March 30, 2019, 4:30 pm
Hey Hoop-Ballers! As the NCAA Tournament marches on, and the time to expand our focus beyond the immediate needs of the fantasy playoffs draws near, what better time than now to continue our focus on the incoming rookie class from the 2019 NBA draft.
If you’re keeping score at home, so far we’ve covered a rough top-15 list of the incoming rookie class (more for dynasty, as where these players land will heavily impact re-draft value), and had a look at some sleeper candidates outside of the lottery that still may serve as meaningful fantasy contributors. With a lot of projection and speculation on the record at this point, it seems like the right time to take a step back and show my work a bit on this math and go over some of the nuts and bolts of attempting to translate college (or international) play into the NBA.
The Sweet Science (Read: Educated Guessing)
Off the bat, I need to throw out the disclaimer that this is not a science. You can argue that there is an art to scouting, and those whose job it is to do this stuff are in the Picasso level class, while I’m still working on my happy little Bob Ross trees. Still, there is no simple equation for guaranteed NBA success based on college stats, eye test metrics or measurables alone.
Even if a scout perfectly manages to peg the strengths, weaknesses, and projected ceiling of NBA prospect, any number of outside factors ranging from coaching and management to personal life and emotional variables can throw a perfect evaluation out of whack.
While it may seem that there are more ways to get it wrong than right (a straight ranking of 1-60 is an easy way to get it wrong), we still have an immense amount of data, trends, correlation and checks on the well-trodden eye-test metrics to help make better informed decisions, or educated guesses if you will.
Metrics that Matter
One of the latest poster-children of college dominance leading to NBA irrelevancy is Jimmer Fredette. The scoring numbers that the he was posting in his senior year of college (albeit in a fairly soft Mountain West Conference) were ludicrous. 28.9 points per game on 45 percent shooting (89 percent at the line) with 3.4 triples, 3.4 rebounds, 4.3 assists, 1.3 steals, and a tough-to-accomplish 0.0 blocks. Digging into his advanced stats we see a decent, but not dominant, 9.5 box plus/minus, a good but not great 2.1 percent steal percentage and a good 59 percent true shooting percentage.
What can we learn from this when attempting to predict the next highly drafted bust, or late selection star? In the case of Jimmer alone as a case study, perhaps not a lot. However, his example taken in the context of some statistical analysis translating college production to the NBA, his case becomes a lot more interesting.
A 2009 analysis done by now Director of Analytics for the Cleveland Cavaliers, Jon Nichols, showed that the strongest correlation between per-minute college statistics and NBA statistics (listed in descending order) came in the categories of blocks (0.93 R^2), assists, rebounds, 3-point percentage, free throw percentage and steals (0.59 R^2). The weakest correlations were between per-minute points (0.34 R^2) and field goal percentage (0.34 R^2), among other things like free throw attempts and fouls that are more in the weeds.
A more recent analysis in 2018 by Fri Lavey (which admittedly has a smaller sample size) found somewhat similar results. Highest correlations – listed in descending order – between per minute college block rate (0.8 R^2), 3-point percentage, rebounding rate, steal rate, and, contrary to Nichols, field goal percentage (0.58 R^2).
Regardless of the differences between both studies (only major discrepancy is in field goal percentage and assists to a lesser extent), points is one of the least translatable aspects of college players games based on regression analysis. Zooming back out to Jimmer, we see a player that is primarily an elite scorer (poor translation confidence), a good but not elite 3-point shooter in terms of efficiency (moderate translation confidence), a pretty average-to-poor facilitator for a point guard (moderate-to-strong translation confidence) and a slightly below average steals producer (strong translation confidence). Sounds like a pretty serious roll of the dice in terms of NBA success despite the gaudy scoring numbers.
All of this is easy to point out with the benefit of hindsight in Jimmer’s case. But, there is no hiding that the numbers do show that if elite scoring and little else are the main facets of a college player’s game, there is a significantly higher chance that it doesn’t translate to the NBA. That is not to say that a Jimmer-type prospect will be a guaranteed bust, but the confidence in college production predicting NBA production in his statistical profile is significantly lower.
Key Indicator Stats of NBA Success
I’ve said it before and I’ll say it again, the most important stat for fantasy production will always be minutes. Per-minute production can be useful tool, but often lost in the fascination with per-minute monsters is the fact that they still need minutes to put up stats.
With that in mind, when evaluating a college or international prospect for fantasy production in the NBA, even more important than translating statistical production is simply looking at whether or not they have the skill-set to crack an NBA rotation.
This is often determined through “eye-test” evaluations and combined with measurables like wingspan and height. “Eye-test” evaluations are important, and there are some incredibly talented scouts who utilize them well. I am not one of those scouts, but am an unabashed stat head (I’d imagine that is a fairly common trait among people drawn to fantasy sports), so we will be covering some statistical and analytic factors that can indicate a prospects “NBA readiness” or potential likelihood of making it at the next level.
A player’s steal percentage (particularly for guards and wings, but also applicable to bigs) is a pretty widely accepted indicator of potential success in the NBA. It can serve as somewhat of a catch-all stat that indicates positive performance in several important areas that may not always show up on the stat sheet.
Athleticism, hand and foot speed, timing, positioning, hustle and simple basketball IQ can all feed into this one stat. While the same could be said for block percentage or other defensive metrics, there does tend to be a correlation between a high steal percentage in college and NBA success.
As with all of these things, I need to qualify that it is not as simple as “elite college steal percentage = elite NBA player.” It is also important to note is that a high college steal percentage does not necessarily translate to a strong defensive player at the next level.
The way I tend to think about this stat is that it is more useful to point out as a red flag if a lottery player or a highly-rated prospect has a low steal percentage in college. The stat has more utility in weeding out potential “bust” candidates at the top of the draft than it does in finding “sleeper” picks later on in the draft.
An example of this in action from last year’s draft class that combines the steal percentage indicator with the statistical correlations discussed above is Collin Sexton. If you look at his primary strengths in college – strong per-minute point production, relatively inefficient shooting, poor per-minute assist numbers for a guard and a sub-par 1.6 steal percentage – those are a lot of red flags from a highly-rated prospect. The jury is still out on Sexton of course, so I’m not saying all this guarantees that he will be a bust, but considering all of these factors he ended up downgraded in my final rookie rankings.
Free Throw Percentage
Free throw percentage is another stat that can indicate much more than you would think at first glance. It is often used as an indication of a player’s potential to translate college 3-point shooting to the NBA, or develop a reliable outside shot if they do not currently have one in college.
First and foremost, there aren’t many long-range deadeye shooters that are poor at the line in the NBA, so that right there gives the theory of linking free throw percentage and NBA 3-point efficiency some credence. Beyond that fairly simple explanation of the correlation between the two factors, efficient free throw shooters also generally have consistent and repeatable shooting mechanics, which may better indicate a players’ potential from beyond the arc than simply looking at college 3-point percentage numbers alone.
As with all of these things, context is very important, and efficient free throw shooting will not always equal efficient NBA 3-point shooter. However, free throw percentage, taken in context with other factors like shot mechanics (looking at you, Lonzo), efficiency from beyond the arc in college, the number of 3-point attempts per game, and the amount of shots from deep that a player is assisted on can all help paint a clearer picture of potential success as an NBA shooter.
Conversion at the Rim
Efficiency at the rim can tell you a lot about a player’s game, and can really help round out eye-test evaluations. In general, what I am looking for in terms of a prospect’s efficiency at the rim is dependent on their position and playstyle, but there are some uniform benchmarks to consider as starting point.
For bigs that take at least 55 percent or more of their shots at the rim, a conversion rate of at least 75 percent or higher is usually where I start to consider prospects as plus finishers at the rim, with anything over 80-85 percent efficiency falling into the “elite” category.
For wing players, a conversion rate of around 65-70 percent or higher is where you can start to consider prospects as above average finishers at the rim, however this also needs to be taken in context with the percentage of shots they take at the rim, and the percentage of those looks at the rim at that are assisted. The same can be said for guards; around 60-65 percent is generally where I’d start to consider a player a plus finisher. Let’s use a fairly polarizing prospect in this year’s draft class as an example.
Cam Reddish has lottery pedigree, but his play this season has left a lot to be desired. The talent and that oh-so intangible “upside” is there, but I’m not convinced that he is the can’t-miss prospect that some think he is. I won’t pick on anyone in particular, but some examples of how I’ve seen Reddish described on scouting reports as a “skilled finisher at the rim, with the size and skillset to carve up defenses attacking the rim.” Watching Reddish, I guess I can see where some of these takes come from – from time-to-time he does look like that type of player – but the majority of what he has put out this season is almost completely opposite to those descriptors. Don’t believe me, let’s look at the data.
The table below takes a look at Cam Reddish in comparison with the “pure shooter” archetype of Tyler Herro, and a player in Jarrett Culver that I think actually fits a lot of the descriptions that Cam Reddish draws above.
% of shots at the rim FG% at the rim % of shots from 3pt FG% from 3pt assisted 3s Cam Reddish 19.3% 51.2% 61.6% 33.3% 80.5% Tyler Herro 21.6% 65.9% 42.5% 36.0% 81.0% Jarrett Culver 40.5% 69.1% 29.0% 33.1% 56.5%
Next to Herro and Culver, Reddish sure seems to fit the mold of a spot-up shooter far more than a versatile offensive threat pulling up and off the dribble. Reddish seemingly has the physical ability to become more than what these stats show, but his really sub-par efficiency at the rim and reliance on assisted threes does raise some red flags for me.
I’ve always held the belief that age and “upside” are overrated in both the real NBA draft and in fantasy hoops circles – particularly in dynasty formats. There are circumstances where it makes sense to go for a younger option over a veteran purely on upside. For instance, if a 21-year-old junior is producing roughly equivalent to an 18-year-old freshman, then it does seem wise to pick the younger player as their rough development curve will likely have a higher ceiling. However, as a general rule, I still think youth and upside is largely over-valued. We will likely hear plenty of debate around this subject as some likely first round and lottery draft selections are well into their early 20s, but how much attention should fantasy managers pay to a rookie’s age in dynasty drafts?
We’ll have a deeper dive on this topic going forward, with some interesting conclusions revealed about how rookies of different ages fare as they jump into the league and how they improve over time. That’ll wrap up this look at how college numbers turn into preliminary forecasts, but we’ll have plenty more on the topic as the tournament rolls on and we get into draft season!
May 24, 2019, 11:45 amNeil Olshey - Team - Trail Blazers
According to Ben Standig of NBC Sports Washington, the Wizards have shown interest in Blazers’ President Neil Olshey becoming the new President of Basketball Operations for the Wizards.
Ted Leonsis has yet to request permission to interview Olshey, who has spent the last seven years with the Blazers and is under contract through the 2020-21 season. Masai Ujiri’s name has also been thrown around as a possible candidate and the Wizards would obviously be willing to wait until the end of playoffs before rushing to a decision.
May 24, 2019, 11:32 amNikola Jokic - C - Denver Nuggets
Nikola Jokic said he plans to play for his home country Serbia during the 2019 FIBA World Cup this Summer.
“I am very pleased with everything I did in the NBA this season, I had a great year in which I performed at the All-Star Game and was selected in the NBA All-Star Five. For me, the cherry on top of this whole season would be a medal with the national team. I am fully prepared to do my best to achieve this goal”, said Jokic, confirming his participation. He will have a little bit of time to rest up, but Serbia is expected to compete against Angola, the Philippines and Italy starting on August 31. The miles will be a test for the big man, but one he has aced before.
May 23, 2019, 11:49 pmKhris Middleton - F - Milwaukee Bucks
Khris Middleton really struggled in Thursday's Game 5, scoring six points (2-of-9 shooting) and pulling down 10 boards as the Bucks fell 105-99 at home.
Middleton's disappearing act offensively was the difference for the Bucks who really need their second best offensive option to demand the ball and produce more. The airball late in the game was a microcosm of the outing for Middleton. He'll need to take more than nine shots (less than any other Bucks starter) for the team to have a good shot at a Game 6 win in Toronto.
May 23, 2019, 11:46 pmBrook Lopez - C - Milwaukee Bucks
Brook Lopez scored 16 points and pulled down eight boards on Thursday night in a Game 6 loss.
Lopez was fine in general and wasn't really a liability, but he also didn't provide as much as needed on the defensive side or from long range. For what it's worth, he has generally outplayed his counterpart Marc Gasol in this series and tonight was no different.
May 23, 2019, 11:44 pmMalcolm Brogdon - G - Milwaukee Bucks
Malcolm Brogdon reentered the starting lineup on Thursday night and put in a solid performance, scoring 18 points and pulling down 11 rebounds.
It was a better sight to see than the disastrous four points in Game 4, but it wasn't enough as his absence from the bench really sucked the offense out of the bench group as the second unit scored a whopping 15 points. A repeat performance from Brogdon and more from Khris Middleton is a potentially winning formula for Game 6.
May 23, 2019, 11:39 pmEric Bledsoe - G - Milwaukee Bucks
Eric Bledsoe showed signs of life on Thursday night, scoring 20 points, but it wasn't enough for the Bucks to overcome the Raptors in Game 5 at home.
Bledsoe was worlds better than he was on Tuesday, but the Bucks didn't have an answer to Kawhi Leonard and lost hold of the game late in the fourth quarter. A dialed in Bledsoe would really help the cause in Game 6.
May 23, 2019, 11:35 pmGiannis Antetokounmpo - F - Milwaukee Bucks
Giannis Antetokounmpo scored 24 points with six rebounds and six assists on Thursday as the Bucks fell to the Raptors in Game 5 of the Eastern Conference Finals.
Antetokounmpo continued to struggle from the free throw line, hitting just four of nine free throw attempts. It seemed like he really got beat up trying to take the ball to the basket late in the game. Even more puzzling, GA wasn't in the game for some key moments late in the game. He'll need to lead from the front for the Bucks to bring this back to Milwaukee.
May 23, 2019, 11:30 pmPascal Siakam - F - Toronto Raptors
Pascal Siakam played 36 minutes, scoring 14 points (on 15 field goal attempts) with 13 rebounds and four defensive counters on Thursday night.
Siakam wasn't efficient on the offensive side including a sequence of three missed 3-pointers on the same possession during the Raptors' sluggish start. He was pivotal to the fourth quarter defensive effort especially when protecting the rim against Giannis late in the game.
May 23, 2019, 11:25 pmFred VanVleet - G - Toronto Raptors
Fred VanVleet was on fire again in Thursday's Game 5, scoring 21 points with all his points coming from seven 3-pointers.
The distance shooting was huge for the Raptors as VanVleet outscored the Bucks' bench by six by himself. VanVleet could definitely be the key to the Raps' efforts to close this series out on Saturday. We'll see if he can keep finding his shooting stroke.
May 23, 2019, 11:19 pmKyle Lowry - G - Toronto Raptors
Kyle Lowry played 39 minutes on Thursday, scoring 17 points to go along with seven rebounds and six assists.
Lowry has been dealing with a thumb injury which may be part of the reason he's struggled with his shot at times in the postseason. Still, most guys are banged up at this point in the season and he's just going to continue to tough it out with the NBA Finals on the horizon.