The impact of wrist fractures on long-term basketball performance

Key points

1. 01Players' traditional stats (points, assists, rebounds per game) were similar before and after injury, but their advanced efficiency measure (win shares) fell significantly.
2. 02Win shares dropped from a mean of 24.3 before injury to 9.6 after return (p < 0.032).
3. 03Higher points per game and higher win shares before injury independently predicted higher win shares after return to play.
4. 04Surgery versus no surgery made little overall difference, except players treated operatively lost more rebounds per game.
5. 05Player position and age were not linked to how players performed after returning.

How it was conducted

Design

Retrospective review of publicly available NBA player records (2002 to 2016), searched September 2019

Participants

31 NBA players who fractured one or more wrist joint bones and had at least one season before and more than one season after injury

Groups

Compared each player's pre-injury versus post-injury performance, and compared operative versus nonoperative and backcourt versus frontcourt players

Primary outcome

Change in performance metrics including points, rebounds, assists, minutes per game, and win shares

Analysis

Student's t-test, chi-squared and Fisher's exact test, plus backwards stepwise multivariate regression

What they found

• Win shares fell from a mean of 24.3 +/- 31.5 before injury to 9.6 +/- 19.6 after return (p < 0.032).
• Points per game (10.6 +/- 6.4 vs 9.2 +/- 6.2, p = 0.403), assists per game (2.3 +/- 2.1 vs 2.3 +/- 2.3, p = 0.993), rebounds per game (4.2 +/- 2.9 vs 3.3 +/- 2.1, p = 0.211), and minutes per game (23.9 +/- 9.6 vs 21.5 +/- 9.2, p = 0.309) did not differ significantly.
• Operatively managed players lost more rebounds per game (mean decline -2.2 +/- 2.0) than nonoperatively managed players (-0.5 +/- 1.9) (p < 0.026).
• Operatively managed players showed a larger win-share decline (-22.6 +/- 34.7) than nonoperative players (-3.2 +/- 22.8), approaching but not reaching significance (p < 0.081).
• Higher pre-injury points per game (standardized beta 0.71; 95% CI 1.2 to 8.5, p < 0.011) and higher pre-injury win shares (beta 1.0; 95% CI 1.4 to 9.5, p < 0.001) independently predicted higher win shares after return.
• The most common fractures were scaphoid (38.7%) and distal radius (35.5%); operative management was used in 48.4% of players.
• Mean age was 26.2 +/- 4.3 years, with 5.2 +/- 3.6 seasons played before injury and 4.1 +/- 3.1 seasons after return.

Limitations

• Retrospective review of a small cohort of 31 players, with no control group of uninjured players.
• The method of identifying players from public databases is not validated and may have missed eligible players.
• The specific bone broken was often unknown or unverified because injury details were not publicly disclosed, limiting clinical context.
• Findings come from elite athletes with top-tier care and conditioning, so they may not generalize to other populations.

Why it matters

For patients

A wrist fracture may let an athlete return and keep scoring at similar numbers, but their overall efficiency and value can stay below their pre-injury level.

For clinicians

Counsel high-level athletes that traditional box-score stats may recover while advanced efficiency measures lag, and that pre-injury performance is the strongest predictor of post-return contribution.

For readers

This is the first study to examine long-term basketball performance after wrist joint fractures, but its small, uncontrolled design means the findings are preliminary.