Talent Badges

If you’ve played NBA 2K before, you may be familiar with their badge system. Players, based on talent in specific key skill sets, are awarded badges of different levels that then boost performance in-game. Our goal is slightly different, being rather to describe standout performance in those skill areas.

We at BBall Index love that concept, but wanted to give it another shot with data. A big reason for that is due to the belief that while the concept from 2K is cool, the execution is a challenge.

Here are a few challenges with 2K’s approach:

  • Allocating Equal Attention – it’s hard to pay all 30 teams attention, so bigger market teams tend to get more badges. Why does RJ Barrett have SEVENTEEN badges? Because it’s likely beneficial for 2K to give Knick fans hope for players dubbed as future stats. Go see for yourself the badge counts by teams and how they relate to market size. This challenge is inherent to an entertainment product.
  • Changing Performance – It’s incredibly hard to keep up with over 500 players a season. Performance ebbs and flows throughout a year, and because of that, it’s easy for badges in 2K to rely on past or early-season performance that’s no longer representative of current performance.
  • Relying on the eye test and basic stats – reputation, eye test, and NBA.com/stats play type leaderboards for efficiency or possession volume, which have been shared to be methodology 2K relies upon, make it difficult to analyze all players in a fair way that’s also complex enough to capture what we believe should go into badge allocations.

Our approach to address these challenges:

  • Automation Enabling Equality – RJ Barrett fans beware, our formulas will make him earn every badge he has (currently, zero). If you’re a Grizzlies fan or Detroit fan, you’ll likely reap the benefits of this more than a Knicks or Laker fan. But the process will be fair, is transparent, and will continue to pay equal attention to every player, regardless of their national exposure, brand, or recognition from media.
  • Dynamic Badge Calculations – Our stats don’t need a player to either grow a reputation in a skill area over time or need pressure from fans to catch up. The math looks at everyone on all 30 teams continuously, and should identify players as or even before they develop their reputations for their critical skills. Our analysis of badge holders should be dynamic. Badge determinations with our approach essentially become automated, with badges recalculating regularly.
  • Leveraging Massive Databases – If you’ve seen our Player Profiles, you know we’re serious about our data, and have quite a bit of it. Combining several metrics cultivated from different source data or aggregated from various sources enables more complex and nuanced analysis.

The end goal? Fair, automatically recalculating badges that accurately identify players possessing key skills that contribute to winning. I’d love for these badges to identify high performing specialists and drive media analysis, helping to set reputations rather than need to lag behind them.

As an aside, I hope RJ Barrett develops into the type of player that can accrue 17 badges. But he’s not there yet, and it’d be unfair to other players to recognize players today for what we hope a player turns into in a few years.

Our approach comes with its own limitations.

We can only measure what can be measured with data. So, for example, you likely won’t see an acrobat badge calculated anytime soon. A handful of other badges fall into the category of only being attributable from film analysis. But I believe the tradeoff is well worth it.

With that out of the way, let’s talk badges.

First, I want to acknowledge that our badge creation is far from complete. We currently have 22 badges completed. The current breakdown is also skewed toward offense, with 13 being related to offense, 6 being analysis of defensive performance, and 3 being neither offense nor defense specific.

Regarding levels of recognition, we currently have Gold, Silver, and Bronze badges allocated. Hall of Fame badges will be added once we build out a larger sample of years, so that the proper context can be captured. Without that context, we don’t know if none, one, two, or ten of the top players in a particular badge are having that caliber of performance.

Badge Points

“Badge Points” is a concept that we also utilize to aid analysis. Our point system follows the olympic model:

Calculation Methodology

When calculating badges, we often look at 3 categories for data points:

  • Prerequisites: data point(s) used to filter out players that don’t match the intended job/type of player analyzed.
  • Differentiators: data point(s) used to rank eligible players meeting prerequisites and allocate badges.
  • Small Sample Eliminators: additional data point(s) used to remove players from consideration who may have outlier performances on small samples. Future improvements will be to replace this method with a padding method to the differentiator stats to, in essence, regress small samples towards the mean.

Without further ado, here are our current badges:

Badges for Offense

Transition Phenom – The idea behind this badge is to capture who is having the highest scoring impact in transition.

  • Prerequisite: none
  • Differentiator: Transition Points Over Expectation (POE), using (Efficiency – Expected Efficiency) * Volume to derive values. Expectations are set based on league average for the play type.
  • Small Sample Eliminator: Transition POE accounts for this
  • Planned Revisions: incorporate passing in transition for a more holistic assessment

One-Man Wrecking Crew – This badge seeks to capture players with the highest rates of unassisted scoring

  • Prerequisite: B+ Scoring Possessions per game minimum (want to find high scorers)
  • Differentiator: Percentage of points unassisted
  • Small Sample Eliminator: none
  • Planned Revisions: incorporate efficiency in calculations

Microwave – This badge identifies players bringing instant offense off the bench

  • Prerequisite: Games Started percentage below 25% (want to look at bench players)
  • Differentiator: Points per Minute
  • Small Sample Eliminator: D Minutes per Game minimum
  • Planned Revisions: incorporate efficiency in calculations

Playmaking Whiz – This badge seeks to identify players with the ability to generate high value scoring opportunities for teammates at high volume

  • Prerequisites: B- RA Assist Pts / 75 Poss and B- Box Creation minimums (want to identify players creating well for their roles and creating often)
  • Differentiator: Average z-scores of High Value Assist +/- & High Value Assists per 75 possessions
  • Small Sample Eliminator: C Potential Assists minimum
  • Planned Revisions: none

Unpluckable – This badge identifies Guards and Wings with high on-ball usage with a low turnover rate from on-ball steals relative to the time they possess the ball

  • Prerequisite: Player must be a Guard or Wing
  • Differentiator: Average z-scores of Role Adjusted Turnover Rate from On-Ball Steals and Time of Possession per game
  • Small Sample Eliminator: B+ Time of Possession/Game
  • Planned Revisions: none

Tear Dropper – This badge identifies players who are prolific and efficient shooting

  • Prerequisite: None
  • Differentiator: Points Over Expectation on Floaters
  • Small Sample Eliminator: Floater POE accounts for this
  • Planned Revisions: none

Difficult Shots – Capturing high rate and ability scoring from pull up jumpers

  • Prerequisites: B- Minutes Share and B- Scoring Possessions per Game minimums
  • Differentiator: Blend of Pull Up 3PT %, Pull Up 2PT%, and Pull Up to C&S Ratio
  • Small Sample Eliminator: 50+ Pull Up 2PA, 50+ Pull Up 3PA
  • Planned Revisions: none

Corner Specialist – This badge identifies players taking a high rate and shooting a high percentage on corner 3-pointers

  • Prerequisites: B- Corner 3PT% minimum
  • Differentiator: Blend of Corner 3PT% and Corner 3s per 75 Possessions
  • Small Sample Eliminator: C 3PA minimum
  • Planned Revisions: none

Catch & Shoot – This badge identifies players taking a high rate and shooting a high percentage on catch and shoot 3-pointers

  • Prerequisites: B- Catch & Shoot 3PT% minimum
  • Differentiator: Blend of Catch & Shoot 3PT% and Catch & Shoot 3s per 75 Possessions
  • Small Sample Eliminator: C Catch & Shoot 3PA minimum
  • Planned Revisions: none

Pick & Popper – This badge identifies players taking a high rate and shooting a high percentage on pick & pops

  • Prerequisites: None
  • Differentiator: Pick & Pop Points Over Expectation per game
  • Small Sample Eliminator: D- Total Pick & Pop scoring possession volume
  • Planned Revisions: none

Deadeye – This badge identifies players taking highly contested 3s and shoots a high percentage

  • Prerequisites: Bottom 20% in 3PT openness
  • Differentiator: 3PT%
  • Small Sample Eliminator: D 3PA minimum
  • Planned Revisions: differentiating by Points Over Expectation on contested and tightly contested 3PT attempts

Giant Slayer – This badge seeks to identify shorter players finishing well at the rim against bigs

  • Prerequisites: C- Adjusted Drives per 75 Possessions and Height < 6’5″
  • Differentiator: FGM at Rim +/-
  • Small Sample Eliminator: C- Shots at Rim minimum
  • Planned Revisions: None

Contact Finisher – This badge seeks to capture players finishing well through contact

  • Prerequisites: None
  • Differentiator: Contact Finish Rate
  • Small Sample Eliminator: C Shooting Foul Volume minimum
  • Planned Revisions: None

Putback Boss – This badge identifies players active on putbacks and effective converting on them

  • Prerequisites: B- Putbacks per 75 Possessions minimum
  • Differentiator: Putback Points Over Expectation
  • Small Sample Eliminator: C Total Putback Possessions minimum
  • Planned Revisions: None

Offensive Rebound Hunter – This badge seeks to identify top offensive rebounding talents

  • Prerequisites: None
  • Differentiator: Blend of Offensive Rebounding Success Rate vs Expected and Offensive Rebounds per 75 Possessions
  • Small Sample Eliminator: C- Offensive Rebound Opportunities
  • Planned Revisions: None

Badges for Defense

Pickpocket – This badge seeks to identify good perimeter defenders whose good on-ball defense results in on-ball steals.

  • Prerequisites: B- Perimeter Defense minimum
  • Differentiator: Loose Ball Steal Rate
  • Small Sample Eliminator: C Loose Ball Steals minimum
  • Planned Revisions: None

Interceptor – This badge seeks to identify good defenders highly active jumping passing lanes.

  • Prerequisites: B- Perimeter Defense minimum
  • Differentiator: Passing Lane Defense Rating (Deflections + Bad Pass Steals per 75 possessions)
  • Small Sample Eliminator: C Total Passing Lane Defense minimum
  • Planned Revisions: None

Rim Protector – This badge identifies players who protect the rim often and impact opponent shooting at the rim

  • Prerequisites: Anchor Big and B- Rim % Contested Minimum
  • Differentiator: Adjusted Rim Points Saved per 36 minutes
  • Small Sample Eliminator: C Total Rim Shots Contested minimum
  • Planned Revisions: None

Intimidator – This badge seeks to identify players defending the rim often and deterring shots at the rim due to their shot blocking and strong interior defense

  • Prerequisites: Big with B- Rim % Contested and B- Blocks/75 Poss minimums
  • Differentiator: Rim Deterrence %
  • Small Sample Eliminator: C Total Rim Shots Contested minimum
  • Planned Revisions: None

Box Out Guru – This badge identifies players with elite box out rates that help their team’s defensive rebounding through those efforts

  • Prerequisites: Defensive Rebounding Positioning Closer than Average, Positive (>0) Real Adjusted Defensive Rebounding Rate
  • Differentiator: Adjusted Box Out Rate
  • Small Sample Eliminator: C- Defensive Rebound Opportunities
  • Planned Revisions: None

Defensive Rebound Vacuum – This badge seeks to identify top defensive rebounding talents

  • Prerequisites: None
  • Differentiator: Defensive Rebounding Success Rate vs Expected, Defensive Rebounds per 75 Possessions
  • Small Sample Eliminator: C- Defensive Rebound Opportunities
  • Planned Revisions: None

Overall Performance Badges

Streaky Badge – This badge identifies players with the lowest game to game consistency regarding impact

  • Prerequisites: C Minutes Share minimum
  • Differentiator: Low Performance Consistency Rating (using per game BPM impact)
  • Small Sample Eliminator: None
  • Planned Revisions: Alter this to look at players with more inconsistency regarding lower performance than general inconsistency

Consistency– This badge identifies players with the highest game to game consistency regarding impact

  • Prerequisites: C Minutes Share minimum
  • Differentiator: High Performance Consistency Rating (using per game BPM impact)
  • Small Sample Eliminator: None
  • Planned Revisions: Alter this to look at players with more inconsistency regarding lack of lower performance than general lack of inconsistency

Nuclear Upside – This badge identifies players with the highest percentage of games where they “go off” and have elite impact

  • Prerequisites: C Minutes Share minimum and >0 BPM
  • Differentiator: Overlap Coefficient of game BPM with League Distribution (looks at percentage of games with performance beyond a normal impact based on league’s distribution)
  • Small Sample Eliminator: None
  • Planned Revisions: None

Badge Tools

In addition to seeing our badges on player profiles, you can find information and interactive tools on our badges in our Current BBall Index Badge document in our Data & Tools package.

Within that document, you can:

  • See a badge matrix that shows every badge for every player
  • Use our Badge Finder tool to quickly pull up all recipients in one place, organized by Gold/Silver/Bronze allocations
  • See badge point counts by team.

Related to that last point, we’ve found badge allocations to vibe well with noted team strengths.

In addition, it turns out there’s a notable relationship between badge allocations and team performance offensively and defensively (to a lesser extent, which should improve as more defensive badges are added). @903coleman on Twitter identified it first here:

Since this is an evolving process, we’re very open to feedback on what should be added and altered. If data exists to measure a key skill, we can likely capture it in badge form. Feel free to share ideas via email (bball.index@gmail.com) or via DM on Twitter (@Tim_NBA).