While we mostly focus on Major League Baseball here on the site, it’s not the only game in town. In fact, while MLB is playing glorified exhibition games in Arizona and Florida, the NCAA is playing games that actually count right now. And, while college baseball doesn’t get the same attention that several other college sports get (especially in March), there is a pretty good reason for each of us to be paying attention to the scores each weekend now – a rule change affecting the type of bats that can be used that may be drastically altering the game at the college level.
The rule essentially governs the type of metal bats that can be used in NCAA games, and requires them to meet a standard of Batted Ball Coefficient Of Restitution. In English, the new bats create a collision between the bat and ball which is not as impactful. When teams began receiving these bats last summer, they immediately noticed the difference, and many coaches predicted steep declines in offensive levels across the sport. There have been about 900 NCAA games played so far this season, so we’re starting to get to the point where we have a decent sample to draw from. Have the bats made a significant impact?
New bat update, comparing first 10 days of 2011 vs. first 10 of 2010. 2010: HRs were 2.8% of BIP. 2011: 1.8% of BIP. Huge.
Also, with new bats, run scoring down even more last weekend. Again, thru first 10 days: 2010: 7.5 runs/game. 2011: 6.25 runs/game.
Home runs are down roughly 36 percent, while run scoring is down 14 percent. We’re still dealing with smaller samples than we would like, but as a first glance, the changes seem to be as advertised. The ball is simply not traveling like it did before, and while it’s possible that weather or other factors could be impacting the results, it’s likely that the change in bats is the main driver of the lower levels of offense.
For the average Major League fan, this simply means that you shouldn’t compare raw statistics from this year to previous years when trying to make conclusions about how a player is performing leading up to the draft. For instance, Anthony Rendon is generally considered the best hitting prospect in the draft. As a sophomore last year, he hit .394/.530/.801. So far this year, he’s hitting .393/.514/.643. While the raw power numbers are down, can you eyeball that and tell whether his performance relative to the new league standard is on par? I can’t, and I’d imagine there’s probably only a half dozen people on earth who can.
College data is tricky to begin with. Conferences are not of equal strength, there are some crazy park factors at certain schools, and the quality of the opposing pitcher can be dramatically different on Fridays than during the middle of the week. When you toss in a changing run environment due to alterations in equipment, the data becomes even more difficult to interpret correctly. That isn’t to say it’s useless, but you should tread carefully when drawing conclusions from college stats in general, and doubly so this year. Follow the guys over at Baseball America and College Splits, as they have their finger on the pulse of the game, and will understand how relative performances stack up.
We like data, but it is often used incorrectly. You’re going to see a lot of incorrect usages of college data in the next few months. Keep the new bats, and how they are impacting the game, at the forefront of your mind.