Which NBA Players Are Most Similar to Each Other? Analyzing Their Playstyles

A few months ago, my colleague and fellow writer on this website, Jesús, sent me a video by JimmyHighroller. In it, using statistical data, he tried to answer the question of who the most similar NBA player to LeBron was. After watching it, I was left wanting to conduct a similar analysis on my own — but with the intention of identifying the players across the league who are most alike in terms of how they play, rather than simply comparing their overall skill levels.

Just like Jimmy did in his video, I divided the analysis into 10 distinct categories, each containing several variables to evaluate.

Stature

Measures the player’s physical attributes like age, height, and weight:
AGE, HEIGHT_METERS, WEIGHT, PLAYER_POSITION

Usage_and_Creation

Evaluates metrics related to pace and ball usage:
USG_PCT, POSS, PACE, MIN

Shooting_tendencies

Focuses on the areas of the court from which a player tends to shoot:
FTA, Mid-Range_FGA, Above_the_Break_3_FGA, Corner_3_FGA, Restricted_Area_FGA, In_The_Paint_(Non-RA)_FGA

Portability

Measures how well a player fits into different offensive systems without needing a central role:
MIN, PIE, LOOSE_BALLS_RECOVERED, USG_PCT, SCREEN_ASSISTS, BOX_OUTS

Passing

Looks at the types and frequency of passes and assists:
AST, AST_PCT, AST_TO, AST_RATIO, SCREEN_ASSISTS, SCREEN_AST_PTS

Defense

Evaluates key defensive statistics:
STL, BLK, DEF_RATING, DREB, DEFLECTIONS, CONTESTED_SHOTS, CHARGES_DRAWN, DEF_LOOSE_BALLS_RECOVERED

Athleticism

Focuses on physical defensive metrics:
STL, BLK, DEFLECTIONS, LOOSE_BALLS_RECOVERED, CONTESTED_SHOTS, PTS_FB

Dominance

Captures metrics related to on-court dominance, such as double-doubles or triple-doubles:
PTS, REB, PLUS_MINUS, NET_RATING, PIE, DD2, TD3

Shooting_ability

Studies shooting accuracy from different areas of the floor:
FG_PCT, FG3_PCT, FT_PCT, TS_PCT, EFG_PCT, Mid-Range_FG_PCT, Corner_3_FG_PCT

Playstyle

Groups stats that describe a player’s style of play — what type of actions they excel in, where they’re most active on the court, and their general role:
AST_PCT, REB_PCT, USG_PCT, PACE, E_TOV_PCT, OREB_PCT, DREB_PCT

To focus the analysis on the most relevant players, I narrowed it down to the top 100 in the league. For each category, I evaluated player similarity by comparing where each player ranked in the league for every variable. The absolute differences in rank between two players were calculated for each variable, and a similarity percentage was derived. These were then averaged to generate a category-level similarity score, and finally a global similarity percentage for every pair of players.

The resulting table features all kinds of pairings — from guards known for their perimeter shooting like Klay Thompson, Bogdan Bogdanovic, and Spencer Dinwiddie, to big men with good range like Myles Turner and Brook Lopez. We also see more traditional interior players like Andre Drummond paired with Jusuf Nurkic, or Alex Len with Jock Landale.

Among similar guards, we find intriguing duos like Jaylen Brown with Franz Wagner or Kyrie Irving with Jamal Murray. The analysis also finds matches among defensively-oriented players, such as Kentavious Caldwell-Pope and Jrue Holiday, or Rudy Gobert with Jarrett Allen. In general, the data reveals a variety of player types with surprisingly high stylistic overlap.

Out of curiosity, I also looked at the opposite end — the player pairs that the algorithm identified as most dissimilar. Unsurprisingly, the largest gaps often appeared in combinations of point guards and traditional centers. Think of setups like pass-first or high-usage guards paired with bigs who rarely leave the paint, such as Rudy Gobert or Andre Drummond.

Below, I’ve included the table with the most contrasting pairs in terms of playstyle.

Which player combinations did you expect to see in the top or bottom tables? Did any of the results surprise you?
Thanks so much for reading!