Case Study 2: Draymond Green and the Limits of Box Score Evaluation

Executive Summary

Draymond Green presents one of the most challenging cases for box score-based player evaluation. Despite modest counting statistics and PER values that suggest an average player, Green has been selected to four All-Star teams, won Defensive Player of the Year, and is widely considered essential to four championship teams. This case study examines how advanced box score metrics fail to capture Green's value, revealing the fundamental limitations of statistics that rely solely on traditional box score data.

Background: The Draymond Paradox

Traditional Statistics Profile

Draymond Green's career averages (through 2023):

By counting statistics, Green appears to be a solid but unspectacular role player.

The Disconnect

Yet Green's resume includes: - 4x NBA Champion (2015, 2017, 2018, 2022) - 4x All-Star (2016, 2017, 2018, 2022) - Defensive Player of the Year (2017) - 2x All-NBA Team - 7x All-Defensive Team

This disconnect between traditional statistics and accolades exemplifies the measurement gap in box score metrics.

Advanced Box Score Metric Analysis

Player Efficiency Rating

PER vs. Perceived Value

Championship Years: - 2015: PER 16.1 (slightly above average) - 2017: PER 16.8 (modestly above average) - 2018: PER 15.4 (barely above average) - 2022: PER 14.1 (below average)

PER suggests Green was an average-to-slightly-above-average player during championship runs. This dramatically contradicts expert evaluation of his importance.

Why PER Fails for Draymond

1. Offensive Bias: Green's defensive dominance isn't captured
2. Scoring Emphasis: Low PPG devastates PER
3. No Gravity Measure: Defensive attention drawn isn't measured
4. No Playmaking Multiplier: Screen assists and hockey assists ignored

Usage Rate: The Low-Usage Star

Green's Usage Rate History

Green's usage rate consistently ranks 4th-5th on his own team, suggesting a minimal offensive role. Yet Warriors' offensive rating was historically higher with Green on court.

The Low-Usage Efficiency Trap

Standard interpretation would classify Green as a low-usage role player. This misses his actual function.

Assist Metrics: Capturing Playmaking

Assist Percentage - A Bright Spot

Green's AST% properly captures his playmaking value - he assists on nearly one-third of teammate field goals while on court.

What AST% Still Misses

1. Screen Assists: Green sets elite screens that lead to scores
2. Hockey Assists: Pass before the pass
3. Defensive Triggers: Steals/blocks leading to transition
4. Offensive Rebounds Leading to Assists: Creates second chances

Example: Green sets screen, Curry's defender switches, Curry drives and kicks to Thompson who scores. Green gets no statistical credit despite initiating the action.

Defensive Metrics: The Critical Gap

Steal and Block Percentages

Green's STL% and BLK% are good but not exceptional - he ranks below historical rim protectors like Gobert. Yet he won DPOY in 2016-17.

The Versatility Factor

What box score metrics miss about Green's defense:

Switching Capability: - Can guard positions 1-5 - No matchup forces lineup change - Enables Warriors' switching schemes

Help Defense: - Elite positioning - Anticipates plays before they develop - Communicates defensive assignments

Rim Protection Without Blocks: - Alters shots through positioning - Forces difficult angles - Opponents shoot worse at rim with Green nearby

On/Off Defensive Evidence

2016-17 DPOY Season:

The Warriors were 8.2 points per 100 possessions better defensively with Green - one of the largest differentials in the league. This value is invisible in PER, Game Score, and similar metrics.

Game Score Analysis

Season Game Score Distribution (2016-17)

Comparing to Other 2017 All-Stars

Green's average Game Score ranked among the lowest All-Stars, yet coaches voted him in based on impact they observed that statistics missed.

The "Death Lineup" Effect

Small-Ball Dominance

The Warriors' "Death Lineup" (Curry-Thompson-Iguodala-Green-Barnes/Durant) was historically dominant:

Green's Role in the Lineup

Green at center enables the lineup because he: 1. Switches everything - No defensive liability 2. Protects the rim - Despite 6'6" height 3. Initiates offense - Acts as point center 4. Spaces floor - Enough shooting threat 5. Covers mistakes - Elite help defense

Without Green, this lineup doesn't exist. His unique skill set is the key that unlocks small-ball dominance. No box score metric captures "enables a historically great lineup."

Comparison to Similar Profiles

"Glue Guys" Throughout History

Green's PER profile most resembles Hall of Famers Rodman and Wallace - players whose value exceeded statistical capture.

The "Championship Contribution" Problem

Advanced box score metrics cannot measure: - Defensive scheme versatility - Clutch defensive stops - Communication/leadership - Lineup enabling - System fit

Green, Rodman, and Wallace all contributed more to winning than their statistics suggested.

Alternative Metrics Better Capture Green

Impact Metrics (Covered in Later Chapters)

These plus-minus-based metrics, which incorporate lineup data rather than individual box score statistics, rate Green as an elite player - aligning with expert assessment.

The Measurement Hierarchy

1. Box Score Metrics (PER, Game Score): Rate Green as average
2. On/Off Metrics: Rate Green as very good
3. Adjusted Plus-Minus (RAPM, RPM): Rate Green as excellent
4. Expert/Coach Evaluation: Rate Green as elite

The more sophisticated the measurement, the higher Green rates.

Analytical Lessons

Lesson 1: Box Score Metrics Have Systematic Blind Spots

Green represents a player archetype - the defensive anchor/facilitator - that box score metrics consistently undervalue.

Lesson 2: Defense Is Poorly Measured

Steals and blocks capture only a fraction of defensive value. Players like Green whose defense comes through positioning, switching, and help are systematically undervalued.

Lesson 3: Enabling Value Is Invisible

Green's ability to unlock lineup possibilities creates enormous value that no box score metric attempts to quantify.

Lesson 4: Usage Rate Context Matters

Low usage is not inherently bad. Green's low usage with positive impact reflects his role optimization, not limited ability.

Lesson 5: Expert Evaluation Has Information Metrics Miss

Coaches and players recognize Green's value because they observe interactions and positioning that statistics cannot capture. This explains All-Star selections despite modest metrics.

The Hall of Fame Question

Statistical Case Against

• Career 8.7 PPG (historically low for HOF)
• Career PER ~15.5 (average)
• No individual scoring titles or milestones
• Limited traditional accolades

Value-Based Case For

• 4 championships as key contributor
• DPOY as ultimate defensive recognition
• Multiple All-NBA/All-Defense selections
• "Enables the greatest offense in NBA history"
• Elite advanced impact metrics

What This Reveals

If Green makes the Hall of Fame (likely), it will demonstrate that value-based evaluation has surpassed box score-based evaluation. His case represents the triumph of impact metrics over traditional statistics.

Conclusions

Draymond Green's career illustrates the fundamental limitations of box score-based advanced metrics:

1. PER dramatically undervalues Green because it cannot capture defensive versatility, help defense, or lineup enabling

2. Game Score fails to register Green's contributions to winning that experts observe directly

3. Usage Rate misclassifies Green as a role player when his actual impact rivals stars

4. Defensive metrics (STL%, BLK%) capture only a fraction of Green's defensive dominance

5. The gap between metrics and accolades reflects genuine measurement limitations, not award voter error

Green's case demonstrates why analysts must move beyond box score metrics to on/off analysis, adjusted plus-minus, and tracking data - topics covered in subsequent chapters.

Discussion Questions

1. Should Hall of Fame voters rely more heavily on impact metrics than traditional statistics?

2. How might box score metrics be redesigned to better capture defensive value?

3. Is Green's impact "real" if it doesn't show in traditional statistics?

4. What additional data collection would help capture "enabling" value like Green provides?

5. How should analysts communicate value that statistics fail to capture?

Data Sources

• NBA.com official statistics
• Basketball-Reference.com
• Cleaning the Glass
• NBA Stats tracking data
• ESPN Stats & Information
• Second Spectrum tracking data