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Advanced Stats: Indicators, Realities, Regressions, Anomalies, etc. (1 Viewer)

Long Ball Larry

Long Ball Larry

Footballguy
I thought it might be useful to have a thread for discussion or observations of any interesting statistical trends for players. Here are a couple that I am noticing today:

1. Johnny Cueto's strand rate is 99.5%.

2. Ian Kennedy and Dallas Keuchel are 8th and 11th in SIERA with pretty much league-average BABIP and strand rates. They are not big strikeout guys and are not on great teams for wins, but they could be nice low-risk pitchers to fill out a staff.

I know that Kennedy is pitching much better than his career averages, but he is inducing a lot more groundballs and obviously is pitching in a great park. With the DBacks, his SIERA's were always under 4.

 
I don't understand that Cueto stat. He has allowed 3 ERs besides HRs and allowed 40 baserunners besides HRs. I could see a few more guys on from errors but that still doesn't put it close. What am I missing about the calculation

Eta: nm i see they use a multiplier for HRs. That's odd, was thinking it was a strand rate.

 
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Nick Castellanos has a 32.9% LD rate and a .272 BABIP. Everyone else with a LD% >27 has a BABIP of at least .324.

On the other hand Yasiel Puig somehow has a LD% of 11.9% but a BABIP of .372. Of course I have no idea how to figure him out.

 
cheese said:
I don't understand that Cueto stat. He has allowed 3 ERs besides HRs and allowed 40 baserunners besides HRs. I could see a few more guys on from errors but that still doesn't put it close. What am I missing about the calculation

Eta: nm i see they use a multiplier for HRs. That's odd, was thinking it was a strand rate.
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Is LOB% not the same as strand rate?

 
I've never actually looked at it, so here is the LOB % formula, for anyone interested: LOB% = (H+BB+HBP-R)/(H+BB+HBP-(1.4*HR))

cueto's BABIP is just .160, also.

 
jfranco77 said:
Nick Castellanos has a 32.9% LD rate and a .272 BABIP. Everyone else with a LD% >27 has a BABIP of at least .324.

On the other hand Yasiel Puig somehow has a LD% of 11.9% but a BABIP of .372. Of course I have no idea how to figure him out.
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A lot of sabr people have stopped looking at LD% because of how arbitrary it can be based on who is recording the stat. Some record a flair to the outfield as a line drive. Others record a high line drive to the deep outfield as a fly ball.

 
Fly said:
jfranco77 said:
Nick Castellanos has a 32.9% LD rate and a .272 BABIP. Everyone else with a LD% >27 has a BABIP of at least .324.

On the other hand Yasiel Puig somehow has a LD% of 11.9% but a BABIP of .372. Of course I have no idea how to figure him out.
Click to expand...
A lot of sabr people have stopped looking at LD% because of how arbitrary it can be based on who is recording the stat. Some record a flair to the outfield as a line drive. Others record a high line drive to the deep outfield as a fly ball.
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interesting.

I'm hearing more about batted ball distance and well-hit average now. I haven't looked into it that closely. Any thoughts on that as a better indicator?

 
Kennedy's xFIP and xERA are both great, and Kuechal's are good. You could make an argument that both are actually underperforming to their advanced metrics.

On Castellanos, LD rate depends on the hitter. He hits everything hard so in his case the correlation with BABIP deserves a look. He's got good pitch recognition and is doing things like creating fly balls with runners in scoring position. I think he will be streaky this year and maybe next, but he's got 25 homers and a high average written all over him.

I mentioned Kenley Jansen's .452 BABIP yesterday, that makes no sense. Adam Jones' BABIP is at a career average but his ISO is way down, some room for concern there. Billy Butler's BABIP is a bit low but he's hitting 58% ground balls this year and has an ISO of .68. As summer approaches those ISO numbers will get better, but how much? Jones we can assume will rebound, Butler I'm not so sure. Adam Lind's BABIP is .371, Adrian Gonzalez' is .270. One is going one way, one is going the other as the season unfolds.

I don't love advanced stats for pitching as much as I do for hitting, and they are nearly useless for fielding IMO. With pitching I think there is too much variation over X number of starts while hitting is more gradual. I like DOM XFIP for pitching most, ISO and wOBA for hitters.

 
Long Ball Larry said:
Fly said:
jfranco77 said:
Nick Castellanos has a 32.9% LD rate and a .272 BABIP. Everyone else with a LD% >27 has a BABIP of at least .324.

On the other hand Yasiel Puig somehow has a LD% of 11.9% but a BABIP of .372. Of course I have no idea how to figure him out.
Click to expand...
A lot of sabr people have stopped looking at LD% because of how arbitrary it can be based on who is recording the stat. Some record a flair to the outfield as a line drive. Others record a high line drive to the deep outfield as a fly ball.
Click to expand...
interesting.

I'm hearing more about batted ball distance and well-hit average now. I haven't looked into it that closely. Any thoughts on that as a better indicator?
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Batted ball distance is being used a lot more now. There's some concern about David Wright in that regard. Well-hit average seems a bit arbitrary. I know it's measured by a private scouting firm called Inside Edge; and they measure it by reviewing video of each hit ball and categorizing it into 3 categories: well-hit, medium-hit, not-well-hit. What's the difference between a medium hit ball and a well hit ball? I couldn't tell you.

 
Gerrit Cole was just dropped in my league for some reason. (We do have short benches and only start 3 SP, but still).

Looking at his numbers, everything is pretty much the same as last year except for HR/FB, which is 14.6%. That would have been the highest rate in the league last season.

His walk rate is up a little bit from last year, though consistent with what he did minors.

Once the HR/FB normalizes, he should be in very good shape.

 
Long Ball Larry said:
cheese said:
I don't understand that Cueto stat. He has allowed 3 ERs besides HRs and allowed 40 baserunners besides HRs. I could see a few more guys on from errors but that still doesn't put it close. What am I missing about the calculation

Eta: nm i see they use a multiplier for HRs. That's odd, was thinking it was a strand rate.
Click to expand...
Is LOB% not the same as strand rate?
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At least in the logical sense it isn't the same. Strand rate of 99.5% would imply to me that he has left 199 out of 200 runners on base. Cueto has allowed 3 baserunners to score and nobody has put anywhere near 200 runners on base, much less the guy dominating more than anyone.

 
Long Ball Larry said:
Fly said:
jfranco77 said:
Nick Castellanos has a 32.9% LD rate and a .272 BABIP. Everyone else with a LD% >27 has a BABIP of at least .324.

On the other hand Yasiel Puig somehow has a LD% of 11.9% but a BABIP of .372. Of course I have no idea how to figure him out.
Click to expand...
A lot of sabr people have stopped looking at LD% because of how arbitrary it can be based on who is recording the stat. Some record a flair to the outfield as a line drive. Others record a high line drive to the deep outfield as a fly ball.
Click to expand...
interesting.

I'm hearing more about batted ball distance and well-hit average now. I haven't looked into it that closely. Any thoughts on that as a better indicator?
Click to expand...
It seems that a given average fly ball distance (say 280 feet) has a corresponding "natural" HR/FB% (say 13%). So if a guy is mid-pack in fly ball distance but has a ton of HRs, he either plays in Yankee Stadium or is due some regression.

Haven't read much about this but I am intrigued.

http://www.fangraphs.com/fantasy/seven-hrfb-rate-decliners/

 
jfranco77 said:
Long Ball Larry said:
Fly said:
jfranco77 said:
Nick Castellanos has a 32.9% LD rate and a .272 BABIP. Everyone else with a LD% >27 has a BABIP of at least .324.

On the other hand Yasiel Puig somehow has a LD% of 11.9% but a BABIP of .372. Of course I have no idea how to figure him out.
Click to expand...
A lot of sabr people have stopped looking at LD% because of how arbitrary it can be based on who is recording the stat. Some record a flair to the outfield as a line drive. Others record a high line drive to the deep outfield as a fly ball.
Click to expand...
interesting.

I'm hearing more about batted ball distance and well-hit average now. I haven't looked into it that closely. Any thoughts on that as a better indicator?
Click to expand...
It seems that a given average fly ball distance (say 280 feet) has a corresponding "natural" HR/FB% (say 13%). So if a guy is mid-pack in fly ball distance but has a ton of HRs, he either plays in Yankee Stadium or is due some regression.

Haven't read much about this but I am intrigued.

http://www.fangraphs.com/fantasy/seven-hrfb-rate-decliners/
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yeah, podhorzer was on this podcast yesterday and talked about BBD quite a bit: http://baseballprof.baseballprofesso1.netdna-cdn.com/wp-content/uploads/Profcasts/2014/Episode53_20140513.mp3

 
Long Ball Larry said:
Gerrit Cole was just dropped in my league for some reason. (We do have short benches and only start 3 SP, but still).

Looking at his numbers, everything is pretty much the same as last year except for HR/FB, which is 14.6%. That would have been the highest rate in the league last season.

His walk rate is up a little bit from last year, though consistent with what he did minors.

Once the HR/FB normalizes, he should be in very good shape.
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Yeah, I'd be all over picking him up.
 
Doctor Detroit said:
I don't love advanced stats for pitching as much as I do for hitting, and they are nearly useless for fielding IMO.
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I heard the creator of Pitch f/x Cory Schwartz saying that they are developing a new system that will finally be able to capture sabermetrics fielding accurately. He said fielding is the "holy grail" of sabermetrics and the new system will change player valuations in real life. He said anytime between late summer and next spring for release, should be awesome.

ETA: Cory not Allan

 
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Fly said:
Devin Mesoraco has a .543 BABIP through 57 PAs. It will more than likely regress a bit.
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well, yes, but his babip is being fueled by a lot of really hard hit balls and extra base hits. The breakout is legit. Now just keep that hammy intact.
 
Doctor Detroit said:
I don't love advanced stats for pitching as much as I do for hitting, and they are nearly useless for fielding IMO. With pitching I think there is too much variation over X number of starts while hitting is more gradual. I like DOM XFIP for pitching most, ISO and wOBA for hitters.
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So how do you evaluate a hitter and determine who is underperforming or overperforming? Obviously a high or low BABIP can be a place to look, but what about other metrics?

I feel like with pitching, I can get a good feel for what a guy is actually doing by looking at SIERA and xFIP, then checking out BABIP, HR/FB and GB%, then looking at K% and walk rates. These things tell me if a guy is pitching well, but getting unlucky, or vice versa.

But for hitters I don't feel as confident, for some reason. Which are the best stats to suggest what a hitter "should be" doing? If a hitter is suddenly hitting a lot more groundballs and/or striking out a lot more (like a Martin Prado for the first 6 weeks), how do we determine whether there has been an actual change in the hitter (aging, injury, etc.) or if it is more luck-based? Just compare to prior years for the same hitter? But certainly at some point, hitters do get worse, right?

Maybe I am just biased to believe more in the pitchers than the hitters, because the pitchers have more control over what they can do.

 
Long Ball Larry said:
Doctor Detroit said:
I don't love advanced stats for pitching as much as I do for hitting, and they are nearly useless for fielding IMO. With pitching I think there is too much variation over X number of starts while hitting is more gradual. I like DOM XFIP for pitching most, ISO and wOBA for hitters.
Click to expand...
So how do you evaluate a hitter and determine who is underperforming or overperforming? Obviously a high or low BABIP can be a place to look, but what about other metrics?

I feel like with pitching, I can get a good feel for what a guy is actually doing by looking at SIERA and xFIP, then checking out BABIP, HR/FB and GB%, then looking at K% and walk rates. These things tell me if a guy is pitching well, but getting unlucky, or vice versa.

But for hitters I don't feel as confident, for some reason. Which are the best stats to suggest what a hitter "should be" doing? If a hitter is suddenly hitting a lot more groundballs and/or striking out a lot more (like a Martin Prado for the first 6 weeks), how do we determine whether there has been an actual change in the hitter (aging, injury, etc.) or if it is more luck-based? Just compare to prior years for the same hitter? But certainly at some point, hitters do get worse, right?

Maybe I am just biased to believe more in the pitchers than the hitters, because the pitchers have more control over what they can do.
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I do agree that it's simpler to piece together a picture of an effective pitcher than a hitter (if that's what you are saying).

If a pitcher is striking people out, not walking people, and inducing groudballs (or weak flyballs), they are probably a good pitcher and good things will eventually happen (with the occasional anomaly, like Nolasco for a some of those years).

I think it's probably different for a hitter because there's so much variation in what a productive hitter looks like. All pitchers have essentially the same "job", while batters are very different.

Does anybody know where to get basic batted ball distance data for hitters?

I see fangraphs has that data that they use in some of their columns, but the data itself isn't on their site that I can see.

I also see some writers mentioning "well hit/medium hit/weakly hit" data that they have access too. That data would be nice to access too.

 
pollardsvision said:
Long Ball Larry said:
Doctor Detroit said:
I don't love advanced stats for pitching as much as I do for hitting, and they are nearly useless for fielding IMO. With pitching I think there is too much variation over X number of starts while hitting is more gradual. I like DOM XFIP for pitching most, ISO and wOBA for hitters.
Click to expand...
So how do you evaluate a hitter and determine who is underperforming or overperforming? Obviously a high or low BABIP can be a place to look, but what about other metrics?

I feel like with pitching, I can get a good feel for what a guy is actually doing by looking at SIERA and xFIP, then checking out BABIP, HR/FB and GB%, then looking at K% and walk rates. These things tell me if a guy is pitching well, but getting unlucky, or vice versa.

But for hitters I don't feel as confident, for some reason. Which are the best stats to suggest what a hitter "should be" doing? If a hitter is suddenly hitting a lot more groundballs and/or striking out a lot more (like a Martin Prado for the first 6 weeks), how do we determine whether there has been an actual change in the hitter (aging, injury, etc.) or if it is more luck-based? Just compare to prior years for the same hitter? But certainly at some point, hitters do get worse, right?

Maybe I am just biased to believe more in the pitchers than the hitters, because the pitchers have more control over what they can do.
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I do agree that it's simpler to piece together a picture of an effective pitcher than a hitter (if that's what you are saying).

Does anybody know where to get basic batted ball distance data for
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Yes to number 1.

basballheatmaps: http://www.baseballheatmaps.com/graph/distanceleader.php

 
I guess that what I am trying to figure out is the best starting point for hitters. Something like Runs Created or OPS adjusted for park factors and/or fielding and/or the lineup around a player. then I would start with that and drill down to other anomalies like HR/FB %, GB%, etc.

 
I usually start with ld% and k/bb. If a player does both of those well he is usually a good hitter. I expect a player with a low ld% and a high fb% to have a poor babip.

 
Fly said:
Long Ball Larry said:
I guess that what I am trying to figure out is the best starting point for hitters. Something like Runs Created or OPS adjusted for park factors and/or fielding and/or the lineup around a player. then I would start with that and drill down to other anomalies like HR/FB %, GB%, etc.
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wRC+

http://www.fangraphs.com/library/offense/wrc/
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But that's a cumulative stat, I think what LBL is looking for are more nitty-gritty things.

I look at K% and BB% first, then LD/GB/FB. I used to be pretty ambivalent towards non-LD%, but I'm following suit with my Athletics and putting more stock in the flyball. You can really only do so much damage with a ball hit on the ground. Look at how Francisco's turned his production around by getting more balls in the air this year (something that Toronto seems to stress).

I also like to look at plate discipline numbers, particularly O-Swing and SwStrk.

 
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Celph Titled said:
Fly said:
Long Ball Larry said:
I guess that what I am trying to figure out is the best starting point for hitters. Something like Runs Created or OPS adjusted for park factors and/or fielding and/or the lineup around a player. then I would start with that and drill down to other anomalies like HR/FB %, GB%, etc.
Click to expand...
wRC+

http://www.fangraphs.com/library/offense/wrc/
Click to expand...
But that's a cumulative stat, I think what LBL is looking for are more nitty-gritty things.

I look at K% and BB% first, then LD/GB/FB. I used to be pretty ambivalent towards non-LD%, but I'm following suit with my Athletics and putting more stock in the flyball. You can really only do so much damage with a ball hit on the ground. Look at how Francisco's turned his production around by getting more balls in the air this year (something that Toronto seems to stress).

I also like to look at plate discipline numbers, particularly O-Swing and SwStrk.
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It sounded like he was looking for a starting point. I would sort by wRC+ and look for names that might seem a little out of place. Puig, Cruz, Moss, and Seth Smith are 2nd, 3rd, 6th, and 7th respectively which seems pretty interesting (to me at least). If I want to know why I'm going to probably look at the following:

1. BB% and K%

Pitch recognition and plate discipline is where it all starts. If there are any differences from career norms in BB% or K% I go to plate discipline. Puig's O-Swing is down 11%, Z-Contact is up 6%, SwStrk is down %6. We're far enough along in the season for me to believe that Puig's discipline has improved and that his success is real and sustainable.

2. HR/FB%

Nelson Cruz' HR/FB% for his career is 17.5%. He's had three seasons where he's eclipsed 21%. His 2014 HR/FB% is 28.4%. That's high. I'm not sold it's sustainable yet. I want to see what kind of HRs he has hit. Hit Tracker shows that 5 of his HRs would have been home runs 16 or less ballparks and 2 more would have been home runs in 18 ballparks. Most of his HRs are legit, not many are cheap. I'd say this is a legit breakout year due for some regression towards the 21% HR/FB. If we regress to that 21% we would expect him to hit about 25 HRs ROS. He has a legitimate shot at 45 HRs this year. (I should note that his BB% and K% falls in line with his career rates).

3. GB/FB

Since coming over to Oakland, Brandon Moss has completely redefined himself as a hitter. He hit a lot of ground balls pre-Oakland and now hits many a fly ball (50% this year, 52% last year). The amount of fly balls he hits coupled with a HR/FB% around 20% means Moss is going to continue hitting home runs. Conversely, guys like Allen Craig and Billy Butler (who have struggled 2014) have seen a huge increase in ground balls.

4. BABIP

I think BABIP for hitters can actually be a sustainable skill (just take a look at Ichiro's season-by-season numbers). But a batter has to prove this for multiple seasons. Seth Smith's BABIP in 2014 is .343. His career rate is .307. We know something is going on that isn't quite normal. (His BB% and K% are improved also). How is his IFFB%? Seth Smith has hit zero infield fly balls this year. His career rate is 6%. In other words he's no Joey Votto. I also like to data mine when I'm looking at BABIP. Especially when it comes to splits. L and R splits can explain a lot for vets (if I remember correctly it takes about 1000 PA for platoon data to stabilize). I'm not going to type out every piece of data here, but let's just say there is a HUGE difference in Seth Smith vs. L than Seth Smith vs. R. And if you look at his 2014 splits you'll notice that he only has 21 PAs against LHP. Hitting against RHP and not hitting infield fly balls is how I'm breaking down Smith's success.

That's more or less my (admittedly crude) method. You can do the same thing on the other end of the spectrum with to figure out why certain hitters are struggling. I think it's enough to get a pretty well rounded idea of what a hitter is doing for the current year and if it's sustainable or not.

 
Fly said:
It sounded like he was looking for a starting point. I would sort by wRC+ and look for names that might seem a little out of place. Puig, Cruz, Moss, and Seth Smith are 2nd, 3rd, 6th, and 7th respectively which seems pretty interesting (to me at least). If I want to know why I'm going to probably look at the following:
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you're both right.

I am definitely trying to figure out a good starting point and the above is definitely what I want to do. Then the next step is to figure out the whys of what is going on and whether there is really something to take note of.

Thanks to all for the replies. I know that there is no "one answer", but these are all good thoughts.

 
When looking at BABIP for hitters, I think their LD/GB/FB splits are Jimmy Key to separating signal from the noise. Jose Bautista has a chronically low LD% given his uppercut, which is why his BABIP numbers are always fairly low.

Being fast also helps.

 
Celph Titled said:
When looking at BABIP for hitters, I think their LD/GB/FB splits are Jimmy Key to separating signal from the noise. Jose Bautista has a chronically low LD% given his uppercut, which is why his BABIP numbers are always fairly low.

Being fast also helps.
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Yeah, one thing I heard mentioned the other day was that the LD/GB/FB split should be roughly 20/45/35. Any lower than that on LD and higher on GB is probably not a good sign.

I guess that is useful for guys who do not have as much of a major league track record in terms of deciding who to be patient with, who to try to jump on before a breakout, or who to ignore even if the standard stats look good.

 
You look at Castellanos who has a 31.3% LD rate this year. We have virtually nothing to compare to for his LD rates prior to this year.

So it seems like he would be a guy to buy, since his FB rate is 36.3%.

But his BABIP is not great for the LD rate, he still only has 5 HR and his HR/FB is just 9.4%. And he's in the middle of the pack in batted ball distance.

So is he a buy or no-buy?

 
Doctor Detroit said:
Kennedy's xFIP and xERA are both great, and Kuechal's are good. You could make an argument that both are actually underperforming to their advanced metrics.

On Castellanos, LD rate depends on the hitter. He hits everything hard so in his case the correlation with BABIP deserves a look. He's got good pitch recognition and is doing things like creating fly balls with runners in scoring position. I think he will be streaky this year and maybe next, but he's got 25 homers and a high average written all over him.

I mentioned Kenley Jansen's .452 BABIP yesterday, that makes no sense. Adam Jones' BABIP is at a career average but his ISO is way down, some room for concern there. Billy Butler's BABIP is a bit low but he's hitting 58% ground balls this year and has an ISO of .68. As summer approaches those ISO numbers will get better, but how much? Jones we can assume will rebound, Butler I'm not so sure. Adam Lind's BABIP is .371, Adrian Gonzalez' is .270. One is going one way, one is going the other as the season unfolds.

I don't love advanced stats for pitching as much as I do for hitting, and they are nearly useless for fielding IMO. With pitching I think there is too much variation over X number of starts while hitting is more gradual. I like DOM XFIP for pitching most, ISO and wOBA for hitters.
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Doctor Detroit said:
Kennedy's xFIP and xERA are both great, and Kuechal's are good. You could make an argument that both are actually underperforming to their advanced metrics.

On Castellanos, LD rate depends on the hitter. He hits everything hard so in his case the correlation with BABIP deserves a look. He's got good pitch recognition and is doing things like creating fly balls with runners in scoring position. I think he will be streaky this year and maybe next, but he's got 25 homers and a high average written all over him.

I mentioned Kenley Jansen's .452 BABIP yesterday, that makes no sense. Adam Jones' BABIP is at a career average but his ISO is way down, some room for concern there. Billy Butler's BABIP is a bit low but he's hitting 58% ground balls this year and has an ISO of .68. As summer approaches those ISO numbers will get better, but how much? Jones we can assume will rebound, Butler I'm not so sure. Adam Lind's BABIP is .371, Adrian Gonzalez' is .270. One is going one way, one is going the other as the season unfolds.

I don't love advanced stats for pitching as much as I do for hitting, and they are nearly useless for fielding IMO. With pitching I think there is too much variation over X number of starts while hitting is more gradual. I like DOM XFIP for pitching most, ISO and wOBA for hitters.
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Having watched almost every Tiger game this year I am amazed at how many hard hit/line drives that Castellanos has hit directly at the OF. Could easily have 12-15 more hits and most would be extra base hits.

 
Long Ball Larry said:
cheese said:
I don't understand that Cueto stat. He has allowed 3 ERs besides HRs and allowed 40 baserunners besides HRs. I could see a few more guys on from errors but that still doesn't put it close. What am I missing about the calculation

Eta: nm i see they use a multiplier for HRs. That's odd, was thinking it was a strand rate.
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Is LOB% not the same as strand rate?
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Cueto LOB % up to 80% (which is still top 10) and BABIP up to .212, which is obviously still low, but he is still 6th in SIERA, so maybe this more or less real.

 
All the numbers say that Brandon McCarthy should be good. He's just got this problem where every flyball he gives up is a home run.

It's crazy to have and xFIP and SIERA that good and still be this bad.

His HR/FB rate is higher than Marco Estrada! And he's given up like 900 homers.

 
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Long Ball Larry said:
Celph Titled said:
Minor league batted ball numbers: http://minorleaguecentral.com/player?pid=592206

I don't want anything to do with Castellanos at present. The LD numbers are nice, but the K/BB is still pretty bad, and he's not hitting for a ton of power or stealing bases.
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that's awesome.

good point about the k/bb rate. I forgot that I did see that yesterday.
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No it's not, he's 22 years old in his rookie season. His k/BB rate is similar to Carlos Gomez, Jose Abreu and Xander Boegarts, guess those guys are avoid too right?

And who expected him to steal a bunch of bases? He's a gap power hitter with great line drive capability, 20-25 homers with an upside of probably 30. He translates into a .280 hitter with a lot of runs created, how those come is dependent upon a number of variables. He is not that expensive in redrafts and likely to keep progressing. He's not Ryan Zimmerman yet, but that's what he's going to be. :2cents:

 
This is an article from last year regarding the possible legitimacy of streakiness.

http://www.gsb.stanford.edu/insights/jeffrey-zwiebel-why-hot-hand-may-be-real-after-all

Excerpts

The hot-hand "fallacy" has its own roots at Stanford. Thomas Gilovich, a graduate student in the early 1980s, began comparing the widespread perception of hot streaks in basketball to the hard data. Gilovich, now at Cornell, led a study showing that the hot hand didn't really exist: The shooting records of the Philadelphia 76ers provided no predictive value of subsequent shots. A player might be hot one minute, but not the next. Fans and even sports professionals, they concluded, were making decisions based on myopic impressions.

Zwiebel and Green argue that the original finding failed to account for a key issue. In basketball, the opposing team quickly adjusts to a "hot" player, devoting extra coverage and forcing that player to attempt more difficult shots. As a result, it's inevitable that a hot player's shooting percentage will decline. It's not because the hot streak was an illusion, but rather that the hot player attracted more opposition.

Baseball is different, because pitchers and coaches have very limited ability to re-deploy resources against a hitter on a hot streak. Pitchers and coaches do play to a hitter's particular weaknesses, but they can't put more people in the hitter's way.

To test their ideas, Zwiebel and Green amassed data on 2 million Major League Baseball at-bats over 12 years. They looked at 10 categories of performance, from batting averages and home-run percentages to strike-out rates. For pitchers, they looked at data such as the average number of hits allowed. They also controlled for the fundamental ability of both pitchers and hitters, in order to isolate the actual "streakiness" of a player's performance.

The result: A player's most recent 25 times at bat was a significant predictor of how that player would do at his next time up — good enough to justify an adaptive reaction by coaches. When a player is "hot," the researchers calculated, his expected on-base percentage will be 25 to 30 points higher than it would be if he just has been "cold." Similarly, a player on a hot streak will be 30% more likely to hit a home run than if he has been on a cold streak.

As it happens, a team of Harvard researchers reached a similar conclusion in a newstudy of basketball. The Harvard team looked at data on 83,000 shots made during the National Basketball Association's 2012-2013 season. But instead of looking simply at completion rates, the researchers built a model for gauging the difficulty of shots. They found that players who had exceeded their expectations in recent shots were likely to face tighter opposition and take more difficult shots. Adjusting for the increased difficulty of the shots, the researchers found that hot players were likely to continue outperforming. The "hot-hand effect," they estimated, raised their chances of making a shot by 1.2% to 2.4%.
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Doctor Detroit said:
I heard the creator of Pitch f/x Cory Schwartz saying that they are developing a new system that will finally be able to capture sabermetrics fielding accurately. He said fielding is the "holy grail" of sabermetrics and the new system will change player valuations in real life. He said anytime between late summer and next spring for release, should be awesome.

ETA: Cory not Allan
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How does he get paid for that?  Teams subscribe?

 
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