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Across 532 NBA players with at least 10 logged games in turnovers, this page measures 32275 games in total. The median player in that field averages 1.0 turnovers. The line closest to a coin flip sits at 0.5 for the median of the 532 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 266 players whose spread can be measured, 0 cluster tightly around their average, 94 vary moderately and 172 swing widely. 532 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 532 measured; the figures above this table are over all 532.
| Player | Club | Logged games | Average | Balanced line | Hit rate there |
|---|---|---|---|---|---|
| Julian Champagnie | Spurs | 118 | 0.8 turnovers | Over 0.5 | 66 of 118 (56%) |
| Keldon Johnson | Spurs | 118 | 0.9 turnovers | Over 0.5 | 73 of 118 (62%) |
| Mikal Bridges | Knicks | 113 | 1.0 turnovers | Over 0.5 | 75 of 113 (66%) |
| Harrison Barnes | Spurs | 108 | 0.6 turnovers | Over 0.5 | 48 of 108 (44%) |
| De'Aaron Fox | Spurs | 106 | 2.2 turnovers | Over 2.5 | 40 of 106 (38%) |
| Karl-Anthony Towns | Knicks | 106 | 2.6 turnovers | Over 2.5 | 51 of 106 (48%) |
| Carter Bryant | Spurs | 105 | 0.5 turnovers | Over 0.5 | 39 of 105 (37%) |
| Dylan Harper | Spurs | 105 | 1.4 turnovers | Over 1.5 | 48 of 105 (46%) |
| Jalen Brunson | Knicks | 105 | 2.4 turnovers | Over 2.5 | 46 of 105 (44%) |
| Javonte Green | Pistons | 105 | 0.5 turnovers | Over 0.5 | 35 of 105 (33%) |
| Luke Kornet | Spurs | 104 | 0.4 turnovers | Over 0.5 | 35 of 104 (34%) |
| Stephon Castle | Spurs | 104 | 3.1 turnovers | Over 2.5 | 59 of 104 (57%) |
| Julius Randle | Nets | 103 | 2.9 turnovers | Over 2.5 | 57 of 103 (55%) |
| Desmond Bane | Magic | 102 | 2.0 turnovers | Over 1.5 | 64 of 102 (63%) |
| Duncan Robinson | Pistons | 102 | 0.8 turnovers | Over 0.5 | 60 of 102 (59%) |
| Jake LaRavia | Lakers | 102 | 1.1 turnovers | Over 1.5 | 33 of 102 (32%) |
| Devin Vassell | Spurs | 101 | 0.9 turnovers | Over 0.5 | 64 of 101 (63%) |
| Donovan Mitchell | Cavaliers | 101 | 2.8 turnovers | Over 2.5 | 57 of 101 (56%) |
| Jamal Shead | Raptors | 101 | 1.5 turnovers | Over 1.5 | 47 of 101 (47%) |
| James Harden | Cavaliers | 101 | 3.6 turnovers | Over 3.5 | 49 of 101 (49%) |
| Naz Reid | Hornets | 101 | 1.7 turnovers | Over 1.5 | 54 of 101 (53%) |
| Jordan Clarkson | Knicks | 100 | 0.8 turnovers | Over 0.5 | 57 of 100 (57%) |
| Rudy Gobert | Timberwolves | 100 | 1.4 turnovers | Over 1.5 | 41 of 100 (41%) |
| Sandro Mamukelashvili | Lakers | 100 | 0.8 turnovers | Over 0.5 | 56 of 100 (56%) |
| Toumani Camara | Trail Blazers | 100 | 1.7 turnovers | Over 1.5 | 49 of 100 (49%) |
| Ronald Holland II | Pistons | 99 | 1.1 turnovers | Over 0.5 | 63 of 99 (64%) |
| Victor Wembanyama | Spurs | 99 | 2.4 turnovers | Over 2.5 | 43 of 99 (43%) |
| VJ Edgecombe | 76ers | 99 | 1.7 turnovers | Over 1.5 | 51 of 99 (52%) |
| Wendell Carter Jr. | Magic | 99 | 1.3 turnovers | Over 1.5 | 40 of 99 (40%) |
| Amen Thompson | Rockets | 98 | 2.3 turnovers | Over 2.5 | 44 of 98 (45%) |
| Ausar Thompson | Pistons | 98 | 1.6 turnovers | Over 1.5 | 48 of 98 (49%) |
| Daniss Jenkins | Pistons | 98 | 1.4 turnovers | Over 1.5 | 35 of 98 (36%) |
| Jaden McDaniels | Timberwolves | 98 | 1.8 turnovers | Over 1.5 | 59 of 98 (60%) |
| Luke Kennard | Suns | 98 | 0.8 turnovers | Over 0.5 | 53 of 98 (54%) |
| Payton Pritchard | Celtics | 98 | 1.3 turnovers | Over 1.5 | 36 of 98 (37%) |
| Quentin Grimes | Lakers | 98 | 1.6 turnovers | Over 1.5 | 42 of 98 (43%) |
| Reed Sheppard | Rockets | 98 | 1.5 turnovers | Over 1.5 | 43 of 98 (44%) |
| Collin Gillespie | Suns | 97 | 1.5 turnovers | Over 1.5 | 46 of 97 (47%) |
| Luguentz Dort | Hawks | 97 | 0.7 turnovers | Over 0.5 | 53 of 97 (55%) |
| Nickeil Alexander-Walker | Hawks | 97 | 2.1 turnovers | Over 1.5 | 59 of 97 (61%) |
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 |
|---|---|---|---|---|---|
| Darius Acuff Jr. | Kings | 12 | 3.7 turnovers | 1.3 | 36% |
| Jalen Johnson | Hawks | 88 | 3.3 turnovers | 1.5 | 46% |
| Deni Avdija | Trail Blazers | 84 | 3.7 turnovers | 1.7 | 46% |
| Jalen Suggs | Magic | 70 | 2.7 turnovers | 1.3 | 48% |
| Giannis Antetokounmpo | Heat | 49 | 3.2 turnovers | 1.6 | 49% |
| Josh Giddey | Bulls | 66 | 3.5 turnovers | 1.7 | 49% |
| Luka Dončić | Lakers | 75 | 4.1 turnovers | 2.0 | 49% |
| Jaylen Brown | 76ers | 90 | 3.5 turnovers | 1.7 | 50% |
| Russell Westbrook | Kings | 64 | 3.3 turnovers | 1.6 | 50% |
| James Harden | Cavaliers | 101 | 3.6 turnovers | 1.9 | 51% |
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 |
|---|---|---|---|---|---|
| KJ Simpson | Nuggets | 20 | 1.3 turnovers | 1.8 | 143% |
| Nikola Topić | Thunder | 20 | 1.4 turnovers | 2.0 | 140% |
| Ousmane Dieng | Bucks | 67 | 1.1 turnovers | 1.6 | 138% |
| Jahmai Mashack | Grizzlies | 35 | 1.4 turnovers | 2.0 | 137% |
| Mario Hezonja | Cavaliers | 14 | 1.0 turnovers | 1.3 | 131% |
| Cody Williams | Timberwolves | 74 | 1.0 turnovers | 1.3 | 126% |
| Nikola Jović | Heat | 55 | 1.2 turnovers | 1.5 | 117% |
| Jalen Slawson | Pacers | 24 | 1.1 turnovers | 1.3 | 113% |
| Taurean Prince | Pistons | 29 | 1.1 turnovers | 1.2 | 112% |
| Kentavious Caldwell-Pope | 76ers | 64 | 1.0 turnovers | 1.2 | 112% |
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 |
|---|---|---|---|---|
| Caleb Wilson | Bulls | 1.5 (4) | 3.5 (6) | 2.0 away |
| Damian Lillard | Trail Blazers | 1.4 (5) | 2.9 (7) | 1.5 away |
| Nate Williams | Warriors | 2.0 (5) | 0.6 (9) | 1.4 at home |
| Vince Williams Jr. | Jazz | 1.2 (20) | 2.3 (20) | 1.1 away |
| Scotty Pippen Jr. | Grizzlies | 3.3 (4) | 2.2 (11) | 1.1 at home |
| Koby Brea | Suns | 0.0 (8) | 1.0 (4) | 1.0 away |
| Malachi Smith | Raptors | 0.4 (10) | 1.4 (7) | 1.0 away |
| MarJon Beauchamp | 76ers | 1.4 (7) | 0.4 (7) | 1.0 at home |
| Darius Acuff Jr. | Kings | 3.3 (7) | 4.2 (5) | 0.9 away |
| Noa Essengue | Bulls | 0.0 (5) | 0.9 (8) | 0.9 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 |
|---|---|---|---|---|
| Chris Youngblood | Trail Blazers | 1.0 turnovers | 0.2 over 40 | 471% above |
| Jeff Green | Rockets | 0.8 turnovers | 0.2 over 32 | 412% above |
| Rayan Rupert | 76ers | 2.6 turnovers | 0.8 over 66 | 212% above |
| Alijah Martin | Raptors | 1.8 turnovers | 0.6 over 34 | 191% above |
| Jamal Cain | Magic | 1.8 turnovers | 0.6 over 60 | 184% above |
| Ron Harper Jr. | Celtics | 0.8 turnovers | 0.3 over 41 | 173% above |
| Thanasis Antetokounmpo | Bucks | 0.8 turnovers | 0.3 over 34 | 172% above |
| Jalen Wilson | Nets | 1.8 turnovers | 0.7 over 54 | 156% above |
| Jamir Watkins | Wizards | 2.0 turnovers | 0.8 over 50 | 150% above |
| Drew Timme | Lakers | 1.2 turnovers | 0.5 over 27 | 149% 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 |
|---|---|---|---|---|
| Will Riley | Wizards | 0.0 turnovers | 1.1 over 84 | 100% below |
| Kenrich Williams | Thunder | 0.0 turnovers | 0.6 over 80 | 100% below |
| Vít Krejčí | Trail Blazers | 0.0 turnovers | 0.6 over 76 | 100% below |
| Nae'Qwan Tomlin | Cavaliers | 0.0 turnovers | 0.4 over 71 | 100% below |
| Micah Peavy | Thunder | 0.0 turnovers | 0.3 over 69 | 100% below |
| Jaden Hardy | Lakers | 0.0 turnovers | 1.0 over 64 | 100% below |
| Jett Howard | Mavericks | 0.0 turnovers | 0.3 over 63 | 100% below |
| Noah Penda | Magic | 0.0 turnovers | 0.7 over 61 | 100% below |
| Al Horford | Warriors | 0.0 turnovers | 0.9 over 58 | 100% below |
| Zeke Nnaji | Nuggets | 0.0 turnovers | 0.5 over 56 | 100% 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.