cards (IP, H, ERA, BB, K) and incorporates them into one very clean, simple to calculate number.

Is game score perfect? No. No metric is. As I’ve posted more and more scores to Twitter lately, some people have asked me whether it is adjusted for park factor, opponent, etc. The answer is no, although I found a Bill James article from a few years ago where he talked about using an adjusted game score formula. I have no idea how I’d ever get my hands on said formula, but you know what? I’m ok with that. It seems everybody wants things to be normalized, adjusted, perfected in today’s society.

But life isn’t perfect, and baseball is no different. Is it tougher on average to pitch in Coors Field than it is in AT&T? Absolutely! But there are days (and even nights) during the season when the ball has major carry in San Francisco too. And honestly, the Rockies play 81 games a season outside of Colorado and still stink. So, while it would be fun to experiment with an adjusted version of game score, it really doesn’t bother me to use the same formula for every pitcher in every park in MLB (and the minors too). Think about this for a minute: when a pitcher gets blown up in Colorado, Milwaukee, Cincinnati, etc., does his ERA get an adjustment because he was pitching in a bandbox? Nope. I’m not sure his game score needs one either.

The beauty of game score for me is that I can sort the information in so many different ways. I can sort by the total game score a pitcher has accumulated during a season (total GSc), his average score (Avg GSc), his record based on each start (a “true” calculation of wins, losses, and no decisions, if you will), or the game score advantage (Advantage) that he’s earned over the course of the season. Game score advantage is a new wrinkle I added into my spreadsheets, and it was something Bill had mentioned in that article about adjusted GSc. What it boils down to is a + or – rating from the base score of 50 that each pitcher starts every game with.

For example, Jeff Samardzija’s 68 GSc (a win) from last night bumped his total Advantage for the season by +18, while Jarred Cosart’s 18 GSc (loss) dipped his Advantage a whopping 32 points for the year. In 2015, Clayton Kershaw owned the highest mark in MLB at +594. Kyle Kendrick was dead last at -213. That’s an 800 point difference. Just think about that for a second!

I can also use game score to measure team success. And quite often (as I showed in a post this offseason), the correlation is pretty solid. Consider our 2016 Gigantes, who have accumulated a game score record of 6-8-4 so far this year. If we take the 4 no decisions and evenly distribute them into the wins and losses, that’s a record of 8-10… exactly the same as the club in real life. Now, it doesn’t match up perfectly for every team, but it’s not too far off on most. That’s pretty cool to me (the correlation, not the 8-10 Giants record!).

Side note: I’ve explained this in previous posts, but a game score “win” is earned by a score of 55 or higher. So far this season, teams whose pitchers who pass that threshold are winning 70% of the time (165 wins in 234 chances). A no decision is handed out for a score of 44-54. Teams have won 46% of the 110 games where pitchers have scored in that range in 2016. A loss is given for a score of 43 or less (32 wins in 148 chances this year; 22%).

Another side note:. Apparently statistician Tom Tango (he goes by the nickname Tango Tiger) loves game score as well. He’s even created a new version (2.0) that starts each pitcher with 40 points instead of 50 and gives more reward for innings pitched. I’ve been reading a lot of Tom’s work lately, and I really like the version 2.0, which can be found in pitcher game logs at Fangraphs (the classic score can still be found in Baseball-Reference and MLB box scores). I’d love to take a closer look at it, but at this point, I have no desire to recalculate almost a month of data I’ve logged from this season.

Ok, so let’s take a look at what the numbers are telling us in 2016, both for teams and individual pitchers.

Team GSc Wins

  1. Cubs = 13
  2. White Sox, Dodgers, Phillies, Nationals = 11

Giants = 6

Team GSc Avg (league average is 51.8)

  1. Cubs = 63.5
  2. Nats = 59.8
  3. White Sox = 58.8
  4. Phillies = 57.7
  5. Royals = 56.6

Giants = 49.1

Individual Total GSc

  1. Jake Arrieta = 301
  2. Clayton Kershaw = 283
  3. Chris Sale = 281
  4. Jon Lester = 262
  5. Edinson Volquez = 250
  6. Jose Quintana = 241
  7. Cole Hamels = 235
  8. Sonny Gray = 234
  9. Jonny Cueto = 229
  10. Aaron Nola = 229

Individual GSc Avg

  1. Jake Arrieta = 75.3
  2. Noah Syndergaard = 71.0
  3. Clayton Kershaw = 70.8
  4. Vince Velasquez = 70.7
  5. Chris Sale = 70.3
  6. Stephen Strasburg = 69.7
  7. Mat Latos = 69.0
  8. Drew Smyly = 68.7
  9. Danny Salazar = 67.7
  10. Ian Kennedy = 67.3

Individual GSc Wins

Arrieta, Kershaw, and Sale are tied for first at 4-0-0. There are 23 pitchers who have 3 GSc wins this year.

Advantage (Top 10)

  1. Jake Arrieta – +101
  2. Clayton Kershaw – +83
  3. Chris Sale – +81
  4. Noah Syndergaard – +63
  5. Vincent Velasquez – +62
  6. Jon Lester – +62
  7. Stephen Strasburg – +59
  8. Mat Latos – +57
  9. Drew Smyly – +56
  10. Danny Salazar – +53)

Giants: Cueto +29; Samardzija +24; Bumgarner +10; Cain -22; Peavy -57

158 pitchers have started a game in MLB this year. Peavy’s -57 advantage is #156.

That’s a lot of information, but I hope I’ve laid it out in a manner that’s easy to read and comprehend. I’ll post more as we move through the season. I’m keeping tabs on SP prospects throughout the Giants organization, and will give periodic updates on that front as well. What are your thoughts? Does game score pass the sniff test? Should it get more recognition and coverage? I’ll let you be the judge of that.

As always, thanks for reading, and have a great weekend!

 

 

 

Week One in the Books

Checking in on a Sunday night for a quick look at our 1st place Giants, as well as some tidbits about starting pitching around MLB.

Giants – A Whole Lotta Runs

It’s important to get the season off on the right foot. Remember last year’s April slide? Well, 5-2 (good for 1st in the West) ain’t bad at all. When you consider a 1-run loss in Milwaukee and a blown 9th inning lead against the Dodgers are the only blemishes, it’s easy to see that this is one of the hottest clubs in baseball at the moment.

Though the bullpen’s done a pretty nice job of limiting runs, the rotation hasn’t hit full stride so far (Bumgarner’s Saturday notwithstanding). Still, you have to admire Cueto’s tenacity today. All kinds of dinks and dunks plus a ton of bad luck, and he’s looking at a 5-0 hole in the first. Six innings later, he’s pitching with a 9-6 lead. That dude can absolutely pitch, and his teammates had his back today. Would Hudson/Vogey/Lincecum have been able to get back on the bump for 7 innings like that last year after laboring through the first? I’m not so sure.

Anyway, this team is riding an offense that is #1 in MLB runs scored, #2 in homeruns (sometimes spring training trends DO continue!), #5 in OPS, and #6 in walks. This is supposed to be a team of gap hitters, but so far they’re putting the ball over the fence with ease. It’s been fun to watch. You know what else I love about this lineup? They’re 6th in the league with only 36 K’s. Every team above them (Miami is #1 with 30) has played 2 or 3 fewer games. Most lineups who hit the long ball also swing and miss. The Giants are packing the punch without striking out. Now THAT’s impressive.

What About Game Score?

I wrote extensively about pitcher Game Score (GSc) this offseason and have taken on the challenge of calculating it for every starting pitcher in every game this year. Remember, Game Score is an easy to calculate metric (start with 50; add 1 pt for every out; 2 pts for every IP after the 4th; 1 pt for every K; subtract 2 for every hit; 2 for every run; 4 for every earned run; 1 for every BB).

Game Scores are often used to compare dominant outings (particularly no-hitters & perfect games), but very few people have ever used them to compare pitchers (and rotations) over a full season or a career. When IP, ERA, H/9, BB/9, and K/9 are still some of the most prevalent counting stats used to evaluate pitchers, why are we not using a metric that combines all of them into one I ask?

A study was done by Sabr.org in 2007 to show the correlation between specific game scores and team wins. Long story short, a pitcher who earns a score of 55 or higher gives his team at least a 60% chance of winning, while a score of 43 or less lowers the team’s win probably to under 40%. The middle area, that 50/50 spot, falls in the range of 44-54. I use this information to award pitchers with wins (55+ GSc), losses (0-43), and no decisions (44-54).

So, just how has the league fared so far in the eyes of Game Score this season?

MLB Totals: 172 GP, 75 W, 54 L, 43 ND – .436 win% | 50.6 GSc avg

NL Pitchers: 87 GP, 37-31-19 | .425 win%  | 49.8 avg

AL Pitchers: 85 GP, 38-23-24 | .447 win% | 51.4 avg

The league average looks to be pretty close to last year (Baseball-Reference lists it at 52 for 2015). How are the win probabilities holding up so far? Teams whose SP’s earn a 55 or higher (GSc W) are winning at a 71% clip. 44-54 (GSc ND) have a win% of 44%. Scores of 43 or less are winning at only a 26% clip so far.

Top 5 GSc by Team

Royals 60.8 | Dodgers 60.7 | Cubs 60.3 | Phillies 58.3 | Mets 58.2

Bottom 5 by Team

D-Backs 37.9 | Rockies 39.2 | Padres 40.5 | Cardinals 40.8 | Astros 41.8

Giants: 2 W -3 L- 2 ND (49.1 avg)

It’ll be interesting to check back in on these throughout the season. If the trends of the first week continue though, the Giants are going to have a lot of fun scoring runs against NL West pitching. As we get a little farther along, I’ll start posting individual pitcher scores and W/L records. For now, it’s a little too early for that. I do know that Clayton Kershaw leads the Majors with a 76.5 Avg through 2 starts. Zack Greinke? 32 Avg.

After two starts of their own Bumgarner’s average is 54.5, Cueto’s is 52.

Thanks for reading everyone. Here’s to another great week of Giants baseball!