I recently wrote about The Citadel’s upcoming baseball campaign. While doing a little research, I wound up with a bunch of league-only stats for all SoCon teams, not just The Citadel. I decided to stick that information in another post, just in case anyone was interested.
Obviously, quite a bit of this is available at the league website, but I’ve also included a few other statistical categories, including team park factors, normalized run totals, and some offshoots of standard stats (like K/9, K/B ratio, etc.). I also delved into the mind of Pythagoras. Well, maybe not…
Anyway, here it is. Keep in mind, these are for conference games only. Each team played 24 league contests during the regular season, 12 at home and 12 on the road.
(Also keep in mind that I’m not exactly a statistical savant. I’m just here to entertain the masses.)
DER stands for Defensive Efficiency Rating, not to be confused with fielding percentage. DER is simply the rate at which batted balls put into play are converted into outs by a team’s defense.
The two statistics did not quite match up, which is not surprising. Fielding percentage does not necessarily indicate how well a team fields. If a play is not made, but is not an error, it is still a play that is not made.
Wofford, for example, finished in the middle of the pack in fielding percentage, but was last in DER. Of course, that doesn’t automatically mean the Terriers were the worst-fielding squad in the league. There are sample size issues, for one thing, and park factors can also come into play.
However, Wofford finished only fifth in WHIP despite leading the league in K/BB ratio. The Terriers had the second-highest K/9 and the second-lowest BB/9. Wofford allowed the second-most hits in the league (and the second-most hits that were not homers).
The “PF-Avg” and “NM-RA” categories are, respectively, “Average Park Factors” and “Normalized Runs Allowed”. I averaged park factors for every team’s league schedule, using Boyd Nation’s most recent park effects data. From that, I calculated “normalized” runs; in other words, how many runs a team would have scored (or allowed) during the conference season playing in a league-neutral environment.
As you can see, the average SoCon squad scored 163.67 runs in 24 games. Mercer, which allowed the fewest runs during conference play, fares well in this category as well. The pitching for Western Carolina and VMI looks a little better as their respective parks are taken into account.
Based on this, it appears East Tennessee State could make a claim to being the league’s best offense last season (at least, in conference action). I have to say, though, that Western Carolina almost pulling off a 1.000 team OPS in SoCon play is quite impressive, regardless of park effects.
I also ran a Pythagorean theorem check to see if any of the league’s teams were luckier than average. Let me explain…well, I’ll let Wikipedia handle it:
Pythagorean expectation is a formula invented by Bill James to estimate how many games a baseball team “should” have won based on the number of runs they scored and allowed. Comparing a team’s actual and Pythagorean winning percentage can be used to evaluate how lucky that team was (by examining the variation between the two winning percentages). The name comes from the formula’s resemblance to the Pythagorean theorem.
I used the most basic formula, not the revised Pythagenpat calculation, mainly because I’m not sure if Pythagenpat really applies to college baseball. It probably does, but I don’t think it matters much for a league season in which each team plays 24 games.
Here is the table in question:
|Team||RS||RA||PyThm||Exp W||Actual W||Diff|
The “luckiest” team in the league in 2016 appears to have been Furman. The Paladins scored almost the same number of runs as they allowed, but wound up finishing 14-10.
Wofford finished 12-12 despite allowing almost one more run per game than its opponents. The two “unluckiest” teams in the league, The Citadel and VMI, finished next-to-last and last in the conference standings.
Some of these statistics may be meaningful. Some may not. The bottom line, though, is the only statistic that really matters is how many wins you put on the board.