Comments on: More Velocity and K/9 Charting

By: Schedule

Schedule — Sat, 30 Oct 2010 10:09:20 +0000

You you should make changes to the page subject More Velocity and K/9 Charting | FanGraphs Baseball to more suited for your subject you make. I loved the post withal.

By: fili

fili — Wed, 18 Feb 2009 09:05:18 +0000

Just noticed that both the X and Y scales for both graphs are inconsistent. That’s bad presentation form :0)

By: fili

fili — Wed, 18 Feb 2009 09:03:39 +0000

I would like to see the slope presented. I’m not sure they are that similar. The trendline for starters starts above 4 and ends up below 8. The trendline for relievers starts below 4 and ends up well above 8, maybe above 9.

Also, noted the cloud distribution with the relievers, breaking them down farther would be helpful. There are some pretty extreme outliers there (11Ks/85MPH for example)

Agreed that K/BF would be more helpful

By: Piecemeal Pete

Piecemeal Pete — Wed, 18 Feb 2009 04:45:44 +0000

Terminator is right. K/BF would be a better stat to use instead of K/9.

By: Terminator X

Terminator X — Wed, 18 Feb 2009 02:16:52 +0000

Oh you’re absolutely right that the difference is likely small and this is all close enough for jazz, but my point is merely if we have what is potentially more accurate data readily available, why not use that instead? It seems like Contact% could be a great option to replace K/9

By: alskor

alskor — Wed, 18 Feb 2009 01:57:00 +0000

Given that the average LHP throws softer than the average RHP… wouldnt a split of these graphs by handedness be worth looking at?

The strange issue of LHP velocity sorts of skews things – though I dont expect any bias, and I do expect a similar slope…

By: don

don — Wed, 18 Feb 2009 01:53:21 +0000

First, I want to say the feedback on this site is great. The starters do appear to be somewhat of a tighter bunch with a few less outliers, though obviously velocity is not the only answer.

Terminator – this is going to be a really rough back of the envelope type calculation which someone can fix later, but the difference between the best defense and the worst defense last year was less than 150 runs over the course of the season. If the difference between the average non home run base hit and an out is something like three quarters of a run, that’s 200 extra outs over the course of a season, compared to 4300 normal outs, give or take. 200 outs is probably a high estimate, and that’s a bigger spread than between the worst and the best fielding units in baseball last year. It still leaves the fielding affect at less than 5%. There’s some park effect too from size of foul grounds whatnot, but my guess would be K/9 is still pretty good. It would be a concern if there were any teams with as big of a fielding difference as your teams A and B, but I don’t think it’s the case.

By: Terminator X

Terminator X — Wed, 18 Feb 2009 00:42:53 +0000

Also, I can’t help but wonder if using something like K% or even Contact% would be a better measure of the effectiveness you’re looking for here. I’ve never liked K/9 because I feel it can be influenced too much by the defense – to use an unrealistic but mathematically simple example:
Pitcher A and B play for different teams (Team A and B, respectively), and both strike out every other batter that comes to the plate
Team A’s defense converts every other ball in play into an out.
Team B’s defense converts every third ball in play into an out

So a 9-inning game for Pitcher A would look like this: (K=strikeout, H=hit, F=fielding put out)
KHKF/KHKF/KHKF/KHKF/KHKF/KHKF/KHKF/KHKF/KHKF (split up into innings)
Getting 18 of his 27 outs from K’s, or a K/9 of 18
Same excercise for Pitcher B:
KHKHK/FKHK/HKFK/HKHKF/KHKHK/FKHK/HKFK/HKHKF/KHKHK
Getting 21 of his 27 outs from K’s, or a K/9 of 21
Despite pitching identical fielding-independent games, the inferior defense of Team B artificially inflates Pitcher B’s K/9, as they supply him with fewer putouts, allowing for him to accumulate more K’s relative to total outs.

By: Terminator X

Terminator X — Wed, 18 Feb 2009 00:23:13 +0000

I agree with Jeff that there is much more of a cloud-effect going on with relievers and it is nowhere near as linear as the graph for starters. For starters, nearly all of them are within 3 K/9 of the expected line, while for relievers there is much more variance as many of them are as far 4 and 5 K/9 away from the expected line. This could be due to a small sample size, which could be addressed by using multiple years worth of data until you reached the 100 IP that the starters have. As has already been pointed out in the other post, situational use likely boosts the RP’s K/9 when compared to the SP’s K/9, but that doesn’t really explain the great amount of pitchers that fall significantly under the line. Those pitchers might be explained as mopup guys and generally poor pitchers who just aren’t good enough to make the rotation, which is why the extreme “underperformers” show up in the RP graph and not the SP graph.

By: fanOFdefenseAGAIN

fanOFdefenseAGAIN — Tue, 17 Feb 2009 23:12:27 +0000

To start off my virginal post here, I’d first like to thank you guys for your great work. This site is a goldmine.

In response to Matt, I agree with your point that starters probably have a higher expected k/9 at every mph, but I would tentatively argue that the the spread is greater than .5(k/9)/mph. Dave is treating relief and starting Ks equally. However, data may show that it is easier to accumulate high K/9 stats as a reliever. I would have to defer to studies for actual evidence but my uninformed prediction would be based on factors, such as seeing a lineup fewer times in a single game, changing leagues more often (as a relief pitcher), electing not to conserve pitchers to elongate your start, etc.

If it does not already exist, I would be interested to see a study that tracked k/9 differentials among pitchers who were converted from starters to relievers. I can imagine some difficulties with such a study though…