Welcome to HIT f/x

You might have already seen the announcement or come across some of the articles, but HIT f/x data is starting to make an appearance. It is partially available to those of us who attended last year’s PITCH f/x conference in San Francisco. The age of HIT f/x is going to usher in a whole new slew of advancement in evaluation metrics so expect the next year or so to see just as much, and likely more, change in the sabr crowd as the past has seen with the widespread adoption of PITCH f/x.

That being said, the data that we have available to us now does not cover that much time. The sample is only that of April 2009 which presents a small sample size issue. Also giving that we do not have retro data from 2008, it is impossible to do the sort of comparison analysis that I bet many of us are interested in.

Still, it is something and it is neat. So let us work with what we do have instead of dwelling on what we do not yet. Here, then as a quick taste, are the initial speeds off the bat for teams over the month of April.

TEX 85.1
CLE 83.5
TOR 83.4
BAL 82.5
BOS 82.2
MIL 82.2
COL 82.2
ARI 81.8
WAS 81.8
ANA 81.7
LAN 81.7
PHI 81.5
DET 81.2
NYA 80.9
MIN 80.7
SFN 80.7
CHA 80.4
TBA 80.4
KCA 80.2
SLN 80.1
FLO 80.0
CHN 79.8
SDN 79.6
PIT 79.5
OAK 79.4
SEA 79.0
HOU 78.9
ATL 78.4
CIN 77.6
NYN 77.4

As you might suspect, this tracks extremely well with a team’s overall wOBA. National League teams are going to get dragged down a bit because of pitchers hitting, so a straight comparison across leagues is not really fair. Also, I suspect that the spreads between good and bad hitting teams are further exacerbated by the worst hitting teams bunting more often.

That is all for now, but rest assured, much more to come.




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Matthew Carruth is a software engineer who has been fascinated with baseball statistics since age five. When not dissecting baseball, he is watching hockey or playing soccer.

32 Responses to “Welcome to HIT f/x”

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  1. Albert says:

    Very excited for this. Also interested in Ortiz’s initial speed off bat for the month of April compared with everyone else.

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  2. Andy S says:

    Sweet, I’ve been looking forward to this.

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  3. CajoleJuice says:

    Can’t say I’m surprised to see the Mets dead last. They hit like a bunch of women.

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    • Paul Boye says:

      Don;t insult women like that.

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    • metty5 says:

      It is interesting because the Mets are in the top for LD% yet 3rd to last in HR/FB. This probably has a little to do with Citi Field’s Park Factor, Reyes Delgado, and Church being out, and David Wright’s power outage. The players the Mets are starting are pretty awful right now.

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      • PhDBrian says:

        Someone explain to me how David Wright and his 3 home runs and 160 k pace is getting any support from knowledgable fans for the All Star game. Go look at his UZR!

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      • Eric says:

        Because he’s hitting doubles & triples at an increased rate, and he has an almost 350 avg, so his OPS is actually within 40 points or so of career highs

        Projecting going forward, yeah the avg is unsustainable, and his iso being so decreased is worrisome; however, for now he’s been nearly as valuable as he always has been.

        However, I will say that I’m not so confident that the HR numbers are going to rebound… Wright was always a “hit HR’s to right-center” type of player, and it’s VERY deep in Citi Field there; even if his power completely rebounds, it wouldn’t shock me if he winds up trading 10 hr’s for doubles/triples

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  4. Fresh Hops says:

    Fuck yes.

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  5. JLP says:

    “National League teams are going to get dragged down a bit because of pitchers hitting…”

    Which just means the M’s bats are extremely slow, seeing as how the only teams below them are weighed down by pitchers. How exciting to find out that my beloved M’s are last place in yet another offensive category.

    Still pumped to see this come out. Can’t wait to see what else is in the wings.

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  6. CajoleJuice says:

    In all seriousness with regards to the Mets, I’m curious to see if this will shed any light on David Wright’s power outage.

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  7. Will Moller says:

    I’m so excited, I could pee.

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  8. matthew says:

    fastest bat speed = Justin Upton

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  9. joser says:

    Now we need Fielder FX, so that we can look at where they start and where they go relative to the batted ball…

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    • Brendan Scolari says:

      I agree. I think this could be more revealing then Hit FX, because we already have so much offensive data.

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      • BrettJMiller says:

        I think when Hit F/X gets bigger, it will help with fielding statistics. I could be wrong, but I believe the ultimate goal of Hit F/X is to show not only the speed off the bat, but trajectory of balls hit and where they land.

        This would help us finally be able to quantify what a line drive is, instead of it being subjective to the person recording the stats. Also, if we know where balls land and at what speed, we’ll have a better idea of who good fielders are, because we will have a better idea of knowing what balls are harder to get to. Therefore, we’ll be able to say something like “only four CFs get to balls hit about this hard in this area of the field”

        I don’t think I’m explaining this very well, but hopefully you understand what I’m trying to say.

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    • lookatthosetwins says:

      I think one of the most important things to come out of this will be a new fielding metric. It still won’t adjust for where a player is positioned, but we’ll have a lot more data to know what balls would and would not have been fielded by an average fielder.

      The other thing that I am excited for is a better model of expected BABIP for hitters. Most xBABIP models use line drive rates, but not all line drives are created equal. We’ll have more accurate data for who is getting lucky on balls in play.

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    • JBrew says:

      This is quoted from the Pitchf/x summit page:

      “Player Tracking research has already begun. In the future we’ll be able to track all players and the ball throughout an entire game. Player tracking will lead to amazing new insights about defensive strategies, reaction times, fielding range and player speed.”

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  10. Will Moller says:

    Alright. I couldn’t wait for the morning–so if anyone wants to check out the correlations, they’re up at http://theyankeesdollar.blogspot.com/2009/06/as-thunder-crashes-down.html.

    Wildest thing that is shown by this? LD% is essentially unconnected to how hard the teams are hitting the ball. Very unintuitive.

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    • metty5 says:

      A line drive is a trajectory type, not a batted ball speed interval. I’m not sure that is surprising. I’m sure there are tons of flyballs and groundballs that are crushed, its the trajectory that makes them outs.

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    • jtr says:

      It makes sense because speed off the bat is absolute speed, not horizontal speed. Line drives have the greatest horizontal speed, hence the .700+ BA on LDs.

      Also, I suspect that even FB/GB are hit quite squarely, since the ball has a great deal of momentum coming in. Even slight deflection will result in a foul. The ball coming off the bat should have a relatively similar velocity based on bat speed regardless of trajectory.

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  11. Tin says:

    this is awosome,but how can we get these thing game-by-game?

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  12. Slyde says:

    I think you need to remove bunts from the equation perhaps. The Mets, Reds, and Braves lead baseball in bunt attempts, which is why I think they are coming in at the bottom of the list.

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    • Slyde says:

      I just assumed the most bunts would come from the NL, but actually Seattle has more bunt attempts than Atlanta, which explains why they are so far down the list. These data don’t line up exactly because this is for all season and Hit FX is just for April, but I think the trend is fairly clear. Here is the number of bunts for each team so far this season. I’d say there is a pretty good correlation between the two lists:
      BAL – 10
      BOS – 11
      TOR – 18
      OAK – 18
      TEX – 19
      CHW – 21
      KCA – 24
      MIL – 25
      NYA – 27
      TBA – 27
      PHI – 29
      ARI – 31
      CLE – 31
      ANA – 32
      PIT – 34
      LAN – 34
      CHN – 34
      DET – 34
      WAS – 36
      MIN – 41
      SDP – 42
      SFG – 43
      SLN – 44
      COL – 45
      FLA – 45
      ATL – 45
      HOU – 48
      SEA – 52
      CIN – 59
      NYN – 61

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      • Slyde says:

        BTW, I hope you don’t think I’m being critical. I think this new data is very exciting and I’m looking forward to what we can learn from it. I just wanted to point out that I think that your list tells more about who is bunting than anything, I believe.

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    • jtr says:

      I correlated these numbers with April’s team BUH%, R^2 was 0.0004. It seems obvious that BUH% would affect it, but these numbers don’t appear to be tainted by bunting.

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      • Will Moller says:

        JTR,

        BUH% is just % of bunt hits, right? (looked for the definition of that on this site and was unable to find it) Most bunts don’t fall for hits, right? That’s likely to have an odd (and not necessarily strongly related) distribution.

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      • jtr says:

        That brings another question, does HITf/x track hits, or all batted balls? If only hits, then BUH% is perfect. If not, it’s good enough because it’s a given that BUH% and ball-batted-for-a-bunt percentage will correlate highly (near 1).

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  13. Will Moller says:

    Slyde–

    Where did you get the data on how many bunts each team had made?

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    • Slyde says:

      Don’t tell anybody, but I got it at Baseball Reference. :) If you go to a league page, under Batting[+] there is a “PH/HR/Situational Hitting” option. The data I used is there.

      I’m not sure if those numbers are precise as I simply added bunt hits and SH attempts. I’m sure there are things missing like failed bunt hit attempts and ROE on bunt hit attempts, but I figured it was accurate enough for the comparison.

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  14. Will Moller says:

    I heart baseball reference. So much information in one place. Cheers–

    Will

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