## Dave Righetti: Lord Of The HR/FB Rate

In a couple of recent posts, I created and then tested a regression model which helps explain the variance in home run per fly ball rate. I ended up with a model which performed really well, so it’s time to turn it loose on the question that sent me down this path in the first place: can Dave Righetti really coach his pitchers to a better HR/FB rate? It turns out, the answer may be “yes”, and it could be more emphatic than I would ever have guessed.

Up until this point, the model included data from 2002-2009, leaving last season out of the sample for testing purposes. Now that I’m satisfied with the validity of the model, I’m going to throw the 2010 data into the sample to increase the sample size and get the most accurate coefficients as possible.

The first instinct for testing this hypothesis might be to compare the model’s projections for Righetti’s Giants against the league average. But since there have been countless manager and pitching coach changes in the league since 2002, comparing Righetti against the aggregate performance of the rest of baseball might only prove that having a consistent coach produces better results. After all, a pitching coach who has held his job for nine-plus years must be doing something right. Instead, Righetti will be tested against the four other pitching coaches who have been with their teams since 2002. Those coaches are the Cardinals’ Dave Duncan, the White Sox’s Don Cooper, the Cubs’ Larry Rothschild and the Twins’ Rick Anderson. True, Rothschild is now with the Yankees, but since the time frame is 2002-2010, he is safe to include.

The first test is to see how many of each coach’s starters outperformed the HR/FB rate that the model would predict. Using the same data restrictions from when the model was built (80-plus innings, same team all season), each coach has between 40 and 48 qualified pitcher-years in the sample, meaning one pitcher’s performance for one season. The question is simply: in how many of those instances did the pitcher outperform his expected HR/FB rate?

For the most part, the model splits each coach’s qualified pitchers in half between those who outperformed their expected HR/FB rate and those who underperformed their projection. Righetti is the only exception. Of the 44 qualifying pitcher-years in Righetti’s reign with the Giants, 38 had a lower HR/FB rate than the model predicted. Considering none of these other coaches had even 60-percent of their pitchers fall on one side or the other, Righetti’s 86-percent rate of starters outperforming their expected HR/FB is simply stunning.

Let’s take things to the next level. Instead of looking at only qualifying pitchers in select seasons (five of Righetti’s pitcher-years were Matt Cain), let’s look at every inning thrown by a starter over the past nine seasons. By plugging data from the multiple season database into the model, we get an expected overall HR/FB rate for the entire time period. Since park factor is one of the variables in the model, a weighted average of park factor was used for the nine seasons. This is particularly important for Anderson’s Twins since they moved ballparks during the time frame.

Again, Righetti is the only pitching coach who seems to have any significant effect on HR/FB rate, and it’s decidedly negative. His starters have a HR/FB almost two standard deviations away from the model’s expectations, while none of the other coaches are over one standard deviation in either direction. Also note that this looks at more than 8,700 innings under each coach’s tutelage. To outperform the model’s expected rate, which predicts the Giants to have a below-average HR/FB already, seems beyond the bounds of luck.

For one last test, let’s include relief pitchers into the sample. Until this point, relievers have been excluded due to their low sample of innings and a general propensity to have low HR/FB rates. But when looking at an aggregation of nine seasons of data, sample size is no longer an issue. It stands to reason that if Righetti can coach good HR/FB rates, he would let his relievers in on the secret as well.

Game, set, match, Righetti. For 13,000 innings over nine seasons, his pitchers have outperformed their expected HR/FB rate by 1.5-percentage points, an effect none of the other four celebrated pitching coaches even came close to matching. Granted, HR/FB rate does not in itself equate to pitcher success, and it may not even be a priority for other coaches. For example, Duncan is notorious for his pitchers’ ground ball rates and Anderson for his staff’s low walk rates. But the question at hand was “Can HR/FB rate be coached?” From the looks of it, the answer may be, “Yes, but only if you are Dave Righetti.”

Doing some quick math shows the impact of the Righetti effect. The Giants have faced 55,874 batters from 2002-2010. Subtracting strikeouts, walks, intentional walks, hit batters and errors results in about 39,000 balls in play. Over that time frame, the Giants had a 37.7 FB%, meaning there were about 14,700 fly balls hit. If the model’s 10.1 HR/FB rate for San Francisco was correct, then Giants’ opponents would have hit about 1,500 home runs, but opponents hit only 1,271 home runs. The difference is over 200 home runs, or about 25 per year.

Considering an average home run is worth 1.42 runs and every 10 runs is roughly equivalent to a win, the team’s home run prevention has contributed about 30 wins to the Giants since 2002, or about three per season. If we were to give Righetti all of the credit for that difference based on an assumed ability to coach HR/FB alone, much less any effect from improving his pitchers’ traditional skills such as strikeout, walk, or ground ball rates, than Righetti would have created about \$110 million in value for the Giants over the last nine years.

It’s unlikely that the difference is all Righetti. We may be underestimating the park factor, or the Giants may target pitchers who can succeed specifically in their park. There is room for a lot of good luck in there as well. But, given that Righetti is one constant in a sea of ever changing variables, and the results continue to stay the same year in and year out, it’s likely that he is part of the answer. We probably need to start including him in discussions about the best pitching coaches in baseball.

Print This Post

Jesse has been writing for FanGraphs since 2010. He is the director of Consumer Insights at GroupM Next, the innovation unit of GroupM, the world’s largest global media investment management operation. Follow him on Twitter @jesseberger.

### 94 Responses to “Dave Righetti: Lord Of The HR/FB Rate”

You can follow any responses to this entry through the RSS 2.0 feed.
1. One way to test whether or not it’s Righetti or the pitchers they acquire is to look at pitchers who pitched for other coaches before or after pitching for Righetti. It cuts down the sample a touch, but you could realistically include relievers too, because his adjustments probably wouldn’t be applied just starters.

2. Steve says:

No don’t include him. He’s ours dammit! Righetti doesn’t know what he’s doing, Bochy doesn’t know what he’s doing. The Giants winning it all in 2010 was a lucky fluke and the Rockies are going to win the NL West this year.

OK what would be interesting to see is how many increased walks his pitchers gave up, because his philosophy seems to emphasize not giving throwing hitters pitches they can crush.

#### -6

It may not be the coaching. Maybe the type of pitcher the giants are making an effort to sign and scout typically have lower hr/fb than expected.

4. Bonferroni says:

5. Bob says:

Very interesting. I’m not really sure how the park adjusted factor works but wouldn’t you want to look at home stats split from away. Is it possible that the giants home adjustment is dominated the home teams numbers? I would imagine this is true for the adjustment number in general as teams would be built to maximize wins in their home ballpark. It seems that the way this is constructed this could be a problem that even with a park adjustment the affect could be larger in certain circumstances. Let’s say Bonds numbers skew the data one way and his numbers could have a significant affect on the park adjustment.

6. Oscar says:

Very well researched and interesting. But, I can’t help but wonder if the park factor being used is 100% correct, as alluded to at the end of the article. Isn’t it also possible he has had above average talent with which to work?

Regardless, Righetti is good. Give him a raise.

• Patrick says:

Oscar,

So you’re suggesting the Giants target players likely to have a lower HR/FB rate than normal? Because you’d have to limit yourself to that stat – In general, better/more talented pitchers aren’t any better at keeping down the HR/FB rate than their less talented brethren.

There may be specific exceptions, but the point is in GENERAL, better pitchers by normal standards aren’t don’t have significantly better HR/FB rates.

7. Telo says:

Sometimes when we dive into a problem or data set, we forget the bigger picture. It’s just a ridiculous idea that pitching coach can have a significant influence over his staff’s HR/FB rate. It’s like saying, Joe Girardi teams hit .350 on Mondays and .200 on Wednesdays, and look, I have 10 years of data to back it up. Do you really think Girardi is making the difference, or is there something else at play, be it luck, or other factors.

Simply, I don’t buy it for a second.

#### -8

• phoenix2042 says:

the problem is that the trend persisted at a statistically significant level for 10 years and 13 thousand innings. it’s simply impossible for it to be luck for that long, that huge of a sample size and that many different pitchers. the hitting .350 on mondays example is invalid because a) girardi has not been coaching for 10 years and more importantly b) you’re making it up as an example that is supposed to look ridiculous and contradict the article. it does look ridiculous, but unfortunately your funny little idea holds no weight compared to the actual reality that the conclusion in the article is supported by 13 thousand innings of data of giants pitchers beating hr/fb projections at a statistically significant rate in which the only constant is dave righetti. if you have a better conclusion that you can back up with solid data from a legitimate sample in which you have only one variable and not just a fictitious and ridiculous made up example, let’s hear it.

#### +8

• Bonferroni says:

See my comment above. If you run 200 significance tests, about 10 will be significant. If you want to maintain 95% confidence levels, you have to multiply the p-values (divide the t-stats) by the number of tests you did.

• MikeS says:

It’s never “…simply impossible for it to be luck…” it’s just less and less likely. My stats education is way out of warranty but I believe if the performance is 2 SD above the mean that implies a 2.5% chance that the results did occur by luck. That may be wrong, I may be confusing p values (which were not stated) or some other way of measuring statistical significance.

• Telo says:

@ MikeS

And that 2.5% is assuming a flawless model, which this is not.

• TonyAngelo says:

or Correlation is not Causation.

I agree that there are likely other factors at play here.

• phoenix2042 says:

my main issue was his example of girardi teams as invalidating the article. because he proposed a ridiculous and impossible scenario out of thin air and asked if we believe it. and of course no one would believe it. but it has absolutely nothing to do with the article at all, it’s just an appeal to inherent belief bias. i mean i can make up crazy examples of anything i want and then claim that it proves someone is wrong about something completely different too, but that doesn’t mean anything. it’s the moral equivalent of saying something like “what if I told you that the sky is red on all mondays and yellow on all fridays? you wouldn’t believe it right? yeah, so then the work week is a myth, no one works monday through friday.” it simply is not a logical rebuttal to the article.

i have no problems with disputing the conclusions in the article, i just want something besides “i don’t buy it for a second” to be the justification, that’s all.

• Antonio bananas says:

what about this one. When ice cream sales go up, so do shark attacks (fact). Thus, people who have digested ice cream must be something sharks crave? Or is it just a correlation that doesn’t actually mean anything and more than likely, it’s hotter when people eat more ice cream and swim more. I don’t doubt that Righetti is a great pitching coach. Maybe we’re understating the park effect somehow, or maybe pitchers feel more comfortable naturally in that park and when it’s their home park, they learn to “pitch to the park” better? Lots of possible scenarios.

• Matt says:

Seriously Telo, I’m with you; if I understand correctly, it’s as if he’s saying that part of the success a particular pitching staff has had might be due to the pitching coach. What’s next? Is he going to ask us to believe that a player’s strength and athleticism contributes to his value on the field? It’s a preposterous hypothesis, and it’s exactly like saying Joe Girardi makes his teams hit .350 on Mondays.

• Telo says:

Something tells me you’ve never played on a baseball team. The pitching coach is not throwing pitches, calling pitches, or doing anything remotely impactful enough to affect fly balls/HR like this. If he was…………. don’t you think someone might catch on and start doing it too?!

Yes telo the coach is not throwing the pitches but he does impact outcomes. Look at the Twins pitcher BB rates. Do you think all these pitchers pitch to contact by choice?

• TonyAngelo says:

Twins pitchers BB rates is a great example of why you can’t give all the credit to the pitching coach.

In Minnesota, throwing strikes is an organization-wide philosophy that effects not just player development, but who they draft and sign in the first place.

By the time they make it to the big league club they don’t really need Rick Anderson to remind them to throw strikes.

• Antonio bananas says:

Telo, I’ve been on a baseball team, I’ve pitched, a piss poor pitching coach is why I went from starting district games as a freshman to feeling awkward when I throw. A great pitching coach is why from age 7 to 14 I was really good (compared to my peers). It’s stupid, like really dumb, to think a pitching coach doesn’t help. good coaches can get in your mind and help you figure things out.

8. rwinter58 says:

wow, just a great article i really loved it. Crazy interesting

9. neuter_your_dogma says:

I’d compare HR/FB with other pitching staffs in the NL West during this time, minus Bonds of course. Could be that Duncan’s staff faced more power oriented lineups. AL is not a fair comparison, as a FB hit by a pitcher isn’t the same as a DH.

• neuter_your_dogma says:

Doing a HR/FB% for 2002-2010 in the NL West, Colo ranked 8th in the ML (11.2%), AZ 16th (10.3%); Dodgers 22nd (9.5%) and Padres 28th (8.9%).

• AJS says:

How much of that is park-based? I would guess a fair bit.

10. phoenix2042 says:

so basically righetti is a 3 WAR player. that’s pretty awesome. since he had a 24 WAR career, can we just add these wins and say he’s been worth 54 WAR now?

#### +21

• Telo says:

See what you started?

• phoenix2042 says:

imagine dave duncan’s WAR now! lol

• hairball says:

I wish I could hit the plus key twice for this comment! Bravo!

11. Great analysis, and not just because it’s about the Giants. :^)

I was wondering how the data would look if you did only relievers (based on SD, look like even bigger spread, and they should pitch in more leveraged situations than general) and if you compared home vs. road numbers. The latter might answer your question about pitching at home being an advantage.

I know that the data will be pretty miniscule, and might be hard to collect, but there are some pitchers who pitched after the Giants, like Russ Ortiz, Livan Hernandez, Shawn Estes, Joe Nathan, among others. It might be interesting to see how they collectively did as a Giant, then how they collectively did afterward. Now, some of this would be skewed by that they are older and therefore probably not as good. But Ortiz, Livan, and Nathan had at least a couple of good seasons afterward. And there were a number of relievers who left the Giants and continued to do well enough, like Alan Embree, Julian Taverez, to have a long after-Giants career.

That is a lot of wins to attribute to a coach, which shows up in the pitchers’ stats.

This brings up a question I’ve been wondering about for a while now: with all the proliferation of WAR estimates, there will be pitchers who are undervalued solely because they don’t fit the DIPS model, are outliers. One already well known outliers are pitchers who ARE able to control their BABIP during their careers, particularly knuckleballers and crafty lefties (per Tom Tippett’s excellent examination of DIPS when he was at Diamond Mind). Now there are pitchers who are able to regularly produce reduced HR/FB, albeit, when they are with the Giants. What is the right WAR for these types of pitchers?

Now for the HR/FB, I can see not giving them credit for it since it appears to be a coach-related phenomenon, but reduced BABIPs are clearly pitcher-dependent, so shouldn’t there be retroactive upgrading of WAR when a pitcher proves (by statistical significance, TangoTiger said roughly 6-7 full seasons of starting pitching IP) to be able to do that (plus knuckleballers would get it immediately)? Otherwise, they are penalized for having a skill that most pitchers do not have but would love to have, which don’t make sense to me.

• anon says:

that was almost longer than the original post, no one will read it

i read the first few sentances

• Viliphied says:

It’s OGC. It’s kind of his MO

• Kevin Yost says:

i call it the adderall effect

12. bcp33bosox says:

Pretty amazing stuff and a lot of fun to read.

13. DavidMI says:

Like some of the other posters, I also enjoyed reading this, but I also have some doubts about it.

Regarding the park factor, one way to test for this would be pretty easy: What was the Giant’s HITTERS rate of HR to FB? If that correlates well with the pitchers’ very low HR/FB rate, then I think it’s safe to say that the park factor was somehow incorrectly applied.

The Giants’ stadium has registered as a slight hitters park for the past few seasons (according to Baseball-Reference and ESPN’s measures), but I would guess that it still suppresses home runs.

But unless there was a MAJOR miscalculation, then this concept can go hand-in-hand with the Giants’ pitchers epic September through October performance last year and his longevity as things that cement Righetti’s status as one of the best.

• zenbitz says:

the park is weird. It suppresses HR to RF but not LF.

I think there is enough data here over 10 years to split it into home/away and LHB/RHB.

14. Locust says:

Great stuff. Thank you.

The relative BB rates would be interesting to know for sure.

Would be interesting to know Rags’ HR/FB rate from back when he pitched (small project….only ~1400 IP). He did walk a lot of guys for a RP, and didn’t give up too many dingers. Interesting.

15. Scout Finch says:

The transformation of Jonathan Sanchez into a legit #2 may be Righetti’s finest hour as a pitching coach. Stay tuned to the 2011 season…

• hringer says:

His FIP was ugly. The BABIP and LOB% Luck Dragons are going to eat him next year.

or he could outperform his FIP like someone he plays with

oh gosh he is coached by Righetti too

• Patrick says:

adohaj… Matt Cain outperforms his xFIP, and performs about in line with his FIP. Almost all of the difference for him is with xFIP.

Snark, fail.

16. skipperxc says:

You, good sir, win the internet today. Fascinating stuff.

17. Matt says:

Great article: good analysis and a really good read.

But I think the calculation of Righetti’s WAR is a bit of an overestimate. It is assuming that all of those fly balls that should have been HRs instead were caught for outs. Isn’t it likely that a good percentage of them went for hits, thus changing the number of runs that were actually prevented?

• dustin says:

Babip on flyballs is really low, right? Like < 0.200?

• Patrick says:

So then the number is 20% lower than given. It’s mostly just a WAG anyway.

18. Cliff says:

Wait, the difference is less than 2 SD, yet it cannot be luck? That does not compute to me. By definition, wouldn’t luck produce those results what, 5% of the time? And of course you are investigating the person with unusual results. Luck sounds like a definite possibility.

19. Oscar says:

I don’t understand how any of this points definitively to Righetti. You’ve already established that pitchers exert control over their HR/FB to some degree. How do you determine whether Righetti taught Cain, for example, to control his HR/FB or whether he’s just the MLB pitching coach for the team that Cain’s on?

• Viliphied says:

Because looking at the team as a whole, there definitely seems to be an organizational philosophy, similar to Duncan with ground balls. It seems, to someone who watches 130+ Giants games a season, that the organization would much rather surrender a walk than a HR, and tells its pitchers not to just groove a fastball on traditional “hitter’s counts”.

• Steroid Shuffle says:

Well then it would be a massive coincidence that every pitcher on the Giants since 2002 happened to be able to control their HR/FB rates, while the rest of the MLB couldn’t.

• Doug Lampert says:

What massive coincedence? If there is ABSOLUTELY NO organizational bias toward pitchers with a good HR/FB ration, and the pitching coach had ABSOLUTELY NO effect whatsoever. Then there’s roughly a 5% chance per team of results this far off expected.

30 teams. 5% per team.

That’s your MASSIVE COINCEDENCE?! That this hit once? And the period of performance is also chosen non-randomly. By choosing periods of performance and teams and whether I’m claiming they’re high or low there are hundreds and hundreds of HR/FB ratios to examine. 5% proves nothing. It doesn’t even do a particularly convincing job of suggesting anything.

20. Oddibe McBlauser says:

Wonderful article, and props are in order for the excellent comments as well. Such good analysis deserves to be buoyed by the high potential for further analysis everyone’s already proposed. Jolly good show….

21. Nate says:

Question: Can Carson Cistulli’s work with estimating GB% from GO/AO data be used to extend this analysis to years prior to 2002?

If so would give you some more example coaches as well as giving Righetti some data from Candlestick.

• Nathaniel Dawson says:

Couldn’t use Cistulli’s calculation, as it’s for groundballs. If someone did the same kind of analysis on flyballs, it might give you something to work with.

it is likely that the same tactics that allegedly induce a lower hr/fb rate could lead to more walks.

– from 2002 to 2010, the giants walk rate (bb/9) was 3.6.
– mlb average walk rate over that span is 3.329. that is a difference of .271 walks/9ip.
– multiplied by the 13008 innings the giants pitched over that span and then divided by 9 you get an additional 391.7 walks.
– linear weight for a walk is .62 runs. multiply times the extra walks to get 242.9 extra runs allowed over the span.
– using 10 runs per win, the giants extra walks led to -24.3 wins

30 wins + -24 wins = +6 wins from 2002-2010

nevermind whatever effect facing a pitcher and not a dhl, home park and division parks, winds at sf, and having a few elite pitchers on your staff could do to hr/fb rates. oh and luck and random variation.

• Nate says:

Linear weight for a walk is .33

• Viliphied says:

Correcting that mistake, the walks take away 129.2 runs, or about 13 wins.

So, 30-13 = 17 Wins over 8 seasons = ~2 Wins/season.

Still pretty significant.

Nate –

good catch. i was thinking of the walk weight used for wOBA which is on a different scale. thanks.

overall points still stand though, i think. seems silly to credit the coach for hr/fb weight while ignoring walk rate. might as well credit adam dunn for his offense and ignore his defensive prowess.

villiphied –

2 wins is still significant, but who says you can attribute that all to righetti. as i said, park effects (size, wind, weather), facing a pitcher and not a dh, the offenses of the teams in their division, and luck/variation all play a part too. righetti probably has some effect but it was almost definitely overstated.in this piece.

for 2002-2010, the other teams offenses in the nl west have ranked in the nl::
runs scored – 2, 10, 13, 14
hr/fb % – 5, 9, 13, 16
woba – 2, 9, 13, 15

inot exactly top offenses to pitch against. and as davidmi mentions, the giants offense has a low hr/fb too, so the park certainly has some effect.

23. fergie348 says:

Shouldn’t the title of this piece be ‘Dave Righetti, Lord of the Flies’? I mean, shouldn’t it? Don’t you people have any cultural awareness apart from baseball?

#### +17

• dustin says:

This is pretty subtle. You should probably have ended it with a tag

• Tron says:

Whoa whoa whoa… who you callin’ “you people”?

24. Chris says:

Wouldn’t it make more sense to track the HR/FB rate of pitchers over time while under the tutelage of Righetti? This way, you could better isolate his effect on the pitchers away from the ballpark/drafting/organizational development factors. Of course, you’d have to do this with other long-tenured pitching coaches for a more meaningful comparison.

• dxclancy says:

Also, how about tracking Giant’s pitchers at ATT Park *before* Righetti?

• dustin says:

That would be tough to do, as the park opened in 2000, when Rags started as the Giants’ pitching coach.

25. DavidMI says:

I just checked Fangraph’s database, hoping to compare the Giants’ 2001 HR/FB rate vs. their 2002 HR/FB rate but, unfortunately, that stat only started tracking in 2002. So I can’t compare the Giants to the year before.

However, I did do something else that I thought was worthwhile, and that was to check how the Giants HITTERS did in HR/FB. Because if the hitters also had an unusually small rate, then I think that a large factor in the cause of this unusually low HR/FB rate would be the ballparks that they were playing in.

The Giants hitters had the sixth-lowest HR/FB rate from 2002 to 2008 of the 30 MLB teams. While the Giants pitchers only gave up 8.6 home runs for every 100 fly balls, the Giants hitters only hit 9.2 for every 100 fly balls.

The ML average for home runs for every 100 flyballs was 10.4. So the Giants pitchers deviated from that at about -1.8, while the Giants hitters deviated from that by about -1.2. (Stat note: that’s just deviation from the mean; I’m not too good with standard deviation.)

Because of how close the Giants hitters were to the pitchers, I think that it’s almost certain that the ballparks (home and road) played a significant factor in the home run suppression – at least as big as any other factor. That’s my opinion.

• Azmanz says:

It’s possible that the Giants’ hitters have just been weak compared to the league. You’d have to compare Giants’ hitters road splits v home splits to determine if the park made an affect.

26. Matt says:

The HR/FB rate for Giants hitters during that time span may not be that useful The Giants had some AWFUL offenses during that time. Bonds was a shadow of his former self after 2004 (for him at least) and let’s not forget that Bengie Molina was the team’s feared cleanup hitter (and leader in HR’s) for two full seasons.

• AJS says:

But how is that different than saying Giants’ pitchers pitched against some terrible offenses (and threw a lot of their games in pitchers’ parks like Dodger Stadium and Petco)?

• rectin says:

One difference is that the awful Giants offense played in every game involving the Giants, whereas the Giants pitching staff still has to play against every other team in the NL and a few in the AL. In other words, the Giants offense has been much worse than the cumulative offense of Giants’ opponents.

27. DavidMI says:

But if we’re going to blame the individual Giant hitters for a low HR/FB rate in that same era, then shouldn’t we credit the individual Giants pitchers (rather than Righetti)? It seems like the logic is inconsistently applied.

In either case, you’re talking about dozens and dozens (hundreds and hundreds?) of Giants players, against thousands of different competing players. Given the similarity of the two numbers (the -1.2 for the hitters and -1.8 for the pitchers), I think that the best thing to look at is the common thread, and that is the stadiums and conditions in which they play.

• CJ says:

Hitters are expected to have significant influence over their HR rates (i.e., we don’t think Pujols is just lucky because his career HR/Fly ball rate is close to 20%). The conventional theory is that pitchers have relatively little control over their HR rates, and thus we expect pitchers’ HR/flyball rates to regress to league average. For that reason, I don’t think you can directly compare the HR/fly ball rates of the Giants’ hitter and pitchers.

• DavidMI says:

I think you’re right – that’s an important distinction that I realized after I typed that post. But if that’s true, then it also negates the entire hypothesis of the article because, of course, a pitching coach sure as hell couldn’t control anything if the pitchers themselves couldn’t.

But there were plenty of other pitching staffs well below the mean FB/HR ratio in that time (the A’s and Marlins were both at -11 and -10%) which demonstrates that there’s persistence amongst pitchers. Whether that’s caused by the park or the pitching staff is a separate question.

More importantly, we’re talking about hundreds and hundreds of Giants hitters and pitchers over the past nine seasons. And because they all seem to average out to a very similar HR/FB ratio, my guess would be that it’s the park, rather than the individuals, that’s the main cause of this.

There are lots of other studies that could be done to test this hypothesis. To separate the Giants starters (who could have similar natural talents that skew the results), just the bullpen could’ve been tested. Better yet, just the bullpen on the road! And I wish we could get the 2001 numbers and compare them to 2002!

But the pitching coach to pitching coach comparison seems a little bit screwy to me, after further thought.

28. KJOK says:

AT & T Park has supressed HR’s 18% over its life, while triples increase 39%. Seems pretty obvious it’s the park keeping more fly balls in the park instead of the pitching coach?

• The Ancient Mariner says:

Yes, it does . . . which might be why it’s included in the original analysis . . .

• Nate says:

The initial model already takes park effect* into account. It’s saying Rags’s numbers are even lower than that.

*Now certainly possibly that park effect not entirely correct.

29. Nick says:

Yes, Righetti’s pep talks and pointers magically lead to flyballs dying out in triples alley.

Fangraphs- Going down the tubes, quick.

#### -10

• Victor Frankenstein says:

“We probably need to start including him in discussions about the best pitching coaches in baseball.”

I am shocked – SHOCKED, I say – at the possibility that this was not already the case.

30. Ryan L says:

31. DrBGiantsfan says:

Great article. I have watched literally hundreds of Giants games over the last 10+ years through the magic of satellite TV. I have believed for a long time that the Giants have an organizational philosophy that is risk-averse to the longball. This notion is backed up by bits and pieces of comments made by various pitchers and TV commenators, but mostly comes from years of just watching. Just a few of my observations:

1. 90+ MPH fastballs thrown at the letters or above have a high probability of being hit in the air, if hit at all, but very little chance of being hit out of the park. Hitters just can’t get the bat on top far enough up on the ball to get enough leverage to drive it out of the park. FB’s thrown at belt level are a whole other story. They get crushed!

2. Most HR’s are not hit off pitches that go where the pitcher intended it to go. They are, for the most part, not lazy fly balls that just happen to carry over the fence. Most HR’s are hit off “mistake” pitches that get crushed. They just have a different trajectory off the bat and are quite easy to pick out long before they get close the the fence in distance.

3. It’s absolutely no accident that the Giants have always tended to have higher walk rates at the same time they have lower HR rates. The Giants would much rather walk the bases loaded than give up a 3 run HR, or put a second runner on base than give up a 2 run dinger. They may give in a little with the bases loaded, but I’m not even sure of that.

4. I don’t think the Giants teach HR suppression per se. What I think they teach and preach is “don’t give in to the hitter, EVER!” In practice that results in a higher walk rate and a lower HR/FB rate. For those of you who calculated how many extra runs the walks have cost the Giants, not so fast there! Remember that the Giants pitchers also tend to have unusually high LOB% too!

5. It isn’t just Rags. The Giants absolutely scout and develop pitchers who have the ability to implement this philosophy. BA ran an article last year in which they said the single biggest factor of future success in a pitching prospect is FASTBALL COMMAND. Dick Tidrow and Brian Sabean scout fastball command. I’ve read comments by Tidrow about conversations he had with Sabean before they drafted Matt Cain and Madison Bumgarner and in both cases the clincher for them was the ability to command the fastball on both sides of the plate. Tidrow’s specific comment about Cain before they drafted him was “he’d be perfect for us!” I believe the philosophy actually starts with Tidrow and Sabean. Rags is just the guy who delivers the message at the MLB level.

• Liem says:

As a person who has also watched hundreds of Giants games on TV and in person, I wholly concur with your observations and reasonings regarding the Giants organizational pitching philosophies. Rather than induce ground-balls and neutralize power by working away, the Giants (especially their starters) believe in pounding the top part of the strike zone. Although Dave Righetti himself may not be the sole source of these philosophies, his tenure as the Giants MLB pitching coach coincides with organizational shift in what types of pitchers were drafted and how these pitchers would pitch at the MLB level.

From 1999-2001 the Giants selected Kurt Ainsworth, Jerome Williams, Boof Bonser, Brad Hennessey and Noah Lowry as 1st round pitchers. While all these pitchers were impressive prospects who pitched for significant stretches in the big leagues, none possessed particularly devastating fastballs. Even Noah Lowry, whose career was shortened by injury, rarely touched 90 and owed his impressive K-rate to a wicked change-up.

From 2002 on the Giants selected Matt Cain, David Aardsma, Tim Lincecum, Madison Bumgarner, Tim Alderson and Zack Wheeler as pitchers in the first round. All were noted at the time for their impressive fastballs and have been promoted within the Giants organization according to the development of that pitch. Alderson, of course is the only 1st round pitcher-pick who was traded from the organization before reaching the big leagues. His departure from the organization coincided with a significant drop in his k/9 rate from High-A to Double-A, which likely served as an alarm to the Giants brass that Alderson’s fastball did fit what the team would demand at the MLB level: throw hard and throw high, even if the batter knows that a strike is coming.

The decision is to pitch high in the zone is most definitely a conscious effort by the Giants to suppress home-runs. The Giants strongly believe in locating 90mph+ fastballs high in the zone, regardless of the lateral location (outside, inside, or in the middle) or whether the batter is expecting it, because the high fastball is the most difficult pitch for hitters to “get under” while maintaining a strong hitting position with an upper-cut swing. In order to send a pitch off to its the maximum trajectory, the hitter must square up to the ball with a slight upper-cut. For most hitters this is most easily achieved by hitting a low-inside pitch since they can easily drop their hands and start the upper-cut as they rotate their backside through. By the time the bat rotates through the zone to meet the inside pitch in front of the plate, the barrel of the bat is moving upward in the same plane that the pitch the moving downward (hence why hitting opposite field with power is so difficult because the bat head is usually just getting down or leveling off when the batter makes contact further back in the swing). On the other-hand, the hard high pitch is the most difficult pitch to “get under” because most batters must level off their swings to meet it, resulting in line drives at best. Of course, if the pitch is thrown hard enough (or high enough), and without less downward movement (i.e. a rising fastball), hitters will usually barely make contact underneath at all and hit a fly ball. Thus, the Giants have conceded that they will give up more base-runners in order to prevent more home-runs.

32. Hank says:

Jesse – is the data in a format that you can look at the same tables with home vs road splits for Righetti’s staff? ( to check if there is an issue with the park correction – while it wouldn’t necessary definitive it could at least mostly rule it out as a potential issue if the splits are similar)

• Hank says:

Yikes… that should read “while it wouldn’t necessarily be definitive….”

• DrBGiantsfan says:

I haven’t done it systematically, but the specific pitchers I’ve looked up have a miniscule difference in home vs away splits. I believe this has been looked at more systematically by others and there is a negligable home-away split. Others have made a case for a tiny home-away split to have a bigger impact than it appears on the surface, but I’m not sure I buy it.

33. cs3 says:

Does anyone think that Righetti is actively teaching his pitchers to limit hr/fb rate?
I would think that is pretty unlikely, and would be surprised if he even *knew* that his pitchers have had so much success in this one particular area over the years. Seems so much more likely that something about his general pitching philosophy just happens to have the effect that we are witnessing.

Why hasn’t anyone interviewed the man and see if he even knows about the phenomenon? There have been countless articles on this subject lately and I would think springtraining is the perfect time to get 5 minutes of his time for a few quick questions…

• DrBGiantsfan says:

If Rags is doing something that gives his team a competitive advantage, why would he admit he even knows about it if somebody asked him?

Like I said in my post above, I believe that what Rags is teaching his pitchers is to never, ever give in to the hitters. Suppressing HR/FB is just one byproduct of that philosophy.

34. Telo says:

Truthfully, if any sort of conclusions can be drawn from this AT ALL, we need to see some pitch f/x. The only way a coach could influence this is if his staff is putting pitches in drastically different places.

• DrBGiantsfan says:

Drastically? All you have to do is recall what Cody Ross did to a couple of Halladay pitches that missed where he wanted them to go by less than 2″ to know that Pitch f/x might not be able to pick up on that difference. That’s why fastball command is such an important part of all this and why it’s not all about Righetti. It’s an ORGANIZATIONAL philosophy that starts with pre-draft scouting and getting pitchers who have the ability to carry that philosophy out.

It would be great to look at Pitch f/x, but I don’t think it would come as a huge surprise to either you or me if it showed that Giants pitchers have a strong tendency to work farther up in the strike zone as opposed to, say, Cardinals pitchers.

• Telo says:

If it’s an organizational philosophy, that’s a much more believable reason than “they are coached into not giving up HR.”

What I’m saying is, if you believe that Righetti is actually having an appreciable affect on HR rates, then ostensibly the ONLY way this could be true is if he is coaching his pitchers to pitch in certain ways, ie selection and location. You might want to look at all pitches hit for FB, HRs, and compare that to pitches throw by the Giants, etc. I just don’t believe that he is saying “ok, keep the ball here in this situation, and here in this situation, and you’re good.” and that leads to 2 sigma of homerun prevention.

It’s a combination of luck, a bad model, and outside factors. There is no way it’s the pitching coach. It’s just an absurd premise.

• DrBGiantsfan says:

I think the message Righetti gives is actually very simple. “Always throw YOUR pitch! Don’t give in to the hitters, EVER!” The lower HR rate is just one of several byproducts of that philosophy. HR’s are hit off “mistakes” and when pitcher’s feel forced to throw something they don’t want to throw AKA “giving in” to the hitter. Credit Giants pitchers for throwing fewer “mistake” pitches and credit Rags and the organization for a philosophy of “never give in.”

• Liem says:

I would be curious to see if pitch f/x could at least confirm my observations that the Giants prefer not to draft sinker-ball pitchers or pitchers whose fast-balls generally dive downward. While many teams salivate at slight the chance of developing the next Brandon Webb, the Giants seem to go after the “under-valued” arms that produce flatter movement. Pitch f/x would not have to show end location as much as relative movement of a pitch in order to confirm my hunch.

• DrBGiantsfan says:

Liiem,

The Giants have drafted all kinds of pitchers, but you are almost certainly right about the ones who they have graduated to the major leagues, Cain, Lincecum, Sanchez, Bumgarner, Wilson, even Romo. Interesting that in a small sample size so far, Zack Wheeler has a huge GO/AO in the minors.

If you are looking for the classic fastball command type pitcher the Giants have had success with, keep your eye on Seth Rosin.

“It’s a combination of luck, a bad model, and outside factors. There is no way it’s the pitching coach. It’s just an absurd premise.”

It was never stated that the pitching coach was the *only* factor. Why can’t the influence of the pitching coach be one of the “outside factors” you mention? Or do you believe that a pitching coach has zero effect on his pitchers?

36. Nate says:

Random stat check:

Just looked at the spring training data so far (only on mlb.com and with just AO instead of FB) and computed HR/AO rate and then separated Grapefruit and Cactus leagues.

In GR, average HR/AO was 9.2% and all teams within -1.48 and +1.84 SD with Toronto best and Tampa Bay worst.

In CA, average = 12.3% (FL and AZ definitely different environments) and all teams except one within -1.46 and +1.31 SD.

The lone exception? The SF Giants with a HR/AO rate of 5.5%, at -2.36 SD.