Numbers alone rarely tell the story about a player, especially a college kid entering the NBA draft. In general, numbers will back up what you’ve gathered already about a player, though certainly not the context and circumstances that actually let you get a better handle on a player’s abilities.
Still, there can be some value in seeing how players stack up against each other at the same position, as well as analyzing how they compare to more players who were recently drafted. It’s not going to tell you everything you need to know, and in some cases, it may tell you very little. But there will be times where numbers, similar or dissimilar, jump out at you, and those are areas where as a team you may want to do further investigating.
I’ll be looking at players who are potential first/early second round players at each position, with their numbers in areas that are relevant to their position, as well as first round picks from 2014 and 2015 at the same positions. The idea isn’t to draw clear-cut conclusions, but it is an interesting exercise to get familiar with this year’s class, and to help gather useful information to examine further.
It is another deep class of college players this year, with a wide-range of players with both scoring and passing abilities. I’m going to break this group’s look down into scoring/shooting and passing/ball control. Here is a link to this year’s shooting guards. Here is a link to the small forward comparisons.
|Gary Payton II||6'3||175||23||18.6||48.6||31.4||53.2||29.1|
|D'Angelo Russell (2015)||6'5||180||19||22.7||44.9||41.1||57.3||29.2|
|Cameron Payne (2015)||6'2||180||20||25.1||45.6||37.7||57.3||30.9|
|Terry Rozier (2015)||6'1||190||21||19.5||41.1||30.6||50.9||33.8|
|Jerian Grant (2015)||6'5||203||22||17.8||47.8||31.6||59.2||51.6|
|Delon Wright (2015)||6'5||178||23||17.5||50.9||35.6||61.9||56.5|
|Tyus Jones (2015)||6'1||190||18||13.9||41.7||37.9||57.5||50.0|
|Marcus Smart (2014)||6'4||220||20||22.0||42.2||29.9||55.2||64.8|
|Elfrid Payton (2014)||6'3||180||20||21.4||50.9||25.9||55.1||64.9|
|Tyler Ennis (2014)||6'2||180||19||14.5||41.1||35.3||51.1||41.4|
|Shabazz Napier (2014)||6'1||180||22||20.5||42.9||40.5||59.1||48.0|
|Jordan Clarkson (2014)*||6'5||193||21||19.9||44.8||28.1||54.7||41.7|
*Clarkson was a 2nd round pick, but started 38 games for the Lakers as a rookie.
Compared to the past couple of years’ point guards, this year’s group is bunched on the high end in terms of scoring, with the lowest points per 40 minutes, Demetrius Jackson, coming in at 17.3, and the highest, Kay Felder, putting up the largest number, 26.5, in the past few years. Looking at each of these player’s team situations, the numbers become very understandable. Jackson played on a Notre Dame team with a lot of ball movement to keep the defense moving and open up shooters, Felder played in an Oakland offense predicated on pushing the ball up the floor quickly for transition baskets, which was benefitted by Felder’s speed, even at just 5’9”.
As usual, there is a wide disparity in field goal percentages, both from the field and behind the arc. Only one player, Gary Payton II, hit over 46 percent from the field, after just seeing two the previous season. Also, only two players, Wade Baldwin and Yogi Ferrell, hit at least 40 percent from three. This area can be the toughest to pinpoint from a pure numbers perspective. Like Delon Wright the year before, Payton’s game is all about trying to use his size to get to the basket, knowing that he isn’t the best shooter. While there was some good size in last year’s group of point guards, only Dejounte Murray and Kris Dunn are taller than 6’3” this year, and neither is a very good shooter, though they find other ways to get their points. Murray is also the youngest player in this year’s class of point guards, though his perimeter shooting is so bad at this point, it’s hard to imagine how he could improve quickly.
The last scoring area I want to look at is free throw rate, which is the number of free throws per 100 field goal attempts. A high free throw rate is usually indicative of a player’s strong ability to attack the basket, and that was certainly true of the two players with the highest rates in the past few seasons. Marcus Smart and Elfrid Payton both posted free throw rates around 65. This year’s class features one player, Baldwin, who had a rate of at least 60, with no one else topping 50 percent. There are a lot of similarities in Baldwin’s style compared to Smart and Payton, but, as mentioned above, Baldwin was also just one of two players to hit more than 40 percent from three-point range, quite different than the other two. Payton’s free throw rate was surprisingly below 30-percent, given the amount he attacked the basket. Part of that is due to his creativity around the basket to avoid contact, but he also doesn’t look to go right at players to draw fouls. Ferrell and Jackson’s low numbers are understandable with their high number of jumpers taken.
|Gary Payton II||6'3||175||23||5.9||2.7||32.9||13.3|
|D'Angelo Russell (2015)||6'5||180||19||5.9||3.4||30.1||14.8|
|Cameron Payne (2015)||6'2||180||20||7.4||3.1||40.0||12.4|
|Terry Rozier (2015)||6'1||190||21||3.4||2.5||19.7||11.6|
|Jerian Grant (2015)||6'5||203||22||7.2||2.3||33.6||13.4|
|Delon Wright (2015)||6'5||178||23||6.1||2.3||33.0||14.2|
|Tyus Jones (2015)||6'1||190||18||6.6||2.3||27.5||15.9|
|Marcus Smart (2014)||6'4||220||20||5.8||3.2||30.1||14.0|
|Elfrid Payton (2014)||6'3||180||20||6.6||4.0||32.9||17.2|
|Tyler Ennis (2014)||6'2||180||19||6.2||1.9||32.3||11.9|
|Shabazz Napier (2014)||6'1||180||22||5.6||3.2||30.8||15.8|
|Jordan Clarkson (2014)||6'5||193||21||3.8||3.0||23.3||14.3|
Focusing on the point guard position, it’s a good idea to see how these players stack up as distributors and in limiting mistakes. As has been a trend the past few years, there is a wide range, especially in the assist categories. While not always a key indicator of what their capabilities will be at the NBA level, it is a good read on where a player’s current strengths are and what kind of role might fit them going forward. It’s always a good idea to take a closer look at the group of players who fall on the low end of the scale in both assists per 40 minutes and assist percentage. As we saw above, a big scoring burden was put on Barber at North Carolina State, and even when he was looking to pass, he didn’t exactly have a group of players around him who could translate his passes into points. Contrast that with Felder, who is also the top scorer in this year’s group, putting up the only 10-plus per 40 minutes assist number seen in the past few drafts. Playing a system built on pushing the ball up the floor quickly at every opportunity; Felder was able to see a boost to his numbers across the board. Dunn and Ulis also put up impressive assist numbers, and though very much different physically, their games were very similar in their ability to get into the defense and draw defenders.
The turnover rates are bit more disparate than we have seen the past few seasons, ranging from Barber’s near 11 percent, all the way to Dunn and Baldwin’s over 18 percent, the highest numbers we’ve seen over the past few years. Often point guard draft prospects with have high turnover rates are also main scorers for their team, with many turnovers coming from trying to force their own scoring opportunities, and, in some ways, Baldwin and Dunn fit this, though they were often just very sloppy. Barber’s low number is also surprising for the same reason, given how much scoring he was counted on for. Ulis’ 11.8 percent is also very impressive, and the number fits his ball-control game perfectly, which is a big reason he has a future in the NBA at his size.
It has been beaten to the ground by now, but the numbers alone don’t tell a player’s story; they are just more data for teams to collect as they get ready to make their picks in June. Even players with similar numbers, good or bad, are not necessarily similar players, especially if they had different roles, but it can give teams reasons to look closer at some of a player’s tendencies. The same caveats apply when you start comparing across different draft classes, but you can find some valuable clues when a lot of the other information gathered also matches up.