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Across 542 NBA players with at least 10 logged games in rebounds, this page measures 32390 games in total. The median player in that field averages 3.2 rebounds. The line closest to a coin flip sits at 2.5 for the median of the 542 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 118 logged games. Of the 513 players whose spread can be measured, 11 cluster tightly around their average, 276 vary moderately and 226 swing widely. 542 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 542 measured; the figures above this table are over all 542.
| Player | Club | Logged games | Average | Balanced line | Hit rate there |
|---|---|---|---|---|---|
| Julian Champagnie | Spurs | 118 | 5.6 rebounds | Over 5.5 | 55 of 118 (47%) |
| Keldon Johnson | Spurs | 118 | 5.0 rebounds | Over 5.5 | 55 of 118 (47%) |
| Mikal Bridges | Knicks | 113 | 3.6 rebounds | Over 3.5 | 56 of 113 (50%) |
| Harrison Barnes | Spurs | 108 | 2.3 rebounds | Over 1.5 | 61 of 108 (56%) |
| De'Aaron Fox | Spurs | 106 | 3.8 rebounds | Over 3.5 | 55 of 106 (52%) |
| Karl-Anthony Towns | Knicks | 106 | 11.8 rebounds | Over 11.5 | 59 of 106 (56%) |
| Carter Bryant | Spurs | 105 | 2.2 rebounds | Over 1.5 | 57 of 105 (54%) |
| Dylan Harper | Spurs | 105 | 4.1 rebounds | Over 3.5 | 59 of 105 (56%) |
| Jalen Brunson | Knicks | 105 | 3.3 rebounds | Over 3.5 | 42 of 105 (40%) |
| Javonte Green | Pistons | 105 | 2.6 rebounds | Over 2.5 | 50 of 105 (48%) |
| Luke Kornet | Spurs | 104 | 5.4 rebounds | Over 5.5 | 48 of 104 (46%) |
| Stephon Castle | Spurs | 104 | 5.3 rebounds | Over 5.5 | 44 of 104 (42%) |
| Julius Randle | Nets | 103 | 6.8 rebounds | Over 6.5 | 58 of 103 (56%) |
| Desmond Bane | Magic | 102 | 4.2 rebounds | Over 4.5 | 44 of 102 (43%) |
| Duncan Robinson | Pistons | 102 | 2.5 rebounds | Over 2.5 | 49 of 102 (48%) |
| Jake LaRavia | Lakers | 102 | 3.8 rebounds | Over 3.5 | 52 of 102 (51%) |
| Devin Vassell | Spurs | 101 | 4.3 rebounds | Over 3.5 | 59 of 101 (58%) |
| Donovan Mitchell | Cavaliers | 101 | 4.6 rebounds | Over 4.5 | 49 of 101 (49%) |
| Jamal Shead | Raptors | 101 | 1.8 rebounds | Over 1.5 | 50 of 101 (50%) |
| James Harden | Cavaliers | 101 | 4.8 rebounds | Over 4.5 | 56 of 101 (55%) |
| Naz Reid | Hornets | 101 | 6.6 rebounds | Over 6.5 | 49 of 101 (49%) |
| Jordan Clarkson | Knicks | 100 | 1.8 rebounds | Over 1.5 | 50 of 100 (50%) |
| Rudy Gobert | Timberwolves | 100 | 11.2 rebounds | Over 11.5 | 53 of 100 (53%) |
| Sandro Mamukelashvili | Lakers | 100 | 4.9 rebounds | Over 4.5 | 48 of 100 (48%) |
| Toumani Camara | Trail Blazers | 100 | 4.9 rebounds | Over 4.5 | 51 of 100 (51%) |
| Ronald Holland II | Pistons | 99 | 3.8 rebounds | Over 3.5 | 50 of 99 (51%) |
| Victor Wembanyama | Spurs | 99 | 11.4 rebounds | Over 11.5 | 49 of 99 (49%) |
| VJ Edgecombe | 76ers | 99 | 5.8 rebounds | Over 5.5 | 57 of 99 (58%) |
| Wendell Carter Jr. | Magic | 99 | 7.6 rebounds | Over 7.5 | 47 of 99 (47%) |
| Amen Thompson | Rockets | 98 | 7.6 rebounds | Over 7.5 | 51 of 98 (52%) |
| Ausar Thompson | Pistons | 98 | 6.4 rebounds | Over 6.5 | 47 of 98 (48%) |
| Daniss Jenkins | Pistons | 98 | 2.5 rebounds | Over 2.5 | 41 of 98 (42%) |
| Jaden McDaniels | Timberwolves | 98 | 4.7 rebounds | Over 4.5 | 54 of 98 (55%) |
| Luke Kennard | Suns | 98 | 2.3 rebounds | Over 1.5 | 57 of 98 (58%) |
| Payton Pritchard | Celtics | 98 | 3.9 rebounds | Over 3.5 | 53 of 98 (54%) |
| Quentin Grimes | Lakers | 98 | 3.4 rebounds | Over 3.5 | 41 of 98 (42%) |
| Reed Sheppard | Rockets | 98 | 2.6 rebounds | Over 2.5 | 45 of 98 (46%) |
| Collin Gillespie | Suns | 97 | 3.9 rebounds | Over 3.5 | 48 of 97 (49%) |
| Luguentz Dort | Hawks | 97 | 3.4 rebounds | Over 3.5 | 45 of 97 (46%) |
| Nickeil Alexander-Walker | Hawks | 97 | 3.4 rebounds | Over 3.5 | 41 of 97 (42%) |
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 |
|---|---|---|---|---|---|
| Cameron Boozer | Grizzlies | 13 | 9.7 rebounds | 2.1 | 22% |
| Walker Kessler | Lakers | 18 | 10.8 rebounds | 2.7 | 24% |
| Nikola Jokić | Nuggets | 82 | 12.6 rebounds | 3.8 | 30% |
| Darius Acuff Jr. | Kings | 12 | 3.8 rebounds | 1.1 | 30% |
| Karl-Anthony Towns | Knicks | 106 | 11.8 rebounds | 3.7 | 31% |
| Rudy Gobert | Timberwolves | 100 | 11.2 rebounds | 3.7 | 33% |
| Jalen Johnson | Hawks | 88 | 9.9 rebounds | 3.2 | 33% |
| Donovan Clingan | Trail Blazers | 95 | 11.2 rebounds | 3.8 | 33% |
| Bam Adebayo | Heat | 87 | 9.7 rebounds | 3.3 | 34% |
| Anthony Davis | Wizards | 31 | 10.8 rebounds | 3.7 | 34% |
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% |
| Tyson Etienne | Nets | 24 | 1.1 rebounds | 1.7 | 150% |
| Ron Harper Jr. | Celtics | 41 | 1.3 rebounds | 2.0 | 147% |
| Kevin McCullar Jr. | Knicks | 21 | 1.3 rebounds | 2.0 | 147% |
| Alijah Martin | Raptors | 34 | 1.2 rebounds | 1.7 | 140% |
| Xavier Tillman | Hornets | 31 | 1.5 rebounds | 2.0 | 138% |
| Tyrese Proctor | Cavaliers | 67 | 1.7 rebounds | 2.2 | 134% |
| Tyus Jones | Nuggets | 81 | 1.0 rebounds | 1.3 | 126% |
| Cam Christie | Clippers | 60 | 1.3 rebounds | 1.7 | 125% |
| Johni Broome | 76ers | 13 | 1.4 rebounds | 1.7 | 125% |
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 |
|---|---|---|---|---|
| Mo Bamba | Jazz | 3.6 (7) | 8.3 (6) | 4.7 away |
| Zach Edey | Grizzlies | 7.1 (10) | 11.6 (11) | 4.5 away |
| Charles Bassey | Warriors | 6.4 (14) | 2.7 (11) | 3.7 at home |
| Morez Johnson Jr. | Mavericks | 6.2 (6) | 3.0 (6) | 3.2 at home |
| Tyler Burton | Grizzlies | 3.1 (8) | 6.3 (4) | 3.2 away |
| Jayson Tatum | Celtics | 10.3 (16) | 7.4 (17) | 2.9 at home |
| Kyrie Irving | Mavericks | 2.2 (5) | 4.5 (6) | 2.3 away |
| Caleb Wilson | Bulls | 7.5 (4) | 5.3 (6) | 2.2 at home |
| Bez Mbeng | Jazz | 4.9 (7) | 2.9 (8) | 2.0 at home |
| Fred VanVleet | Rockets | 2.3 (7) | 4.3 (4) | 2.0 away |
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 |
| Lachlan Olbrich | Bulls | 8.6 rebounds | 3.0 over 37 | 184% above |
| Jordan McLaughlin | Spurs | 2.4 rebounds | 0.9 over 62 | 176% above |
| Tyson Etienne | Nets | 3.0 rebounds | 1.1 over 24 | 167% above |
| Tyrese Proctor | Cavaliers | 4.4 rebounds | 1.7 over 67 | 166% above |
| Rayan Rupert | 76ers | 7.4 rebounds | 2.9 over 66 | 156% 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 |
| Jamal Cain | Magic | 5.4 rebounds | 2.3 over 60 | 131% above |
| E.J. Liddell | Nets | 5.8 rebounds | 2.7 over 26 | 119% 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 |
|---|---|---|---|---|
| Tre Mann | Wizards | 0.0 rebounds | 1.6 over 59 | 100% below |
| Bronny James | Lakers | 0.0 rebounds | 0.5 over 56 | 100% below |
| Caleb Love | 76ers | 0.0 rebounds | 2.2 over 51 | 100% below |
| Amir Coffey | Suns | 0.0 rebounds | 1.1 over 51 | 100% below |
| Chaz Lanier | Pistons | 0.0 rebounds | 0.6 over 41 | 100% below |
| Jahmir Young | Heat | 0.0 rebounds | 0.3 over 14 | 100% below |
| Moussa Cissé | Mavericks | 0.2 rebounds | 4.8 over 46 | 96% below |
| Noah Penda | Magic | 0.2 rebounds | 3.1 over 61 | 94% below |
| Daeqwon Plowden | Kings | 0.2 rebounds | 2.6 over 41 | 92% below |
| Nick Richards | Heat | 0.4 rebounds | 4.6 over 53 | 91% 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 and grades are Parlay Builder’s own calculations.