Last week I showed the players with the biggest leaps in scoring from 2012-13 to 2013-14. One thing I didn’t show on that list was the freshmen who burst onto the scene, and the different factors that contributed to their PPG scoring. Jabari Parker and Andrew Wiggins may have received all the headlines, but they weren’t the only freshmen with amazing scoring numbers. For some of these players, their production is tempo aided. See Q.J. Peterson at VMI. And for everyone but Parker, Wiggins and Fordham’s Jon Severe, they played in conferences where the opposing defenses were not nearly as stout. But PPG scoring at this rate is still special in any league.

Freshman

Team

PPG

Raw Pace

Opp Def

ORtg

Pct Poss

James Daniel

Howard

21.0

67

106

104

34%

Andrew Rowsey

UNC Ash.

20.3

70

108

111

26%

Jabari Parker

Duke

19.1

65

101

112

32%

Q.J. Peterson

VMI

19.0

75

109

107

27%

Jon Severe

Fordham

17.3

69

101

97

29%

Damon Lynn

NJIT

17.2

69

108

106

25%

Martez Harrison

UMKC

17.2

71

106

100

30%

J. Brownridge

Santa Clara

17.2

66

104

121

23%

Andrew Wiggins

Kansas

17.1

69

101

113

25%

Cameron Payne

Murray St.

16.8

68

108

107

30% 

If these players are this good as freshmen, it is tempting to wonder how good they will be next year. If Santa Clara’s Jared Brownridge’s ORtg is already 121, is he going to be setting a new record soon for points per possession performance?

After all, the data show that the biggest leap in production is typically between a player’s freshman and sophomore seasons. But we need to be a little careful with this statement. The reason that sophomores typically make the biggest leap is because freshmen tend to make the most mistakes. They take more bad shots and commit more avoidable turnovers. As the following tables show, the improvement in efficiency for freshmen is largely driven by the fact that they make the most mistakes.

The table shows all D1 players in the last 10 years with at least 100 possessions in consecutive seasons. I show how their ORtg changes based on their ORtg in the previous season. For players with low ORtgs, bigger improvements are both possible and likely. When you make more mistakes, you are more likely to improve. But for players with high ORtgs, players that didn’t make a lot of mistakes, the odds of becoming more efficient are smaller. When a player has an efficiency rating over 125, it is highly unlikely that the player will improve on that ORtg the following season.

The next table pulls out the freshmen separately. They are show in red. On the whole, these players perform at a worse level. (Players on the left side of picture have lower ORtgs.) And thus on average, freshmen are more likely to improve. But for freshmen on the right side of the picture, freshmen with high ORtgs, are unlikely to see sizable jumps in efficiency the following season. (Note that freshman with high ORtgs may still earn more playing time and see their PPG production increase for that reason.)

That isn’t to say that some player characteristics don’t matter. The next table pulls out the Top 100 recruits in red. These recruits not only have higher ORtgs in general, they are also more likely to improve. Stated differently, for a player with an ORtg of 110, the Top 100 recruit is more likely to maintain or improve on that efficiency, while the player outside the Top 100 is more likely to slip back.

Of course as the graphs show, almost anything is possible. Quality recruits sometimes don’t get better, and low ranked recruits sometimes do get better. But high school evaluations of a player’s ability do have a small amount of predictive power for improvement.

This is all a long way of telling college basketball prognosticators to be careful. The sophomore leap is real, but it is largely about freshmen correcting mistakes. For polished and skilled freshmen, don’t expect the same huge jump in efficiency.