Ryan Knaus

The Numbers Game

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Advanced Stats' Fantasy Impact

Wednesday, December 20, 2017

I call my Wednesday column 'The Numbers Game' for a simple reason -- ultimately, fantasy basketball boils down to statistics. It doesn't matter what sneakers a player wore, what his nickname is, or how much trash he talked to an opponent. The only thing that counts is how many points, rebounds, assists, steals, blocks, etc. the player recorded. Did they hit 3-pointers? Did they score efficiently? The rest is background noise.


However, that doesn't mean we shouldn't always look for new ways to quantify fantasy value and project future production. Today's column looks at statistical metrics beyond the typical boxscores and game logs -- we're still dealing strictly with numbers and quantifiable production, just at a more nuanced level. I'll be listing commonly-used advanced statistics with three parts: 1) Definitions, 2) Real-world examples of the statistics, and 3) How they can help empower fantasy owners to make better decisions. Simple as that. Let's begin with a metric we frequently use in columns and news blurbs -- usage rate.


Note: All definitions and stats cited are from NBA.com.


Usage Rate (aka Usage %)


Definition: The percentage of team plays used by a player when he is on the floor.


Example: Players with usage north of 30% are invariably studs -- James Harden leads the league at 35.7%, followed by DeMarcus Cousins, Kristaps Porzingis, Joel Embiid, Russell Westbrook and Giannis Antetokounmpo. Whenever Porzingis misses games, suddenly his 33.8% usage is up for grabs -- enter Michael Beasley. The shot-happy backup forward has a usage rate of 28.8% this season, which is the highest among non-starters.


Fantasy Utility: We love usage for fantasy hoops, because it distills a player's offensive role into one simple-to-understand percentage. If a player's usage is trending up, that's almost always a good sign -- their coach is calling more plays for them, teammates are putting their faith in them, etc. The opposite is also true. Carmelo Anthony had a usage rate north of 29% with New York last season, but that's fallen to 24.6% with OKC. While still a substantial number for most players, the nearly 5% dip in usage takes a big toll on a player who relies on scoring for the lion's share of his fantasy value.


Usage is particularly important in points leagues and DFS, where offensive volume is paramount. In an analysis last season, I showed that usage had a strong positive correlation with overall DFS values, higher even than rebounds, assists, steals or blocks. Here's a snippet from that column (note: more weight has since been given to steals and blocks):


Statistical correlation to overall DFS values (2016-17):


"[Points] have the strongest correlation with overall value. Usage is second and it's interesting to see turnovers with the third-strongest correlation -- they are a part of usage, for one thing, and their negative impact is outweighed by the fact that players who commit the most turnovers also tend to rack up the most counting stats in other categories. My takeaway is that, for DFS purposes [and most points leagues], you can basically ignore turnovers."


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Pace (Team or Player)


Definition: The number of possessions per 48 minutes for a team or player.


Example: The Lakers lead the league in pace, averaging 104.6 possessions per game. Close behind them are the Suns (104.0), Nets (103.8), Sixers (103.3) and Warriors (103.0). Fast-paced teams tend to get out and run -- the Warriors lead the league in fastbreak scoring. At the other end of the spectrum, the slowest-paced teams in the league are the Grizzlies (95.5), Spurs (96.6), Kings (96.9), Jazz (97.3) and Mavericks (97.3).


Fantasy Utility: At the simplest level, more possessions mean more opportunities for points, 3-pointers, rebounds, assists, steals and blocks -- the counting stats we love in fantasy leagues. If you're deciding between multiple players on a busy night, or building a DFS lineup, it generally makes sense to target games with high over/under totals (the expected combined scoring for both teams). Tonight the high total belongs to the Lakers/Rockets game. At 226 expected points, there's simply more fantasy value up for grabs than in a game like Pistons/Mavericks. No surprise there, since one game features two teams with fast pace, while the other features two of the slowest teams.


You can also look at pace on an individual player level, but I don't find that to be helpful for fantasy purposes. It's basically just a reflection of the team-based data. One interesting wrinkle, however, is comparing the pace between a team's starters and their bench units. In doing so, we find the following:



For the most part, bench units tend to actually speed things up a little bit, particularly for the Clippers, Grizzlies and Spurs. That provides a bit more incentive to play second-unit guys against those teams, whereas there's a bit less incentive to play your reserves against Orlando, Milwaukee or Golden State. Overall, though, the difference of a handful of possessions doesn't really tip the scales for fantasy purposes. One of the fun things about statistics...you never know what an analysis will reveal (or not) until you do it.



Defensive Rating/Offensive Rating (aka Defensive Efficiency/Offensive Efficiency)




Defensive Rating: The number of points allowed per 100 possessions by a team. For a player, it is the number of points per 100 possessions that the team allows while that individual player is on the court.


Offensive Rating: The number of points scored per 100 possessions by a team. For a player, it is the number of points per 100 possessions that the team scores while that individual player is on the court.



Example: The Warriors are averaging 118.9 points per 100 possessions with Stephen Curry on the court this season, which is easily the highest Offensive Rating in the NBA. Defensively, the Spurs have allowed just 94.9 points per 100 possessions while Dejounte Murray has been on the court, giving him the league's best Defensive Rating.


On a team basis, we can see that among 5-man lineups with at least 100 minutes together, easily the stingiest has been the Mavericks with J.J. Barea, Yogi Ferrell, Devin Harris, Dwight Powell and Dirk Nowitzki. Never in a million guesses would I have come up with that five-man unit. Go figure.


Def/Off Ratings can be misleading on a player-specific basis, however, since role players often have inflated Offensive Ratings simply by virtue of playing alongside superstars. There's a reason Shaun Livingston ranks No. 9 overall in ORtg, and it's not because he's such a dynamic offensive threat. Ditto for P.J. Tucker at No. 10, or my personal favorite this season, OG Anunoby at No. 6 (115.6 points per 100 possessions).


Fantasy Utility: Mike Gallagher and I thoroughly went over the fantasy implications of Offensive/Defensive Ratings in the latest Rotoworld hoops podcast, which you can check out here. We also discuss a ton of other advanced stats, so give it a listen if this topic interests you. As mentioned on the podcast, Off/Def Ratings are best used for 1) determining which players are thriving in their assigned role, and whose minutes should therefore be safe, and 2) identifying the easiest or hardest matchups. For example, the second-stingiest 5-man unit has been Goran Dragic, Josh Richardson, Dion Waiters, Justise Winslow and Hassan Whiteside. Dragic, Winslow and Whiteside are all banged up right now, but when that unit is healthy you might want to avoid them when possible.



Net Rating


Definition: Measures a team's point differential per 100 possessions. On player level this statistic is the team's point differential per 100 possessions while he is on court.


Example: Take a player's offensive rating, subtract their defensive rating, and you get their "net rating." Eric Gordon leads the NBA in this metric -- he ranks No. 2 in ORtg (116.9) and No. 10 in DRtg (98.7), for a Net Rating of 18.2. That means Houston has outscored opponents by an average of 18.2 points per 100 possessions while Gordon has been on the court this season.


Fantasy Utility: Net rating basically just distills the information discussed above for Off/Def ratings. It's a quicker way to sum up a player's overall efficacy in their given role -- clearly, Eric Gordon is thriving despite the shift from starter to sixth-man when Chris Paul return.




True Shooting Percentage (TS%) and Effective FG Percentage (eFG%)




True Shooting Percentage: A shooting percentage that factors in the value of 3-point field goals and free throws, in addition to conventional 2-point field goals.


Effective FG Percentage: A shooting percentage that factors in the value of 3-point field goals being 1.5 times more valuable than made 2-point field goals.


Example: The formula for eFG% is simple: Field Goals Made + (3-pointers x 0.5) / Field Goal attempts. If Robert Covington shoots 6-of-16 from the field with four 3-pointers, his standard FG% would be 37.5%. By weighting the impact of his 3-pointers, however, that jumps to 50.0 eFG%, which is a more accurate representation of his actual efficiency.


Robert Covington: 6-of-16 FGs with four 3-pointers = 16 points on 16 shots = 50% Effective FG%

Jusuf Nurkic: 8-of-16 FGs with zero 3-pointers = 16 points on 16 shots = 50% Effective FG%



For TS%, we just add the impact of free throws to the equation: Points /  [2 x (Field Goals Attempted+0.44*Free Throws Attempted)]. To illustrate the difference, let's modify the scoring lines given above to include free throws.


Robert Covington: 6-of-16 FGs, 5-of-5 FTs with four 3-pointers = 57.7% True Shooting

Jusuf Nurkic: 8-of-16 shooting, 4-of-8 FTs with zero 3-pointers = 51.2% True Shooting


True Shooting provides the fullest picture of a player's actual offensive efficiency. Effective Field Goal % isn't quite as all-encompassing, in that it leaves out free throws, but it's still better than the bare-bones FG% we're all used to seeing.


Fantasy Utility: I've never played in a fantasy league that uses eFG% or TS% as a category. I'm also not sure I'd want to -- although they are indisputably more accurate for real-world purposes, including them in fantasy is problematic. By weighting 3-pointers and free throws into one number (eFG% or TS%), you're creating redundancies if your league already counts 3-pointers made or 3PT%, free throws made or FT%. And if you eliminate 3-pointers made, for instance, to account for it's impact in TS%, you've now devalued their overall fantasy impact. So...for fantasy purposes, I'm not convinced it really benefits us much to focus on these advanced percentages. If you feel differently, let me know! I can always be reached via email or on Twitter @Knaus_RW.



Points Per Possession


Definition: The number of points a player or team scores per possession.


Example: Among players with at least 1.0 post-up per game, Rondae Hollis-Jefferson has been the most effective with 1.28 points per possession. Joel Embiid is scoring a solid 0.99 points per possession on his post-ups, and he also leads the league (by a lot) with 11.0 post-up possessions per game.


Knowing that Embiid is very reliant on post-ups, we can quickly cross-reference how many PPP teams are allowing to that play type (viewable right here). The Spurs are allowing a mere 0.71 PPP against post-up plays this season, and the Warriors, Bucks and Rockets have also been stingy. If you're thinking about Embiid in DFS leagues, therefore, you'll probably want to fade him in those matchups.


Fantasy Utility: PPP is a quick-glance method for establishing a player's strengths and weaknesses. As noted above, you can determine the PPP allowed by opponents to determine which teams are best to target and avoid. For more details about this method, check out my column "Team Matchups vs. Positions."


That's all I have time for this week! I hope it's helped to clarify terminology for those of you unfamiliar with advanced stats, while providing food for thought if you're already savvy to things like usage rates and TS%. As usual, please send me any insights or questions you might have. Good luck this week!


Despite residing in Portland, Maine, Ryan Knaus remains a heartbroken Sonics fan who longs for the days of Shawn Kemp and Xavier McDaniel. He has written for Rotoworld.com since 2007. You can follow him on Twitter.
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