I love the game of baseball. I played it longer than any other sport during my lifetime, and every year I tell myself that I'm going to pay more attention to Iowa baseball, and every year I get sidetracked. In 2011, I even went as far as buying a pretty awesome (at least I thought so) Iowa baseball t-shirt to get myself pumped for the season. Unfortunately, I was wearing it when I climbed and fell out of a tree in Bosnia. The shirt was mostly white, and as I rolled down the hill, my mostly white shirt turned mostly green and brown. Needless to say, that shirt stayed in Bosnia and I have not bought another since.
This spring, I'm going to try to at least pay occasional attention to this team. So with a little break before Iowa basketball starts tournament season, I thought I would dive into the early season stats for the Hawkeye baseballers.
As we know, they started off the season red hot. And even though they just recently dropped three straight to Kansas State, they are still 9-4 on the season. So, what have they been doing right so far this season? What have they done wrong? And, more importantly, just how good are they?
Let's see what we can find out.
Iowa vs. The Rest of the Big Ten
Let us start by first looking at each team's stats through Monday, March 10th. First, hitting:
For more information about the listed stats, click on the abbreviation above the column for a link to some nice resources.
Each team is ordered by their weighted on base average (wOBA), which is a stat that properly assigns value to things a hitter does. For instance, a home run is worth 1.95 runs on average, while a single is worth 0.90. Because it properly weights these things, it is superior to batting average, which counts home runs the same as singles, and doesn't take into account walks. Think of it like you do eFG% compared to FG% in basketball. Keep in mind, however, that these weights are for Major League Baseball, so they may not directly apply to college. With that being said, I still think they get the job done.
Anyway, the "+" categories are how good each team is compared to the Big Ten average. For instance, Iowa has a wOBA+ of 119, which means their 0.390 wOBA is 19% better than the Big Ten average of 0.329. As you can see, the Hawkeyes have been well above the Big Ten average in every offensive category so far this year.
Now, let's look at pitching:
The chart above shows pitching stats for each Big Ten team ranked by fielding independent pitching (FIP). Again, think of FIP as the eFG% to ERA's FG%. However, I'm not sure how directly FIP translates from MLB to the college ranks but, again, I think it works well enough for our purposes.
Interestingly enough, Iowa's FIP is 8% above the Big Ten average, while their ERA is 5% below the Big Ten average. That's because Iowa has been good at limiting home runs and has been even better at striking opposing batters out. Where they have struggled, though, has been with walks and hit batters. FIP takes into account only those three categories, because those seem to be what a pitcher has the most control out of. Once a ball is hit, it is basically up to the defense to convert it into an out. With an FIP lower than their ERA, you could make the argument that Iowa's pitching staff has been better than what they've looked based on runs allowed so far. Unfortunately, that doesn't necessarily mean regression to the mean for the Hawkeye pitchers, because the schedule will most likely get tougher as the season goes on, which brings me to my next point.
Division I college baseball has 264 teams, all with various different talent levels. This makes it difficult to compare teams. And, in this case, it makes it even more difficult to compare within a conference like the Big Ten when none of the teams have played each other yet this season. In other words, just looking at raw, unadjusted stats is extremely misleading. To get a better idea of each team's actual talent, I like to use Boyd's World's Iterative Strength Ratings (ISR). For more information on ISR click here. Also, I recommend browsing the site, as there is a vast wealth of knowledge to behold, including past years' strength of schedule ratings, park factors, etc.
Now, let's look at what Boyd's World says about the Big Ten, again through Monday, March 10th only:
|Team||W%||BW Rating||BW Rank||SOS Rank|
The ISR ratings work similar to mine in college basketball, where 100 is average, and anything above 100 is above average. Right now, ISR has Iowa at #101 in the country with a rating of 105. Perhaps the most important thing to consider this early in the season is that Iowa's schedule rates out as the 220th most difficult schedule out of 264 teams and the least difficult in the Big Ten. That's not very good. Essentially, Iowa has played a bunch of cupcakes so far, and has beaten them up pretty badly. Well, except for when they were swept in a three game series vs. #112 Kansas State this past weekend. So, aside from Kansas State, Iowa has handled their business against a very weak schedule thus far.
Okay, so we've got numbers, but you're more of a visual person. Here are some charts:
Plotting each team by their winning percentage and their strength of schedule, what we see is that Iowa currently has the best win percentage in the Big Ten. They also have the weakest schedule, too. By a lot. Ohio State, Indiana, Michigan, and Nebraska look pretty good in comparison, as they all have pretty good win percentages against much more difficult schedules. Meanwhile, Purdue... They've had the second most difficult schedule this year, and have gone 1-11.
Next, let's look at each team's runs scored vs. runs allowed margin per nine innings compared to their schedule:
Again, Iowa has outscored their opponents by over 2 runs per nine innings, but have done so against a slate of cream puffs. Despite having a slightly below 0.500 win percentage, Illinois is really the only other team to have a positive runs per nine margin against a tougher than average schedule. And, really, they are the only team in the conference with those bragging rights right now. Also, Purdue... again.
Finally, let's look at the ISR rankings against each team's strength of schedule:
Again, we see Iowa with an above average ranking, but a below average schedule to date. Meanwhile, it looks as if Ohio State, Indiana, Michigan, and Illinois are the tougher teams in the conference.
So there's a brief overview of Iowa's season compared to the rest of the Big Ten to date. But what about the micro, since we just covered the macro?
Sorted by wOBA, Taylor Zeutenhorst has been Iowa's best hitter at this point in the year. Zeus (that's easier to type than Zeutenhorst, and I like it as a nickname, so that's what I'm calling him) has 2 of Iowa's 7 home runs on the year, 1 of their 3 triples, and 3 of their 26 triples. In addition, his added ability to draw walks (and get hit by pitches) on the year, has helped offset his tendency to strike out.
I'll let you dig further into the tables (keep in mind that these numbers ARE NOT adjusted for strength of opponent, so grain of salt please), but just about all of their offensive players have been above average this year in terms of wOBA. So that's good.
Let's wrap up the hitters with some charts:
The chart above breaks down each player's trips to the plate this year based on the outcome of that plate appearance. You can see that Tyler Peyton (in only 29 plate appearances) has turned the highest percentage of his plate appearances into hits. Here we can also see Zeus' propensity for walks and strikeouts.
Our last hitter chart breaks down each player's hits on the year:
Enter Blake Hickman. His 3 home runs out of 8 hits on the season stands out on this chart. Add in his 2 doubles on the year, and it's pretty clear that his ability to drive the ball for some power gives him the fourth highest wOBA on the team this year. And despite having an awesome power-hitting name, Jake Mangler has been basically all singles so far this year. Again, there is plenty of data for you to look over on your own here, so let's move on to the pitchers.
|Pitcher||IP||BABIP vs.||BABIP vs.+||Avg. vs.||Avg. vs.+||OBP vs.||OBP vs.+||SLG vs.||SLG vs.+||OPS vs.||OPS vs. +||FIP||FIP+|
As it turns out, in addition to being a pretty good hitter (albeit in only 29 plate appearances), Tyler Peyton has been a decent starting pitcher this year. Of course, a 4% above average FIP against a weak schedule isn't exactly the equivalent of setting college baseball on fire. Calvin Mathews' 24% above average FIP, on the other hand (weak schedule be somewhat damned) looks pretty impressive. I mean, at least this looks like Mathews (a sophomore!) could be a pretty good pitcher come Big Ten play. That being said, we should also keep in mind that 22 innings pitched isn't much of a sample size. So let's not jump the gun just yet.
As for the charts, let's compare the starters:
Looking at Matthews' numbers, we see that part of his FIP is probably being driven by the fact that he has yet to give up a home run in his 22 innings. That being said, his strikeouts per nine innings is second best out of Iowa's starters, while his walks and hit batters per nine is the best by quite a bit. Tyler Peyton, though, definitely looks like his FIP is being driven by keeping the ball in the ball park. College baseball doesn't have batted ball data, so I don't know if he's a ground ball pitcher, as opposed to a fly ball pitcher, but even if he was, once he starts facing better hitters, his FIP+ is most likely going to drop below 100 quite a bit. Andrew Hedrick is basically Tyler Peyton, only he has already dropped below that 100+ FIP mark. Meanwhile, Sasha Kuebel has been hit more times than a Georgia Tech quarterback by Adrian Clayborn in the Orange Bowl. That seems to be a whole lot of bad luck, though, as his opponent's BABIP is at 0.458 (!!!), and in only 12 innings. His strikeouts seem to imply that he has great stuff, but his walks seem to imply that he doesn't always command that stuff very well.
Overall, 75% of this starting rotation seems to have a bit of a walk problem. That could be an issue come Big Ten play.
Finally, let's end this long piece with a look at the relievers:
(Note: I didn't include HR/9 on this chart because Iowa's relievers have yet to surrender one.)
Ryan Rumpf and Blake Hickman have posted high strikeout numbers, but have only pitched 2 and 3 innings, respectively. Radtke, Hibling and Shulista, though, have pitched 9, 8, and 7 innings apiece. Radtke has been better than average in strikeouts and walks, but has been responsible for more runs than expected. Shulista has been the exact opposite (Small sample sizes, y'all!). Hibbing, finally, has been kind of in the middle, but with more runs. These are all tiny samples, so let's wait until later in the year to pass any judgements.
Okay, so, there you go. There's your overview of Iowa's baseball team 13 games into the season. They started off the season extremely hot, but we should keep in mind that they have played a very easy schedule. Despite the lineup of cupcakes to begin the season, the bats look like they might be pretty good this year, seeing how the Hawkeyes' offensive numbers have been so far above the Big Ten average to date. It's the pitching, though, that seems a bit worrying. Calvin Mathews looks good so far, but the rest of the starters seem to have some control issues and I would be very surprised if any of the remaining three could finish the season with a FIP+ greater than 100. And I'll wait to pass judgement on the relievers.
Overall, this looks like it could be a middle-of-the-pack Big Ten team this season. ISR has them at #4 in the conference right now, but I'm not sure they are better than Michigan or Illinois. It should be interesting to follow them as the season continues. I will probably check in on their stats every so often for the remainder of the year. Next up, they face a Georgetown team that ISR has ranked #238. In reality, it doesn't look like Iowa will be challenged again until they play 81st ranked Nebraska on March 21st. Until then, let's hope Iowa keeps piling it on their below average foes. That's really all we can hope for with a schedule rated so low.