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Across 506 NBA players with at least 10 logged games in rebounds, this page measures 28181 games in total. The median player in that field averages 3.3 rebounds. The line closest to a coin flip sits at 2.5 for the median of the 506 players whose distribution supports one — half the field is more often over it, half more often under. The deepest sample here is Julian Champagnie, with 105 logged games. Of the 480 players whose spread can be measured, 9 cluster tightly around their average, 267 vary moderately and 204 swing widely. 506 of them have at least three games home and away, so the venue gap below is measured rather than assumed. Every figure is counted from official box scores and describes games already played. It is not a projection, and on its own it says nothing about whether any price on offer is worth taking.
Each player's own most balanced threshold — the half-point line he has finished above in closest to half his logged games — measured from his distribution rather than read off a book. Deepest sample first, not best to worst. The 40 deepest samples of 506 measured; the figures above this table are over all 506.
| Player | Club | Logged games | Average | Balanced line | Hit rate there |
|---|---|---|---|---|---|
| Julian Champagnie | Spurs | 105 | 5.8 rebounds | Over 5.5 | 51 of 105 (49%) |
| Keldon Johnson | Spurs | 105 | 4.9 rebounds | Over 4.5 | 57 of 105 (54%) |
| Mikal Bridges | Knicks | 101 | 3.7 rebounds | Over 3.5 | 51 of 101 (50%) |
| Harrison Barnes | Spurs | 97 | 2.5 rebounds | Over 2.5 | 43 of 97 (44%) |
| Karl-Anthony Towns | Knicks | 94 | 11.6 rebounds | Over 11.5 | 49 of 94 (52%) |
| Carter Bryant | Spurs | 93 | 2.3 rebounds | Over 1.5 | 55 of 93 (59%) |
| De'Aaron Fox | Spurs | 93 | 3.8 rebounds | Over 3.5 | 48 of 93 (52%) |
| Jalen Brunson | Knicks | 93 | 3.3 rebounds | Over 3.5 | 38 of 93 (41%) |
| Javonte Green | Pistons | 93 | 2.7 rebounds | Over 2.5 | 45 of 93 (48%) |
| Cason Wallace | Thunder | 92 | 3.2 rebounds | Over 3.5 | 41 of 92 (45%) |
| Dylan Harper | Spurs | 92 | 3.9 rebounds | Over 3.5 | 49 of 92 (53%) |
| Julius Randle | Timberwolves | 91 | 6.8 rebounds | Over 6.5 | 53 of 91 (58%) |
| Luke Kornet | Spurs | 91 | 5.5 rebounds | Over 5.5 | 44 of 91 (48%) |
| Stephon Castle | Spurs | 91 | 5.3 rebounds | Over 5.5 | 38 of 91 (42%) |
| Devin Vassell | Spurs | 90 | 4.3 rebounds | Over 4.5 | 39 of 90 (43%) |
| Duncan Robinson | Pistons | 90 | 2.6 rebounds | Over 2.5 | 45 of 90 (50%) |
| Jake LaRavia | Lakers | 90 | 3.8 rebounds | Over 3.5 | 47 of 90 (52%) |
| Jordan Clarkson | Knicks | 90 | 1.8 rebounds | Over 1.5 | 46 of 90 (51%) |
| Desmond Bane | Magic | 89 | 4.2 rebounds | Over 4.5 | 37 of 89 (42%) |
| Jamal Shead | Raptors | 89 | 1.8 rebounds | Over 1.5 | 42 of 89 (47%) |
| Naz Reid | Timberwolves | 89 | 6.3 rebounds | Over 6.5 | 42 of 89 (47%) |
| Bruce Brown | Nuggets | 88 | 3.8 rebounds | Over 3.5 | 41 of 88 (47%) |
| Donovan Mitchell | Cavaliers | 88 | 4.6 rebounds | Over 4.5 | 42 of 88 (48%) |
| James Harden | Cavaliers | 88 | 4.9 rebounds | Over 4.5 | 49 of 88 (56%) |
| Luke Kennard | Lakers | 88 | 2.5 rebounds | Over 2.5 | 36 of 88 (41%) |
| Reed Sheppard | Rockets | 88 | 2.8 rebounds | Over 2.5 | 43 of 88 (49%) |
| Rudy Gobert | Timberwolves | 88 | 11.2 rebounds | Over 11.5 | 48 of 88 (55%) |
| Ausar Thompson | Pistons | 87 | 6.1 rebounds | Over 6.5 | 40 of 87 (46%) |
| Dennis Schröder | Cavaliers | 87 | 2.5 rebounds | Over 2.5 | 36 of 87 (41%) |
| Jose Alvarado | Knicks | 87 | 2.3 rebounds | Over 1.5 | 53 of 87 (61%) |
| Ronald Holland II | Pistons | 87 | 3.8 rebounds | Over 3.5 | 45 of 87 (52%) |
| Sandro Mamukelashvili | Raptors | 87 | 4.9 rebounds | Over 4.5 | 43 of 87 (49%) |
| Scottie Barnes | Raptors | 87 | 7.4 rebounds | Over 7.5 | 39 of 87 (45%) |
| Toumani Camara | Trail Blazers | 87 | 5.1 rebounds | Over 4.5 | 48 of 87 (55%) |
| Daniss Jenkins | Pistons | 86 | 2.4 rebounds | Over 1.5 | 50 of 86 (58%) |
| Donte DiVincenzo | Timberwolves | 86 | 4.1 rebounds | Over 4.5 | 33 of 86 (38%) |
| Oso Ighodaro | Suns | 86 | 5.2 rebounds | Over 4.5 | 48 of 86 (56%) |
| Payton Pritchard | Celtics | 86 | 3.9 rebounds | Over 3.5 | 48 of 86 (56%) |
| Quentin Grimes | 76ers | 86 | 3.5 rebounds | Over 3.5 | 37 of 86 (43%) |
| Tim Hardaway Jr. | Nuggets | 86 | 2.6 rebounds | Over 2.5 | 40 of 86 (47%) |
Standard deviation in the market’s own units, and the same figure as a share of the player’s average so it means the same thing in points as in passing yards. A narrow spread means the average is close to what a typical game actually looked like; it says nothing about what the next one will look like.
| Player | Club | Logged games | Average | Standard deviation | Spread as % of average |
|---|---|---|---|---|---|
| Nikola Jokić | Nuggets | 71 | 12.9 rebounds | 3.7 | 29% |
| Karl-Anthony Towns | Knicks | 94 | 11.6 rebounds | 3.7 | 32% |
| Domantas Sabonis | Kings | 19 | 11.4 rebounds | 3.7 | 32% |
| Rudy Gobert | Timberwolves | 88 | 11.2 rebounds | 3.7 | 33% |
| Jalen Johnson | Hawks | 78 | 10.1 rebounds | 3.3 | 33% |
| Bam Adebayo | Heat | 73 | 10.0 rebounds | 3.3 | 33% |
| Steven Adams | Rockets | 32 | 8.6 rebounds | 2.8 | 33% |
| Donovan Clingan | Trail Blazers | 82 | 11.4 rebounds | 3.9 | 34% |
| Santi Aldama | Grizzlies | 43 | 6.7 rebounds | 2.2 | 34% |
| Victor Wembanyama | Spurs | 86 | 11.3 rebounds | 4.0 | 35% |
The other end of the same measurement. A wide spread means the average describes the middle of a broad range rather than a typical night, which is worth knowing before reading anything into that average.
| Player | Club | Logged games | Average | Standard deviation | Spread as % of average |
|---|---|---|---|---|---|
| JD Davison | Rockets | 30 | 1.2 rebounds | 2.2 | 182% |
| Isaiah Crawford | Rockets | 14 | 1.1 rebounds | 1.8 | 158% |
| Tyson Etienne | Nets | 24 | 1.1 rebounds | 1.7 | 150% |
| Tyrese Proctor | Cavaliers | 54 | 1.2 rebounds | 1.8 | 148% |
| Kevin McCullar Jr. | Knicks | 21 | 1.3 rebounds | 2.0 | 147% |
| Ron Harper Jr. | Celtics | 35 | 1.5 rebounds | 2.1 | 141% |
| Xavier Tillman | Hornets | 30 | 1.4 rebounds | 2.0 | 141% |
| Adou Thiero | Lakers | 31 | 1.3 rebounds | 1.8 | 137% |
| Asa Newell | Hawks | 46 | 2.1 rebounds | 2.7 | 130% |
| Jonathan Mogbo | Raptors | 43 | 1.6 rebounds | 2.0 | 126% |
Both averages are over the games actually played at each venue, and the game count for each is in the cell beside it. A gap measured over a handful of games either way is one you cannot distinguish from noise — this table prints the denominators so you can tell which is which. Three games a side is the floor for appearing here at all.
| Player | Club | Home (games) | Away (games) | Gap |
|---|---|---|---|---|
| Zach Edey | Grizzlies | 5.8 (4) | 14.1 (7) | 8.3 away |
| Charles Bassey | Warriors | 5.8 (8) | 2.2 (5) | 3.6 at home |
| Tyler Burton | Grizzlies | 3.1 (8) | 6.3 (4) | 3.2 away |
| Jayson Tatum | Celtics | 11.4 (12) | 8.7 (10) | 2.7 at home |
| Domantas Sabonis | Kings | 10.1 (9) | 12.5 (10) | 2.4 away |
| Dejounte Murray | Pelicans | 4.0 (6) | 6.4 (8) | 2.4 away |
| Bez Mbeng | Jazz | 4.9 (7) | 2.9 (8) | 2.0 at home |
| Dylan Cardwell | Kings | 8.5 (23) | 6.5 (21) | 2.0 at home |
| Jusuf Nurkić | Jazz | 9.5 (22) | 11.4 (19) | 1.9 away |
| Naz Reid | Timberwolves | 7.3 (43) | 5.4 (46) | 1.9 at home |
Last five logged games against the full log, reported only where the gap is more than a tenth of the player’s own average. It is a description of five games that have been played and it is not a forecast of the sixth.
| Player | Club | Last 5 | Full log | Difference |
|---|---|---|---|---|
| Joe Ingles | Timberwolves | 2.4 rebounds | 0.7 over 30 | 243% above |
| Rayan Rupert | Grizzlies | 8.4 rebounds | 2.9 over 64 | 186% above |
| Lachlan Olbrich | Bulls | 8.6 rebounds | 3.0 over 37 | 184% above |
| Duop Reath | Trail Blazers | 3.2 rebounds | 1.2 over 32 | 169% above |
| Tyson Etienne | Nets | 3.0 rebounds | 1.1 over 24 | 167% above |
| Ryan Nembhard | Mavericks | 5.6 rebounds | 2.2 over 60 | 153% above |
| Rob Dillingham | Bulls | 5.0 rebounds | 2.0 over 65 | 148% above |
| Jalen Wilson | Nets | 5.2 rebounds | 2.1 over 54 | 146% above |
| Collin Sexton | Bulls | 5.2 rebounds | 2.3 over 68 | 128% above |
| Jordan Hawkins | Pelicans | 3.8 rebounds | 1.7 over 51 | 120% above |
The same comparison in the other direction, and the same caveat: five games is five games, and a run below a baseline is as often noise as it is a change.
| Player | Club | Last 5 | Full log | Difference |
|---|---|---|---|---|
| Caleb Love | Trail Blazers | 0.0 rebounds | 2.3 over 49 | 100% below |
| Chaz Lanier | Pistons | 0.0 rebounds | 0.6 over 37 | 100% below |
| Blake Wesley | Trail Blazers | 0.0 rebounds | 1.1 over 35 | 100% below |
| Jahmir Young | Heat | 0.0 rebounds | 0.3 over 14 | 100% below |
| Vít Krejčí | Trail Blazers | 0.2 rebounds | 2.2 over 69 | 91% below |
| Gradey Dick | Raptors | 0.2 rebounds | 1.9 over 79 | 89% below |
| Trendon Watford | 76ers | 0.4 rebounds | 3.0 over 60 | 87% below |
| Noah Penda | Magic | 0.4 rebounds | 3.1 over 60 | 87% below |
| Aaron Wiggins | Thunder | 0.4 rebounds | 2.6 over 78 | 85% below |
| Jase Richardson | Magic | 0.2 rebounds | 1.1 over 55 | 83% below |
At the half-point threshold each player has finished above in about half their logged games. It is measured per player from their own distribution rather than read off a sportsbook, which is why it is on this page at all: a posted line moves through the day and this page is rebuilt once, so a number taken from a book would be wrong by morning.
No. Nothing here is ordered by how good a bet it is, and no price is quoted anywhere on the page. The tables are ordered by sample depth, by spread and by the size of a measured gap, because those are the things a game log can actually establish.
The count is printed beside every one of them. A player only appears once they have ten or more logged games in the market, and games they did not play are absent rather than counted as zero, so an average describes games they were actually in.
No. A trend here is a comparison between a player’s last five logged games and their full log, and it is reported only when the gap is large enough to be worth naming. It is a description of what has happened, and history is not a forecast.
What these tables are measuring, explained: how to read a hit rate and what its denominator hides, what an over/under line is and what it is not.
NBA player props and live odds
Odds and lines come from licensed data feeds and refresh on a schedule; hit rates, edges and grades are Parlay Builder’s own calculations.