- Joined
- Oct 24, 2025
- Messages
- 217
- Reaction Score
- 1,539
Over the past 15 years, advanced basketball statisticians have demonstrated that there is a "rubber band effect" in games. This refers to a phenomenon where the distance between two teams' scores tends to narrow, especially when one team holds a large lead. Much like a stretched rubber band that snaps back when released, trailing teams often experience a surge in performance while leading teams may stagnate, resulting in frequent comebacks.
Matthew Goldman and Justin Rao perhaps first quantified the rubber band effect in their 2013 paper, "Live by the Three, Die by the Three? The Price of Risk in the NBA."
Jeremias Engelmann further refined this analysis in 2014. His work demonstrated that the effect is nearly linear: teams down by 20 points score about six more points per 100 possessions than expected, while teams up by 20 score about four fewer.
This effect is attributed to the trailing team's increased effort, higher risk-taking (more 3-point attempts), and shifting focus to their most efficient players. Conversely, teams with large leads often often play more cautiously, use bench players, or lose defensive focus, such as by not "boxing out" for rebounds. Stated psychologically, trailing players are motivated by "loss aversion," taking bolder risks to avoid defeat, while leading players may subconsciously become "lazy" or overly safe.
A corollary of the rubber band effect should be that teams that win by large average MOVs are likely even better than most team efficiency metrics suggest, while teams that lose by large average MOVs are likely even worse. Or should the corollary snap in the other direction?
Matthew Goldman and Justin Rao perhaps first quantified the rubber band effect in their 2013 paper, "Live by the Three, Die by the Three? The Price of Risk in the NBA."
Jeremias Engelmann further refined this analysis in 2014. His work demonstrated that the effect is nearly linear: teams down by 20 points score about six more points per 100 possessions than expected, while teams up by 20 score about four fewer.
This effect is attributed to the trailing team's increased effort, higher risk-taking (more 3-point attempts), and shifting focus to their most efficient players. Conversely, teams with large leads often often play more cautiously, use bench players, or lose defensive focus, such as by not "boxing out" for rebounds. Stated psychologically, trailing players are motivated by "loss aversion," taking bolder risks to avoid defeat, while leading players may subconsciously become "lazy" or overly safe.
A corollary of the rubber band effect should be that teams that win by large average MOVs are likely even better than most team efficiency metrics suggest, while teams that lose by large average MOVs are likely even worse. Or should the corollary snap in the other direction?
