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Ohio State Statistical Breakdown

I’ve been a bit out of the loop heavily lately. I apologize. Today we started Spring Quarter at Ohio State, with three classes back-to-back-to-back from 9:30 AM to 3:30 PM, on top of being under the weather, things have been a bit of a struggle.

Instead of being smart and taking a few days to rest and stay clear of all baseball thoughts, I’ve been busy keeping the engine churning. Though the Weekend Wrap will be delayed, I do have something of value.

Given the struggles the Buckeyes have had of late, back-and-forth banter with a BSB contributor has spawned a pretty impressive feature in which I highly recommend all to read. Going behind the numbers and digging deeper than anyone ever has, we present to you an Ohio State Statistical Breakdown of what has been a roller coaster 2010 season brought to you by formerlyanonymous.

Hi, I’m formerlyanonymous. I generally keep to the back of the blog, just tweaking HTML tables for Chris, or things like that. I’m also the baseball contributor to over at mgoblog, a Michigan-centric sports blog. Last weeks struggle at Ohio State definitely has just passed by casually, even for fans of other programs. So with that in mind, I’ve been compelled to take a peak into Ohio State in an effort to find out just what is wrong with the Buckeyes. In this post, I’m going to stick mainly to the offense, as pitching is hard to compare in a very short season so far. Several pitchers have hardly enough  innings to really dissect properly. Hopefully this will give at least a little bit of tangible insight to what’s up with the Buckeyes. Enjoy.

When I start any post of a statistical nature in college baseball, I always like to start with the three major derived statistics that are available to us, batting average (BA), on-base percentage (OB%), and slugging percentage(SLG%). While batting average is somewhat hit or miss, OB% and SLG% tend to have a bit bigger influence on runs scored depending on who you ask. In the following graph (yes, Excel is fun), you’ll see how Ohio State has cumulatively progressed in those three stats, as well as see a fourth line indicating the RPI of their opponent. It’s scaled to a point where if you play the #1 team in Division 1 (using Boyd’s World pseudo-RPI as of Thursday), their data point would be at 1.000. If you play a team that is #301 in the nation, or a D2 or NAIA team for the sake of simplicity, the team would register as a ZERO in the scaled RPI. Chart:

As you can see above, OSU has been fairly consistent for the most part this season. Outside of the two losses to end the spring trip, the Buckeyes have generally shown that they can at least hit inferior pitching. When faced with teams like UCONN and Tennessee, they have a very noticeable drop in production. And there there’s teams like Marshall, or other teams just barely in the top 50% of pseudo-RPI that the Bucks stay consistent with. This probably indicates that this is about the level that the Buckeyes are competitive with, a far drop from that shiny top 25 ranking they received early in the preseason. So why is that?

When going through the individual box scores, two major things stood out to me – the defense and the stranded runners. The defense is truly atrocious with a .954 fielding percentage. The NCAA average is generally around .960, which, while sounding close, probably puts the Buckeyes in the bottom 35%. The last NCAA stat update had them ranked #214 out of 291. A look at OSU’s errors per game numbers:

That’s half of their games with 1 error or less. That’s just not going to cut it. In sum, those errors have lead to 28 unearned runs. Meanwhile, the teams that OSU is supposed to be competing with in the Big Ten, leader Michigan State and Michigan, they’re both fielding over .975, ranking in the top 30 in the nation. That’s a huge advantage the teams from up north have, they can play defense. Now, some of this bad defense can be pinned on a few individual players, most notably Brad Hallberg with a .795 fielding percentage on 8(!) errors. Cory Kovanda at second is right behind him at 7 errors on the season, but being a full time player, he’s managed to keep at least a .918 fielding percentage. It’s not entirely on them though, as 6 different Buckeyes have at least 3 errors on the season, and only 4 have fielding percentages above .960 (the 2008 NCAA average fielding percentage) in Burkhart, Streng, Dew, and Stephens. Dew is the only outfielder and Streng is aided by getting plenty of put outs playing first base (he has 3 errors as well).

The other stand out statistic is runners left on base. This stat is a little less concrete, but I’ve created a visualization to help at least put it in perspective. In the following graphic, the size of the player’s tile is based on their number of RBI. The color of their tile represents the number of runners they’ve stranded. The darker the color, the more runners left on base.

Click any image to see full size representation

Looking above, it should be no surprise to OSU fans that Hurley, Stephens, DeLucia, and Kovanda are the big RBI producers. To further that, Hurley and Kovanda have done very well with runners on and two outs, stranding very few base runners. Stephens, while dark orange, isn’t that bad of a situation. He’s been fairly high risk high reward. DuLucia, in the same way, is producing more RBI than he’s stranding runners. That’s good. The surprise though, is how many runners are getting stranded by Dew and Burkhart. Those two were expected to be big RBI guys this year, and to some extent, they just aren’t producing the way that they should be with runners on.

Looking at the slugging percentages, we can also get an idea of how certain players are doing. That chart:

Again, Hurley is destroying any and all pitching. Likewise, Stephens is as well, but due to a brief injury stint, he’s a bit behind in at bats. Meanwhile, Streng really stands out:

Streng 66 14 18 6 4 2 10 1 0 1 0.273 0.333 0.288 19 119 9 3 0.977 0 1 4

By making Dew the designated hitter instead of the everyday first baseman, Streng is being inserted into the lineup. He’s been a blatant weak link in the lineup, and a change may be warranted. While stats are somewhat limited on the back ups, I like the idea of using Cypret as a designated hitter just due to his ability to get on base this season. He doesn’t have to be the stereotypical RBI power hitter in the DH role, but rather someone who gets on base and lets others knock him in. That’s just as valuable in this lineup. Sure, he may not have a lot of AB’s this season, but he should be given a chance given his production in games where he has gotten multiple at bats (6/16, 4 R, 3 RBI, 2 BB).

We’ll take at one more visualization of this kind next. This relates the on-base percentage (color) to number of runs scored (tile size).  This is a slightly tougher visualization to make out as one metric (runs scored) depends on usage rate. I’ll give you an example after the chart:

Here, you can see Rupert has been a machine at getting on base, but he’s very low on the list of runs scored. Looking at the above visualization of slugging percentage vs. at bats, you’ll also notice he’s had half as many at bats as any of the major hitters. Despite that, you can see he’s scored nearly as many runs as as Stephens, DeLucia, or Streng. While part of the reason Rupert doesn’t see much playing time is his defense (4 errors for a .826 fielding percentage), he’s got a huge offensive advantage over Engle in the middle infield. Even Engle has four errors this season, granted he’s had quite a few more opportunities to redeem himself.

Between these two playing time questions, I’m lead to believe that perhaps Bob Todd isn’t giving his lineup much consideration? It would seem to me that with Hurley’s great numbers, you’d be batting him second or third in the lineup. Why is his bat being wasted at lead off? Why isn’t Rupert given a bigger shot and a chance to hit lead off with Hurley, Stephens, and Burkhart behind him? If he’s going to be an RBI producer again, can Dew be dropped in the lineup to get him some better chances with runners on base in front of him, at least getting the pressure off him? Or can we bump him up to take advantage of his solid on-base numbers? All these seem like reasonable questions to be asked.

If it were up to me, I’d have a lineup that looked a bit more like this:

# Player Po.
1 Rupert R 5
2 Burkhart 2
3 Hurley 7
4 Stephens 8
5 Dew 3
6 DeLucia 9
7 Kovanda 4
8 Cypret DH
9 Engle 6

I think this maximizes the on base capabilities as well as the power. I think it’s time for change, and this lineup at least gets the opportunity for players to compete. I will note that I originally wanted to switch Burkhart and Dew, but after looking into the speed of each player, I had them switched. As far as Todd’s propensity to create an alternating righty, lefty, righty lineup, I just don’t think it works with his talent that well.  I can’t justify unlinking Burkhart and Hurley in the lineup as back-t0-back lefties. Stephens just isn’t as good as either of them to warrant insertion.

On the other end of the spectrum, most of the outsiders opinion on pitching can be boiled down to one decision: Why on Earth did Todd schedule 7 games (potentially 8 according to the schedule) in 7 days? There’s no way that the bullpen was going to be able to handle that. While yes, they do have quite a break after the week long of pitching, there is an extreme increase in the chance of injury pitching this much. Eric Best made a start and 3 relief appearances during that time. That’s unsettling knowing that he was being slowly worked back into the pitching staff following a injury.

Things like that make me question some of the practices in Columbus. It just seems sketchy or potentially threatening. When added to the strange reasoning with the batting order, I wonder just what it will take before Buckeye alumni and fans start to put the heat on Todd. Sure, last season was a great year, but how much of that was on the coach, and how much of that was on his players counteracting the coaching? I’m not sure.

Whatever it is, it’s been an interesting year already for Ohio State, and it probably won’t change over night when the Big Ten season comes around.

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2 Responses

  1. Board room or front office? Because every MLB team uses more statistics than ever before. The Billy Beane money ball thing was one thing, but the expansion of statistical analysis in general is everywhere in baseball not just small markets in MLB. I see what you’re saying that baseball is a simple game and I think you need to trust your eyes, but there is certainly a place for statistical analysis too, IMO.

  2. These non-DI games mean little.

    Lake Erie (DII) just beat Cleveland State. After Cleveland State beat Kent State.

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