Unless you’ve been living under a rock for the past few weeks, you’re probably aware that Cornell’s baseball team has gotten off to a hot start this season. Through ten games, the Big Red are 6-4 (including 5-1 over their last six), good for the best record so far among the Ivies. Though the games that lead up to conference play are considered preseason and don’t count towards the final Ivy League standings, Cornell has started strong, and as of d1baseball.com’s latest rankings, they have the 79th best rating percentage index (RPI) in the country. This puts them second in the Ivy League behind only Princeton (41st best), and ahead of perennial powerhouses including USC (80th), Cal State Fullerton (88th) and Long Beach State (93rd). So after the disappointing 13-27 season last year, the questions we should look to answer are these: how has the team gone from bottom to top so quickly, and is this success sustainable?
There are a lot of different factors that we can look at upon delving into this subject, but perhaps none is as important as the impact new head coach Dan Pepicelli has had on the team since taking over in early August. While his influence may not necessarily be graph-able or chart-able like some of the other factors we’ll look at, there’s no denying that the new head coach has brought big changes to the team’s attitude. His high-energy, high-intensity style has helped the team focus, says walk-on senior Marlon Rainville. “Every time we’re on the field, we’re treating [practice] like a game.” Freshman Josh Arndt adds that “the coaching change has brought a lot of extra energy, and the team has really picked up on that.” The first season under a new head coach is always certain to have added excitement, and it looks as though Coach Pepicelli has been able to focus that excess energy into making the team even better.
Another factor that we can look at is the relatively mild winter that Ithaca has had. While the temperature in December likely doesn’t have a huge impact on how a
team does the following spring, there may be more of a correlation than one might think. The warmer a winter is (and the less snow there is on the ground), the more a team can practice on the field and see live pitching/hitting, the impact of which should not be understated when talking about early season performance. Below you can see a graph which takes the past seven seasons of Cornell baseball and plots number of wins in the first ten games against the average high temperature during the preceding winter. Even though the sample size is fairly small, and even though there is a large difference in skill level between teams from year to year, we can still see a slight linear correlation between the two variables. The r value sits at about 0.6, meaning the correlation is small (as expected), but it does give us reason to think that the warmer weather this past winter might have had some impact on how well the Big Red are doing to start the 2016 season.
We know that the team has done better in terms of wins, but we can also look at various other statistics from the first ten games and compare them to those of last season in order to see what on-field events have led to Cornell’s success. Let’s begin with the three statistics that make up the slash-line
: batting average, on base percentage, and slugging percentage. As you can see in the graph on the right, the team’s batting average and on base percentage are marginally better than they were last year; batting average has improved by four points to .250, while on base percentage is ten points higher this season, putting it at a very respectable .339. The team’s slugging percentage, on the other hand, has jumped from a measly .324 last season (less than the team’s OBP) to the .395 that it’s currently sitting at. Another handy statistic that we can look at is isolated power (ISO) which measures how many extra bases a player generates per at bat and is calculated by subtracting batting average from slugging percentage. Over the first ten games of the season, the Big Red as a team have an ISO of .145, which to put it into perspective is around the same as what Jose Altuve and Jason Heyward had last year in the MLB. More importantly, it’s significantly higher than what it was last season (.078). From this we can see that the Big Red, compared to last year, are getting more hits, are getting on base more frequently, and have more of their hits going for extra bases.
So clearly, the Big Red have been riding an offensive surplus to generate more runs and therefore win more games. The next question to answer then, is how many more extra base hits has Cornell produced. To compare last season’s offensive production to that of this season, I’ve created the graph to the left which is basically a cumulative distribution function of extra base hits and home runs. Simply put, it measures the total number of extra base hits and home runs the team had over time. As you can see in the graph
, the total number of extra base hits this season isn’t actually that much greater than what last year’s team had through ten games. Instead, it’s the type of extra base hit that has caused the increase in slugging percentage. So far in 2016, the Big Red have hit ten home runs. In all of 2015 the team hit six, meaning that in only the first quarter of the 2016 season, the team has surpassed, and nearly doubled, last year’s total. In fact, the 2016 team equaled the 2015 total in a single game; on March 12, in a game against Wofford College, the Big Red demolished the Terriers’ pitching to the tune of six home runs. At this pace, this year’s team will hit over six times as many home runs as there were last year. So why the sudden power surge? A lot can be credited to Cole Rutherford, a junior transfer from Orange Coast Community College. So far this season, Cole has accounted for four of the team’s ten home runs, as well as driving in 11 runs and slugging .771. What’s more interesting is the fact that Rutherford has only 10 hits on the season, meaning that 40% of his hits have left the yard. Additionally, he has a double and two triples, meaning 70% of his hits have gone for extra bases. The offense has also been led by sophomore Dale Wickham (2 HR, 6 RBI, .579 SLG) and junior Tommy Wagner (1 HR, 4 RBI, .439 SLG).
From the data seen so far, it’s fair to say that the team’s early success is in large part due to their uncharacteristic surge in power. The final question to answer then is this: is there any chance that the Big Red will continue to hit at this torrid pace or has the offensive outburst over the first few games simply been a statistical anomaly, bound to regress towards the mean? Statistically speaking, one would expect the team’s offense to slide towards its true talent. This is not a team that should be hitting one home run per game; by removing the March 12th game from our sample, we can see this. When ignoring the six home runs hit that day, the team has hit only four home runs over nine games, giving them 0.44 per game – a lot closer to where they should be. Therefore, we should expect the power to drop somewhat from what we’ve seen so far in the coming series, in turn dropping the team’s slugging percentage and isolated power.
That said, one of the major indicators of how a team is performing relative to how they should be is the team’s batting average on balls in play (BABIP) which for the Big Red has been surprisingly low so far this season. Last season, the team had a BABIP of .298, meaning 29.8% of balls put in play by the team fell for hits. This season, the team’s BABIP is so far only .278, a whopping twenty points lower than last year. Not a single major league team in 2015 had a BABIP lower than .280, and with college defenses being much less skilled than professional ones, one would expect even the worst college team’s BABIP to be higher than .280. Therefore, even though Cornell’s power will likely regress, the team’s batting average and on base percentage should both rise as the season progresses, and if this is the case, then there’s no reason to believe that the Big Red won’t continue to score at their current pace. Assuming the pitching will continue to perform well (the team ERA is a 4.93, over half a run better than last season’s 5.54), this is a team that should remain towards the upper-end of the Ivy League for the rest of the year.
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