Tulane Baseball: Early Season Recap

Every week for the remainder of the season we'll do a rundown of the past week's games (including midweek) and player performance. We encourage comments and contributions -- email us at CWATCF@gmail.com if you're the appropriate combination of stats nerd and Tulane fan.

Following last weekend's games, Tulane is 6-2 (yes, we're aware they played last night -- it'll be covered next week).

Mar 02, 2008	Minneapolis, Minn.	Tulane Green Wave 5, TCU Horned Frogs 3	Box score
Mar 01, 2008	Minneapolis, Minn.	Minnesota Gophers 7, Tulane Green Wave 5	Box score
Feb 29, 2008	Minneapolis, Minn.	Pepperdine Waves 4, Tulane Green Wave 2	Box score
Feb 27, 2008	New Orleans, La.	Tulane Green Wave 10, Louisiana-Lafayette 1	Box score
Feb 26, 2008	New Orleans, La.	Tulane Green Wave 4, Southeastern La. 3	Box score
Feb 24, 2008	New Orleans, La.	Tulane Green Wave 9, Illinois Chicago 2	Box score
Feb 23, 2008	New Orleans, La.	Tulane Green Wave 4, Illinois Chicago 3	Box score
Feb 22, 2008	New Orleans, La.	Tulane Green Wave 6, Illinois Chicago 0	Box score

UIC, unsurprisingly, was a bit of a mismatch for the Green Wave, and doesn't tell us much. The victories over ULL and SELA, however, were solid and cause for a good bit of hope -- repeat after us: Louisiana baseball is the best in the nation. On the other hand, the 1-2 weekend in Minnesota wasn't exactly a disaster -- the competition was solid, if not great -- but it exposed a few potential weaknesses. Like last year, the Wave are striking out a bit too much, not walking quite enough, and not showing a ton of patience at the plate. As the YOGWF boys have pointed out, some of that can be attributed to some strange strike zones in the early games (perhaps the umps have a bit of warming up to do, too?) ... but if it doesn't get fixed, Tulane's going to have trouble putting up runs against better pitchers.

Speaking of pitchers, the majority of Tulane's have been excellent, sporting a WHIP of around 1.21. The starters in particular have been exceptional, going deep into games and proving to be difficult to hit. That said, there are some signs of trouble on the horizon. Some of the BABIPs are unsustainably low, the BB/9 of 3.84 is teetering on the edge of ugliness, and holy crap we've hit 16 people in 9 games!?!!?! We may need to invest in Kevlar vests for visiting teams.

Still, if we get pitching like this for the rest of the season, we'll be playing well into the summer.

Player	SLG%	OB%	EqA(Natl.)	EqA(CUSA)
Jared Dyer	0.654	0.433	0.323	0.330
Aja Barto	0.714	0.441	0.355	0.362
Sam Honeck	0.367	0.382	0.239	0.246
Rob Segedin	0.375	0.303	0.208	0.214
Drew Allain	0.406	0.343	0.244	0.251
Seth Henry	0.280	0.333	0.161	0.168
W. McFadden..	0.348	0.357	0.255	0.261
Anthony Scelfo	0.414	0.378	0.265	0.272
Josh Prince	0.143	0.217	0.095	0.085

(FYI, EqA National balances the team's stats against a large sample of national teams; CUSA only uses conference stats. Go here for a primer on EqA, or here for our breakdown. Go here for full Tulane stats.)

A few things stand out here, even given the small sample size or around 25 ABs: Dyer has had an All-American start to the season, Barto has been excellent (though his 33% K rate is frightening), Henry has had a rough first two weeks ... and wow, Prince (a big time transfer) has been horrible. What worries us is that RJ won't give him enough time to work through his early season troubles, and there's not a great second option at SS.

Note for uber-nerds:

We use last year's statistics from CUSA, Big 10, Pac 10, ACC and SEC schools for our league numbers. This is poor methodology, obviously, but we do it for several reasons: 1) College baseball stats are hard to find (especially for smaller leagues like the SWAC), rarely updated, and poorly organized. Using last year's stats means that we don't have to spend hours finding and reformatting stats from various leagues. Assuming no major changes (new bats, etc.), statistics should be similar from year to year. 2) Since the season is relatively short, sample size is relatively small. Using the larger pool of numbers from last year gives us a more accurate reading. 3) College baseball ballparks aren't uniform and often don't play "fair." Bigger leagues play more games in relatively uniform, "fair" parks and therefore are more susceptible to statistical analysis.

We should also note that none of the numbers are park adjusted. The rationale here is the same as above, coupled with the fact that Tulane's new stadium, unlike Zephyr, plays relatively fair -- Rick Jones said it, so it must be true. When we post next week about last year's team, we will park-adjust for Zephyr.

In other words, spare us the bitching or do a better job yourself.