New Stat: Hit Game Rate (HGR)

One of my favorite things to do is come up with stats that look at different things. I have my Runs Created stat that basically considers how many runs you were a part of during a particular season (Runs + RBI – HR). Tonight, I shall go over the Hit Game Rate and see how the current Cardinals team stacks up.

Now what is a Hit Game Rate, you might be asking? Very simply put, a Hit Game is a game in which you get a hit. Hit Game Rate, is how often you get a hit in any given ballgame. This isn’t like batting average where it measures how many hits you get. It simply counts how often you have a ballgame in which you get a hit, whether it be one hit or five hits.

The basic idea of the stat is to gauge whether a person is being consistent or whether their batting average might be inflated by one or two really hot games. After all, Player A who goes 1-for-4 for four nights will have a .250 batting average, but Player B who goes 0-for-4 for three games and then 4-for-4 the last will also have that .250 batting average. Each is a very different player and perceptions of the player will be different.

While the 4-for-4 performance will stick in the mind and bring conclusions of “flashes of brilliance” from fans, would you really rather a guy who will go off every fourth night? Okay, perhaps I’d prefer him if he did it like clockwork, but that’s not likely to happen.

If we go back to our previous example, Player A would have four Hit Games in four games, giving him a 1.000 Hit Game Rate, or HGR. Meanwhile Player B would have just one Hit Game in four games, giving him a .250 HGR.

Think about it this way, if Batting Average is the statistic that tells you how often a player has hit per at bat, HGR tells you how often that player has a hit per game. Each should be fairly important factors when judging the player.

And we all¬†subconsciously¬†track HGR. Player A above will be viewed as a player who is “hitting” while Player B will be a guy who is viewed as “struggling.”

Hopefully the above paragraphs made sense and you have an idea what I’m trying to talk about. So let’s go through and check out the Cardinals’ players and see where they stack up by HGR.

  1. Lance Berkman (1.000, 9/9)
  2. Allen Craig (.833, 10/12)
  3. Jon Jay (.815, 22/27)
  4. Rafael Furcal (.735, 25/34)
  5. Yadier Molina (.727, 24/33)
  6. Matt Holliday (.694, 25/36)
  7. David Freese (.618, 21/34)
  8. Skip Schumaker (.611, 11/18)
  9. Carlos Beltran (.583, 21/36)
  10. Matt Carpenter (.500, 16/32)
  11. Daniel Descalso (.464, 13/28)
  12. Tyler Greene (.440, 11/25)
  13. Tony Cruz (.400, 4/10)
  14. Shane Robinson (.375, 9/24)
  15. Erik Komatsu (.286, 4/14)

Interesting to take note at the two bottom names on that list. Those are the two guys who have been moved off the 25 man roster. Komatsu being waived with the return of Allen Craig to head to Minnesota, and then Shane Robinson being optioned to Memphis when Lance Berkman returned.

It’s also interesting to me to see Carlos Beltran is only 9th on the list and a guy like Matt Holliday is up in 6th. Beltran, of course, is hitting .295 and he has 13 home runs to lead the team and the league. Meanwhile Matt Holliday is hitting just .269, still down from his normal career numbers but up from up from where he was a month ago.

The top two spots are held by Berkman and Craig, which is to be expected to a point, they have a smaller sample size. Both have been pretty hot. Berkman has gotten a hit in all 9 games he’s played this season, the 7 before the DL trip and the 2 afterwards. Meanwhile Craig has hit in all but 2 games this season.

Having Jay and Furcal basically leading the larger sample sized players isn’t that big of a surprise. The two of them have had crazy high batting averages and ultimately a fairly high batting average will correlate with a high HGR, as will a fairly low batting average with a low HGR, but comparing two guys with similar batting averages it will tell you who hits more often.

I think I’ll have to revisit this as the sample sizes grow larger and see how they correlate with the general fan sentiment towards a player.

It’s maybe not in-depth and I’m probably not up for any award for contributions to baseball, but it’s one of my fun little stats that I like to compute to help me determine a player’s performance value.