Part 4 of a series on the NBA’s fading home-court advantage; start with Home Court Advantage Is Fading.
I can show you exactly what happened on the glass, and I cannot tell you why. The single largest driver of the NBA’s home-court decline, on the straight-line breakdown, is rebounding, worth about 30% of it. The turnover gap closing adds nearly as much, another 27%. Close enough that the two trade places: re-draw the seasons and re-run the whole breakdown, and rebounding finishes first 76% of the time, turnovers 21%. (How I Know This Isn’t Made Up has that test in full.) Together they outweigh the more expected suspects, and rebounding plus the half of the turnover fade that isn’t the three-point shift is the part of the story the data can measure but not explain.
The rise in three-point attempts explains close to half of the decline, and The Three-Point Suspect makes that case. Rebounding is the largest piece the three-point boom can’t touch: in games with the same three-point volume, the rebounding advantage keeps fading just as fast.
Shooting was the expected suspect, and it earned its billing. Rebounding wasn’t on most lists at all, yet it carries more of the decline than any other single box score factor, and it is the one the analysis can trace precisely without being able to say what caused it. The ranking of the pieces hasn’t flipped: shooting is still the largest slice of the advantage in the regular season, rebounding next, with foul calls and turnovers filling in the rest; in the playoffs turnovers and rebounding are effectively level, with turnovers nominally ahead. What flips when you ask which piece shrank is that rebounding moves to the front.
What happened: the home rebounding edge disappeared
The home team’s rebounding advantage has shrunk steadily for 40 years, on both sides of the glass. The home advantage on defensive rebounds fell from about +1.6 boards per game in the 1980s to roughly +0.6 today, a drop of about a full board. The home advantage on offensive rebounds fell from about +0.6 to slightly below zero.
Part of that defensive-rebound drop looks as though it ought to be arithmetic rather than home teams rebounding worse. The league scores more efficiently than it did at the start of this record, and the tempting next step is that fewer shots therefore miss, so fewer defensive rebounds are there for anyone to collect. That step does not hold, and an earlier version of this article took it.The efficiency gain is in points per shot, because more of the makes are threes; the share of shots that actually go in went from 49.2% to 47.1%, so it did not rise at all. More shots miss now rather than fewer: about 45 a game per team then, about 47 now. The pool of boards to collect grew, so fewer missed shots cannot explain the home team’s fading rebound count. The cleaner comparison is each team’s share of the offensive rebounds available: how often it gets the miss back, rather than how many misses there were. That share fell leaguewide too, from 33% in the 1980s to 26% today, both teams combined: recovering fewer misses was a leaguewide change.
On that cleaner measure, the gap is clear. In the mid-1980s, home teams converted about 34% of their offensive rebounding chances; away teams converted about 31%. Both rates fell, but the home rate dropped 8 percentage points while the away rate dropped only 5. The two lines converge and cross by 2025–26. The advantage didn’t close because away teams became better offensive rebounders. Home teams lost their edge in recovering misses; the rates do not tell us how hard either side tried. The chart bends upward at the end because both home and away recovery rates have risen in recent seasons, even as the gap between them kept closing.
Why the home rate fell farther is not something this data can answer. The usual explanations are strategic (teams choosing transition defense over second chances) or about the crowd (a home building that once spurred extra glass-crashing had nothing left to amplify once the league-wide retreat took hold). These are plausible explanations, not conclusions this analysis can establish.
📊 How the home rebounding and turnover advantages faded. Left: the raw home-minus-away…
What can the cameras tell us?
The player-tracking cameras in use since 2013–14 let us check the recent rebounding pattern with another measure. The value of the cameras is that they see what the box score can’t, and for this case, that’s box outs. The home advantage in converting offensive-rebound chances slid from a mid-2010s level of about 1.2 percentage points to 0.2 today, while home teams held no measurable box-out advantage and the second-chance-points advantage barely changed. The cameras have only been running since 2013–14, though, and because the three trends were judged together, none of them clears the bar on its own. The offensive-rebound conversion measure points the same way as the longer box-score record; the other panels offer no clear trend. By the time the cameras arrived, much of the 40-year decline had already happened, so this short record cannot explain the full decline.
Neither a recovery rate nor a box-out count measures how hard a team tried to rebound. These figures cannot separate tactical choices, player positioning, and success in contested rebounds.
📊 The modern player-tracking view of the home rebounding advantage (2013–14 on; box-outs…
Turnovers: the same quiet fade, half of it also a mystery
Across the full 40-year span, home teams committed about 0.4 fewer turnovers per game than visitors; that gap has nearly closed. About half of that fade disappears once games are compared at the same three-point rate. One plausible reading is that three-point attempts generate fewer live-ball turnovers than drives and post play, so as both teams moved out the absolute number of turnovers fell league-wide and the home team’s advantage shrank with it; that mechanism is the reading, not a separate test. Part of what is left is road-specific: the road turnover penalty fell from 0.85 to 0.13 per 100 possessions as away turnovers fell faster than home ones. What the data can’t settle is why road teams improved. One plausible reason is better scouting and video preparation: visiting teams handle unfamiliar defensive schemes better than they once did. That fits the pattern, but it isn’t something this data can prove on its own. Together, turnovers account for about 27% of the regular-season decline, nearly matching rebounding.
Both unexplained halves may share a single root. As the analytical tools for shot selection, scouting, and game preparation reached all 30 teams at roughly the same pace, the home team’s old preparation advantage had less room to live. When every team lands on the same approaches regardless of venue, the advantage that came from knowing your own building better has nowhere to go but down. That’s a reasonable story for why both unexplained halves move together, but it’s a guess this data has no way to confirm.
The playoffs point the same way
The postseason leans in the same direction on rebounding. The home rebound-share advantage has fallen by roughly three-quarters there too. But the playoffs run on a fifteenth as many games, so this evidence is consistent with the regular-season story rather than standing on its own. The playoff turnover edge is a different story: its trend is too uncertain to call in either direction. The rebounding direction is clear; the turnover trend is not.
The glass is where the decline is largest and the explanation is thinnest. That gap isn’t a hole in the analysis: it is the finding. The next article turns to the suspects that looked guilty and weren’t, the travel and rest and rule changes with airtight alibis.
Next: The Usual Suspects. Travel, rest, crowd size, and nearly every rule change: the suspects that looked guilty and turn out to have alibis.
Back to the series hub: The Disappearing Home-Court Advantage
How this was made: the writing here is mostly AI/LLMs working from my analysis and direction; the numbers are all Python on public NBA data. Every claim is backed up by data. The data, analysis, and conclusions are trustworthy. The full note is on the series hub.
Data: NBA.com Stats, pulled with the open-source nba_api tool; attendance records from Basketball-Reference.