Nets' draft projection: Chris McCullough

ESPN Stats & Information

Jun 18, 2015, 04:27 PM ET

According to the Chad Ford Mock Draft 7.0, with the 29th pick in the NBA draft, the Brooklyn Nets will select Chris McCullough.

According to ESPN Stats & Info’s NBA Draft Projection Model, McCullough is projected to have a statistical plus/minus of minus-0.63 in years 2 through 5 of his NBA career. Statistical plus/minus is an estimate of a player’s contribution to his team’s point differential per 100 possessions. An SPM of zero is considered league average (weighted for minutes), and replacement level players have an SPM of about -2.

The projection model calculated the likelihood of a player to fall into one of four categories: Superstar, Starter, Role Player and Bust. There are generally one superstar, 10 starters and 25 role players who come out of each draft class. The projections for McCullough are as follows (percents do not add to 100 because of rounding):

Superstar: 0.7 percent

Starter: 19 percent

Role Player: 29 percent

Bust: 51 percent

Below are the projections for the top five college players in the 2015 draft class:

Top college players in 2015 NBA draft class by projected SPM

Player	Position	Projected SPM	Superstar	Starter	Role Player	Bust
Karl-Anthony Towns	C	1.03	13.5%	42.7%	16.3%	27.5%
Justise Winslow	SF	0.88	8.4%	51.1%	17.7%	22.9%
Stanley Johnson	SF	0.68	6.8%	42.4%	27.9%	23.0%
Jahlil Okafor	C	0.52	5.9%	41.0%	23.6%	29.6%
D`Angelo Russell	PG	0.51	15.2%	34.2%	9.7%	40.9%

When projecting a player’s SPM, Year 2 through Year 5 were selected because first-round picks are under control of the team that drafted them for four years with the potential of the player taking a fifth-year qualifying offer. Rookie seasons are excluded; they often are outliers, which can be attributed to a player being drafted by a bad team, needing time to develop, etc.

To project SPM, box-score statistics (adjusted for the level of competition faced and pace of game), Chad Ford’s Top 100 Prospect Rankings and player information (age, height, weight, class year, position) were the main inputs. The model is based off this information from 2001 to 2010 to predict SPM for players in later draft classes. Steps were taken to adjust for players who played very few minutes or did not play at all in the NBA.

Scouts’ ranks were the biggest factor in projecting a player’s success. Among the other findings in the projections, younger players generally achieve a higher SPM, team-adjusted offensive and defensive efficiencies matter, and having higher adjusted rate stats (assist percentage, rebound percentage, effective field goal percentage) in college is good for a player’s projection (unadjusted counting stats such as points are not as important).