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Across 499 NBA players with at least 10 logged games in turnovers, this page measures 28078 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 499 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 252 players whose spread can be measured, 0 cluster tightly around their average, 87 vary moderately and 165 swing widely. 499 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 499 measured; the figures above this table are over all 499.
| Player | Club | Logged games | Average | Balanced line | Hit rate there |
|---|---|---|---|---|---|
| Julian Champagnie | Spurs | 105 | 0.8 turnovers | Over 0.5 | 60 of 105 (57%) |
| Keldon Johnson | Spurs | 105 | 0.9 turnovers | Over 0.5 | 65 of 105 (62%) |
| Mikal Bridges | Knicks | 101 | 1.0 turnovers | Over 0.5 | 67 of 101 (66%) |
| Harrison Barnes | Spurs | 97 | 0.7 turnovers | Over 0.5 | 46 of 97 (47%) |
| Karl-Anthony Towns | Knicks | 94 | 2.5 turnovers | Over 2.5 | 44 of 94 (47%) |
| Carter Bryant | Spurs | 93 | 0.5 turnovers | Over 0.5 | 36 of 93 (39%) |
| De'Aaron Fox | Spurs | 93 | 2.2 turnovers | Over 2.5 | 35 of 93 (38%) |
| Jalen Brunson | Knicks | 93 | 2.4 turnovers | Over 2.5 | 43 of 93 (46%) |
| Javonte Green | Pistons | 93 | 0.5 turnovers | Over 0.5 | 34 of 93 (37%) |
| Cason Wallace | Thunder | 92 | 0.9 turnovers | Over 0.5 | 50 of 92 (54%) |
| Dylan Harper | Spurs | 92 | 1.5 turnovers | Over 1.5 | 42 of 92 (46%) |
| Julius Randle | Timberwolves | 91 | 2.8 turnovers | Over 2.5 | 47 of 91 (52%) |
| Luke Kornet | Spurs | 91 | 0.4 turnovers | Over 0.5 | 32 of 91 (35%) |
| Stephon Castle | Spurs | 91 | 3.3 turnovers | Over 2.5 | 54 of 91 (59%) |
| Devin Vassell | Spurs | 90 | 0.9 turnovers | Over 0.5 | 59 of 90 (66%) |
| Duncan Robinson | Pistons | 90 | 0.7 turnovers | Over 0.5 | 52 of 90 (58%) |
| Jake LaRavia | Lakers | 90 | 1.1 turnovers | Over 0.5 | 61 of 90 (68%) |
| Jordan Clarkson | Knicks | 90 | 0.9 turnovers | Over 0.5 | 55 of 90 (61%) |
| Desmond Bane | Magic | 89 | 2.0 turnovers | Over 1.5 | 55 of 89 (62%) |
| Jamal Shead | Raptors | 89 | 1.4 turnovers | Over 1.5 | 40 of 89 (45%) |
| Naz Reid | Timberwolves | 89 | 1.6 turnovers | Over 1.5 | 46 of 89 (52%) |
| Bruce Brown | Nuggets | 88 | 1.1 turnovers | Over 1.5 | 32 of 88 (36%) |
| Donovan Mitchell | Cavaliers | 88 | 2.8 turnovers | Over 2.5 | 48 of 88 (55%) |
| James Harden | Cavaliers | 88 | 3.7 turnovers | Over 3.5 | 46 of 88 (52%) |
| Luke Kennard | Lakers | 88 | 0.8 turnovers | Over 0.5 | 50 of 88 (57%) |
| Reed Sheppard | Rockets | 88 | 1.5 turnovers | Over 1.5 | 41 of 88 (47%) |
| Rudy Gobert | Timberwolves | 88 | 1.4 turnovers | Over 1.5 | 37 of 88 (42%) |
| Ausar Thompson | Pistons | 87 | 1.5 turnovers | Over 1.5 | 39 of 87 (45%) |
| Dennis Schröder | Cavaliers | 87 | 1.7 turnovers | Over 1.5 | 45 of 87 (52%) |
| Jose Alvarado | Knicks | 87 | 1.0 turnovers | Over 0.5 | 55 of 87 (63%) |
| Ronald Holland II | Pistons | 87 | 1.1 turnovers | Over 0.5 | 57 of 87 (66%) |
| Sandro Mamukelashvili | Raptors | 87 | 0.8 turnovers | Over 0.5 | 49 of 87 (56%) |
| Scottie Barnes | Raptors | 87 | 2.7 turnovers | Over 2.5 | 48 of 87 (55%) |
| Toumani Camara | Trail Blazers | 87 | 1.7 turnovers | Over 1.5 | 45 of 87 (52%) |
| Daniss Jenkins | Pistons | 86 | 1.5 turnovers | Over 1.5 | 30 of 86 (35%) |
| Donte DiVincenzo | Timberwolves | 86 | 1.4 turnovers | Over 1.5 | 31 of 86 (36%) |
| Oso Ighodaro | Suns | 86 | 1.3 turnovers | Over 1.5 | 27 of 86 (31%) |
| Payton Pritchard | Celtics | 86 | 1.3 turnovers | Over 1.5 | 31 of 86 (36%) |
| Quentin Grimes | 76ers | 86 | 1.6 turnovers | Over 1.5 | 38 of 86 (44%) |
| Tim Hardaway Jr. | Nuggets | 86 | 0.5 turnovers | Over 0.5 | 36 of 86 (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 |
|---|---|---|---|---|---|
| Deni Avdija | Trail Blazers | 71 | 3.8 turnovers | 1.7 | 44% |
| Josh Giddey | Bulls | 54 | 3.6 turnovers | 1.6 | 45% |
| Jaylen Brown | Celtics | 78 | 3.6 turnovers | 1.7 | 46% |
| Jalen Suggs | Magic | 64 | 2.7 turnovers | 1.3 | 48% |
| Jalen Johnson | Hawks | 78 | 3.3 turnovers | 1.6 | 48% |
| Luka Dončić | Lakers | 64 | 4.0 turnovers | 1.9 | 48% |
| Stephen Curry | Warriors | 43 | 2.8 turnovers | 1.4 | 49% |
| Russell Westbrook | Kings | 64 | 3.3 turnovers | 1.6 | 50% |
| Giannis Antetokounmpo | Bucks | 36 | 3.2 turnovers | 1.6 | 50% |
| James Harden | Cavaliers | 88 | 3.7 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 |
|---|---|---|---|---|---|
| Nikola Topić | Thunder | 19 | 1.4 turnovers | 2.1 | 147% |
| KJ Simpson | Nuggets | 20 | 1.3 turnovers | 1.8 | 143% |
| Jahmai Mashack | Grizzlies | 31 | 1.6 turnovers | 2.0 | 128% |
| Ousmane Dieng | Bucks | 57 | 1.3 turnovers | 1.7 | 126% |
| Jalen Slawson | Pacers | 13 | 1.3 turnovers | 1.6 | 121% |
| Tre Mann | Hornets | 53 | 1.0 turnovers | 1.2 | 120% |
| Cody Williams | Jazz | 67 | 1.1 turnovers | 1.3 | 118% |
| Micah Potter | Pacers | 47 | 1.0 turnovers | 1.1 | 113% |
| Kevin Huerter | Pistons | 74 | 1.0 turnovers | 1.1 | 110% |
| Gui Santos | Warriors | 68 | 1.5 turnovers | 1.6 | 110% |
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 |
|---|---|---|---|---|
| Leaky Black | Wizards | 2.3 (4) | 0.5 (11) | 1.8 at home |
| Scotty Pippen Jr. | Grizzlies | 3.7 (3) | 2.3 (7) | 1.4 at home |
| Jalen Green | Suns | 1.7 (19) | 3.1 (17) | 1.4 away |
| Trae Young | Wizards | 3.3 (8) | 1.9 (7) | 1.4 at home |
| Nate Williams | Warriors | 2.0 (5) | 0.6 (9) | 1.4 at home |
| Zach Collins | Bulls | 0.5 (6) | 1.8 (4) | 1.3 away |
| Malachi Smith | Nets | 0.4 (9) | 1.7 (6) | 1.3 away |
| Tyler Herro | Heat | 2.5 (17) | 1.4 (16) | 1.1 at home |
| Bogdan Bogdanović | Clippers | 1.8 (10) | 0.7 (13) | 1.1 at home |
| Vince Williams Jr. | Jazz | 1.2 (20) | 2.3 (20) | 1.1 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 |
|---|---|---|---|---|
| Jeff Green | Rockets | 0.8 turnovers | 0.2 over 32 | 412% above |
| Ousmane Dieng | Bucks | 4.4 turnovers | 1.3 over 57 | 234% above |
| Rayan Rupert | Grizzlies | 2.8 turnovers | 0.9 over 64 | 226% above |
| Gary Trent Jr. | Bucks | 2.0 turnovers | 0.6 over 65 | 217% above |
| Micah Peavy | Pelicans | 1.0 turnovers | 0.3 over 61 | 205% above |
| Jordan Hawkins | Pelicans | 2.0 turnovers | 0.7 over 51 | 200% above |
| Pacôme Dadiet | Knicks | 0.4 turnovers | 0.1 over 36 | 188% above |
| Leonard Miller | Bulls | 2.2 turnovers | 0.8 over 46 | 181% above |
| Amir Coffey | Suns | 0.6 turnovers | 0.2 over 50 | 173% above |
| Thanasis Antetokounmpo | Bucks | 0.8 turnovers | 0.3 over 34 | 172% 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 |
|---|---|---|---|---|
| Javonte Green | Pistons | 0.0 turnovers | 0.5 over 93 | 100% below |
| Gradey Dick | Raptors | 0.0 turnovers | 0.5 over 79 | 100% below |
| Jordan Walsh | Celtics | 0.0 turnovers | 0.5 over 75 | 100% below |
| Jaylen Clark | Timberwolves | 0.0 turnovers | 0.3 over 74 | 100% below |
| Nae'Qwan Tomlin | Cavaliers | 0.0 turnovers | 0.4 over 71 | 100% below |
| Landry Shamet | Knicks | 0.0 turnovers | 0.5 over 70 | 100% below |
| Dru Smith | Heat | 0.0 turnovers | 0.8 over 70 | 100% below |
| Vít Krejčí | Trail Blazers | 0.0 turnovers | 0.6 over 69 | 100% below |
| Will Richard | Warriors | 0.0 turnovers | 0.8 over 69 | 100% below |
| Noah Penda | Magic | 0.0 turnovers | 0.7 over 60 | 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, edges and grades are Parlay Builder’s own calculations.