formmarket 57%
Perry Ng
7/10
Over 0.5 shots · 5 in a rowLast 101.85
Championship · England
expected lineupDerby CountyDerby County last 5, most recent first: lost 1-2 away at Charlton Athletic, lost 1-2 at home to Sheffield United, won 3-2 away at Queens Park Rangers, lost 1-2 away at Norwich City, won 1-0 at home to Oxford United. v Cardiff CityCardiff City last 5, most recent first: drew 1-1 at home to Wrexham, lost 2-4 away at Norwich City, drew 0-0 at home to West Bromwich Albion, drew 1-1 at home to Oxford United, lost 0-2 away at Sheffield United.
Best edge
+27.2%
Joe Ward · shots
Last 10
7/10
Perry Ng · Over 0.5 shots
Referee
+19%
Ruebyn Ricardo · cards v league
1 live call — tap one for the price it beat
Shotsbet365Joe Ward+27.2%Over 1.5 shots3.75fair 2.95
The gap — the model’s fair price is 2.95 and bet365 is offering 3.75. That distance is the +27.2% edge, and it is what was published — not a price fetched now. Confidence low.
The projection — 0.95 shots expected from 75 minutes, built on 46 matches on record.
opponent
Cardiff City
12.3
Concede fouls committed · 3rd most of 27 · last 10 matchesAllowed a game
opponent
Cardiff City
17.2
Concede tackles · 3rd most of 27 · last 10 matchesAllowed a game
referee
Ruebyn Ricardo
22.6
Referee record · 4.9 cards a game · league 22.3 / 3.4 · last 20Fouls a game
RefereeRuebyn Ricardo25 on record
- Fouls/game
- 22.9-1%
- Cards/game
- 5.0+19%
Availability29 players projectedexpected lineup
- Minutes
- 0 confirmed
- 0 expected
- 29 provisional
An expected XI is out. Minutes mix whether a player is flagged to start with his own minutes as a starter and as a substitute.
Value — 1 live call
Published at the price shown, scored against the closing line.
Market
Sort
| Player | Market | Best odds | Fair odds | Edge | Bookmaker | Status |
|---|---|---|---|---|---|---|
| Joe Ward | Over 1.5 shots | 3.75 | 2.95 | +27.2% | bet365 | live |
Published at the price shown and scored against the closing line whatever happens next — the same rows, with staking context, are on the value board and in the track record.
Derby CountyHome · 4-2-3-1 · 11
Bench3 Forsyth10 Brewster13 Bilbija15 Salvesen23 Ward24 Nyambe26 Hedges31 Vickers37 Eames
The expected XI — it changes until the teamsheet is handed in. Players are placed in the shape the teamsheet itself gives, so a player covering out of position appears where he is playing rather than where he is registered.
Recent results
Last six completed matches per side, newest first. Half-time score in brackets where the feed carries one.
Derby CountyDerby County last 5, most recent first: lost 1-2 away at Charlton Athletic, lost 1-2 at home to Sheffield United, won 3-2 away at Queens Park Rangers, lost 1-2 away at Norwich City, won 1-0 at home to Oxford United.
- 15 AugACharlton Athletic(1-0)1-2L
- 2 MayHSheffield United(1-0)1-2L
- 25 AprAQueens Park Rangers(1-1)3-2W
- 21 AprANorwich City(0-1)1-2L
- 18 AprHOxford United(1-0)1-0W
- 11 AprASouthampton(1-0)1-2L
Cardiff CityCardiff City last 5, most recent first: drew 1-1 at home to Wrexham, lost 2-4 away at Norwich City, drew 0-0 at home to West Bromwich Albion, drew 1-1 at home to Oxford United, lost 0-2 away at Sheffield United.
- 17 AugHWrexham(0-1)1-1D
- 3 MayANorwich City(0-3)2-4L
- 26 AprHWest Bromwich Albion(0-0)0-0D
- 21 AprHOxford United(0-0)1-1D
- 18 AprASheffield United(0-1)0-2L
- 12 AprHStoke City(0-0)0-1L
Player props
Model projections. Nothing here has been compared to a bookmaker.
How this is calculated →Fouls29 playersHighest: Carlton Morris, 1.35 expectedshowhide
What drives it — Who referees the match. A strict official lifts every player on the pitch, which is the part most books price off a season average. See what has actually happened.
| Player | Team | Exp. mins | Projected | Over 1.5 | Model detail |
|---|---|---|---|---|---|
| Carlton MorrisFWD | Derby County | 77provisional | 1.35 | 39% | |
Projected distribution 027% 134% 223% 311% 44% 51% 6+0% | |||||
| Alex RobertsonMID | Cardiff City | 73provisional | 1.27 | 36% | |
Projected distribution 030% 134% 222% 310% 43% 51% 6+0% | |||||
| Yousef SalechFWD | Cardiff City | 71provisional | 1.08 | 29% | |
Fewer than 30 matches. §6.3 will not publish an edge on this player, and his own rate is heavily outweighed by his position group here. Projected distribution 036% 135% 219% 37% 42% 51% 6+0% | |||||
| Lewis TravisMID | Derby County | 84provisional | 1.08 | 29% | |
Projected distribution 035% 136% 219% 37% 42% 50% 6+0% | |||||
| Dion SandersonDEF | Derby County | 79provisional | 0.97 | 26% | |
Projected distribution 039% 135% 217% 36% 42% 5+0% | |||||
| Bobby ClarkMID | Derby County | 63provisional | 0.90 | 23% | |
Projected distribution 043% 134% 216% 35% 41% 5+0% | |||||
| Oscar FrauloMID | Derby County | 34provisional | 0.89 | 22% | |
Fewer than 30 matches. §6.3 will not publish an edge on this player, and his own rate is heavily outweighed by his position group here. Projected distribution 045% 132% 214% 35% 42% 51% 6+0% | |||||
| Patrick AgyemangFWD | Derby County | 40provisional | 0.86 | 22% | |
Projected distribution 045% 133% 214% 35% 42% 50% 6+0% | |||||
| Perry NgDEF | Cardiff City | 82provisional | 0.85 | 21% | |
Projected distribution 044% 135% 215% 35% 41% 5+0% | |||||
| Lars-Jørgen SalvesenFWD | Derby County | 20provisional | 0.80 | 19% | |
Projected distribution 050% 132% 212% 34% 42% 51% 6+0% | |||||
10 of 29 players shown, ranked by projection. Show all 29 →
Tackles29 playersHighest: Lewis Travis, 1.45 expectedshowhide
What drives it — Possession share. A tackle count depends far more on how much of the match is played at your own end than on a player’s own form. See what has actually happened.
Opponent — Cardiff City concede 17.2 tackles a game — 3rd most of 27 in the Championship.
| Player | Team | Exp. mins | Projected | Over 1.5 | Model detail |
|---|---|---|---|---|---|
| Lewis TravisMID | Derby County | 84provisional | 1.45 | 41% | |
Projected distribution 027% 132% 222% 311% 45% 52% 6+1% | |||||
| Perry NgDEF | Cardiff City | 82provisional | 1.35 | 38% | |
Projected distribution 029% 133% 221% 310% 44% 51% 6+1% | |||||
| Alex RobertsonMID | Cardiff City | 73provisional | 1.18 | 32% | |
Projected distribution 034% 133% 219% 39% 43% 51% 6+0% | |||||
| Ollie TannerFWD | Cardiff City | 48provisional | 0.88 | 22% | |
Projected distribution 046% 131% 214% 35% 42% 51% 6+0% | |||||
| David TurnbullMID | Cardiff City | 43provisional | 0.82 | 20% | |
Fewer than 30 matches. §6.3 will not publish an edge on this player, and his own rate is heavily outweighed by his position group here. Projected distribution 049% 130% 213% 35% 42% 51% 6+0% | |||||
| Sondre LangåsDEF | Derby County | 83provisional | 0.80 | 20% | |
Projected distribution 047% 134% 214% 34% 41% 5+0% | |||||
| Joe WardMID | Derby County | 75provisional | 0.80 | 20% | |
Projected distribution 048% 132% 214% 35% 41% 5+0% | |||||
| Charlie TaylorDEF | Derby County | 70provisional | 0.80 | 20% | |
Projected distribution 049% 131% 214% 35% 41% 5+0% | |||||
| Bobby ClarkMID | Derby County | 63provisional | 0.77 | 19% | |
Projected distribution 050% 131% 213% 34% 41% 5+0% | |||||
| Matt ClarkeDEF | Derby County | 65provisional | 0.72 | 17% | |
Projected distribution 053% 130% 212% 34% 41% 5+0% | |||||
10 of 29 players shown, ranked by projection. Show all 29 →
Shots29 playersHighest: Yousef Salech, 1.84 expectedshowhide
What drives it — The player’s own shot rate, shrunk toward others in his position, then adjusted for how many shots the opponent concedes. See what has actually happened.
| Player | Team | Exp. mins | Projected | Over 1.5 | Model detail |
|---|---|---|---|---|---|
| Yousef SalechFWD | Cardiff City | 71provisional | 1.84 | 52% | |
Fewer than 30 matches. §6.3 will not publish an edge on this player, and his own rate is heavily outweighed by his position group here. Projected distribution 020% 127% 223% 315% 48% 54% 6+2% | |||||
| Carlton MorrisFWD | Derby County | 77provisional | 1.76 | 51% | |
Projected distribution 020% 129% 224% 315% 47% 53% 6+2% | |||||
| Sammie SzmodicsMID | Derby County | 65provisional | 1.57 | 45% | |
Projected distribution 026% 129% 222% 313% 46% 52% 6+1% | |||||
| Callum RobinsonFWD | Cardiff City | 54provisional | 1.41 | 39% | |
Projected distribution 030% 131% 220% 311% 45% 52% 6+1% | |||||
| Patrick AgyemangFWD | Derby County | 40provisional | 1.37 | 37% | |
Projected distribution 031% 132% 219% 310% 45% 52% 6+1% | |||||
| Rhian BrewsterFWD | Derby County | 46provisional | 1.19 | 32% | |
Projected distribution 036% 132% 218% 39% 44% 51% 6+1% | |||||
| Bobby ClarkMID | Derby County | 63provisional | 1.08 | 29% | |
Projected distribution 038% 133% 218% 38% 43% 51% 6+0% | |||||
| Joe WardMID | Derby County | 75provisional | 0.95 | 25% | |
Projected distribution 041% 134% 217% 36% 42% 50% 6+0% | |||||
| Cian AshfordFWD | Cardiff City | 65provisional | 0.93 | 24% | |
Fewer than 30 matches. §6.3 will not publish an edge on this player, and his own rate is heavily outweighed by his position group here. Projected distribution 043% 133% 216% 36% 42% 50% 6+0% | |||||
| Ollie TannerFWD | Cardiff City | 48provisional | 0.93 | 24% | |
Projected distribution 044% 132% 215% 36% 42% 51% 6+0% | |||||
10 of 29 players shown, ranked by projection. Show all 29 →
Shots on target29 playersHighest: Yousef Salech, 0.80 expectedshowhide
What drives it — Shot volume first, conversion second — literally: the projection is the shots model thinned by the player’s own on-target rate, so a high-volume low-accuracy shooter and a sniper price differently at the same shot count. See what has actually happened.
| Player | Team | Exp. mins | Projected | Over 0.5 | Model detail |
|---|---|---|---|---|---|
| Yousef SalechFWD | Cardiff City | 71provisional | 0.80 | 53% | |
Fewer than 30 matches. §6.3 will not publish an edge on this player, and his own rate is heavily outweighed by his position group here. Projected distribution 047% 133% 214% 34% 41% 5+0% | |||||
| Carlton MorrisFWD | Derby County | 77provisional | 0.75 | 51% | |
Projected distribution 049% 134% 213% 34% 41% 5+0% | |||||
| Callum RobinsonFWD | Cardiff City | 54provisional | 0.63 | 44% | |
Projected distribution 056% 130% 210% 33% 41% 5+0% | |||||
| Sammie SzmodicsMID | Derby County | 65provisional | 0.58 | 43% | |
Projected distribution 057% 130% 210% 32% 4+1% | |||||
| Patrick AgyemangFWD | Derby County | 40provisional | 0.51 | 38% | |
Projected distribution 062% 128% 28% 32% 40% 5+0% | |||||
| Rhian BrewsterFWD | Derby County | 46provisional | 0.42 | 33% | |
Projected distribution 067% 125% 26% 31% 4+0% | |||||
| Joe WardMID | Derby County | 75provisional | 0.34 | 28% | |
Projected distribution 072% 123% 24% 3+1% | |||||
| Lars-Jørgen SalvesenFWD | Derby County | 20provisional | 0.33 | 26% | |
Projected distribution 074% 121% 24% 31% 4+0% | |||||
| Ollie TannerFWD | Cardiff City | 48provisional | 0.31 | 26% | |
Projected distribution 074% 121% 24% 3+1% | |||||
| Corey Blackett-TaylorFWD | Derby County | 27provisional | 0.29 | 25% | |
Fewer than 30 matches. §6.3 will not publish an edge on this player, and his own rate is heavily outweighed by his position group here. Projected distribution 075% 120% 24% 3+1% | |||||
10 of 29 players shown, ranked by projection. Show all 29 →
Fouls won29 playersHighest: Lewis Travis, 1.67 expectedshowhide
What drives it — How much a player runs at defenders. Dribble volume drives this far more than the referee does. See what has actually happened.
Opponent — Cardiff City concede 12.3 fouls a game — 3rd most of 27 in the Championship.
| Player | Team | Exp. mins | Projected | Over 1.5 | Model detail |
|---|---|---|---|---|---|
| Lewis TravisMID | Derby County | 84provisional | 1.67 | 49% | |
Projected distribution 021% 130% 225% 314% 46% 52% 6+1% | |||||
| Perry NgDEF | Cardiff City | 82provisional | 1.53 | 44% | |
Projected distribution 024% 132% 224% 313% 45% 52% 6+1% | |||||
| Alex RobertsonMID | Cardiff City | 73provisional | 1.29 | 37% | |
Projected distribution 030% 133% 221% 310% 44% 51% 6+0% | |||||
| Carlton MorrisFWD | Derby County | 77provisional | 1.26 | 36% | |
Projected distribution 031% 134% 221% 310% 43% 51% 6+0% | |||||
| Yousef SalechFWD | Cardiff City | 71provisional | 1.24 | 35% | |
Fewer than 30 matches. §6.3 will not publish an edge on this player, and his own rate is heavily outweighed by his position group here. Projected distribution 032% 133% 220% 39% 44% 51% 6+0% | |||||
| Cian AshfordFWD | Cardiff City | 65provisional | 1.03 | 28% | |
Fewer than 30 matches. §6.3 will not publish an edge on this player, and his own rate is heavily outweighed by his position group here. Projected distribution 039% 133% 218% 37% 42% 51% 6+0% | |||||
| Alex MowattMID | Derby County | 65provisional | 0.95 | 25% | |
Projected distribution 042% 133% 216% 36% 42% 51% 6+0% | |||||
| Chris WillockFWD | Cardiff City | 48provisional | 0.89 | 23% | |
Projected distribution 045% 132% 215% 36% 42% 50% 6+0% | |||||
| Patrick AgyemangFWD | Derby County | 40provisional | 0.87 | 22% | |
Projected distribution 046% 132% 214% 35% 42% 51% 6+0% | |||||
| Bobby ClarkMID | Derby County | 63provisional | 0.77 | 19% | |
Projected distribution 049% 132% 213% 34% 41% 5+0% | |||||
10 of 29 players shown, ranked by projection. Show all 29 →
Saves1 playersHighest: Jacob Widell Zetterström, 2.66 expectedshowhide
What drives it — Opponent shot volume. A keeper’s own record carries so little that this market shrinks harder than any other on the board. See what has actually happened.
| Player | Team | Exp. mins | Projected | Over 2.5 | Model detail |
|---|---|---|---|---|---|
| Jacob Widell ZetterströmGK | Derby County | 89provisional | 2.66 | 48% | |
Projected distribution 09% 120% 223% 320% 413% 58% 6+7% | |||||
1 of 7 markets have no projection for this fixture.
Trends and angles
Form against the lines the books are pricing, what the opposition concede, and the referee against his league.
- 7/10Last 1011/20Last 205 in a rowL101111102001most recent first · jade beats 0.5
- 12.3Allowed a game3rd most of 27last 10 matches
- 17.2Allowed a game3rd most of 27last 10 matches
- 22.6Fouls a game4.9 cards a gameleague 22.3 / 3.4last 20
Facts with sample sizes, not predictions. The market % beside a line is the books’ median price with margin in, and the over market runs hot.
every priced linebuilderReferee
§5.1: the dominant covariate for fouls, and the reason two identical players price differently on different days.
Ruebyn Ricardo
25 matches on record · full record →
Fouls per game
22.9
-1% vs leagueleague 23.2 fouls
Cards per game
5.0
+19% vs leagueleague 4.2 cards
Cards, home side
2.0
Derby County
Cards, away side
2.9
Cardiff City
Derby County 2.0Where the cards go2.9 Cardiff City
Fouls — every foul committed by both teams in a match he refereed, averaged over his completed matches. The match being previewed is never in it.
Cards — any card, yellow or red, both teams. The same definition the card props settle against, so this figure and the Cards market count the same events. A dismissal that the feed records as a second yellow counts as two.
Both league averages are the mean across all five competitions Per90 covers, not this fixture's league alone — the fouls comparison has always been that, and the cards comparison is built the same way so the two percentages beside each other mean the same thing.
The model
What the numbers on this page are, and what they are not.
How are these projections calculated?OpenClose
Not tips and not prices. Each row is the model's expected count for one player in this match — how many fouls, tackles or shots it thinks he records — plus the full spread of outcomes around it. Nothing in the projections has been compared to a bookmaker; that comparison is what the Value tab is.
Step 1
His own record
Every completed match in the dataset, as a rate per 90 minutes. The n column is how many matches that rests on.
Step 2
Pulled toward his position
A thin record gets pulled hard toward other players in his position, in his league — a goalkeeper toward goalkeepers, not toward the outfielders around him. How hard is fitted per market, not chosen: tackles pull about four times harder than shots on target.
Step 3
This fixture's conditions
How much of the stat the opponent concedes, what the referee’s matches look like, and home or away. This is where a projection stops being a season average.
Step 4
Scaled to expected minutes
A rate becomes a count only once you say how long he plays. 60 minutes carries two-thirds the exposure of 90, and the distribution is built at that exposure.
How to read each column
- Model /90
- The model’s rate for this match with the minutes taken back out — steps 1 to 3 already applied. It moves with the opponent and the referee, so it is not his raw career rate; the builder shows career and model rates side by side. Open any row to see it.
- Exp. mins
- Minutes the model expects. Confirmed means the lineup is out; provisional means it is guessing from his start rate, and is the widest of the three.
- Projected
- The expected count in this match, at those minutes. This is the number a line is set against.
- Over 1.5, etc.
- Read straight off the distribution beside it, not off how often he has beaten that line before. It answers what the model thinks, not what has happened.
- n
- Matches behind his own rate. Under 30 it turns amber: the projection is mostly his position group speaking, and §6.3 will not publish an edge on it.
- Distribution
- The whole spread, not just the average. The dashed amber cut is the line; jade bars beat it. An expected 1.8 fouls made of 2 every week and an expected 1.8 made of a 0 and a 5 are different bets, and this is where you see which one you have.
Counts are modelled as negative binomial rather than Poisson, because fouls and tackles are overdispersed and a Poisson would systematically underprice the tails — which is exactly where over bets live. Every market on this page cleared its calibration gate before it was allowed to produce a projection: when the model says 60%, it lands within a point or so of 60% out of sample.
Fouls v20260821-1755 · Tackles v20260821-1755 · Shots v20260821-1755 · Shots on target v20260821-1755 · Fouls won v20260821-1755 · Saves v20260816-1229
The full write-up — every gate, every fitted parameter and what the model refuses to price — is on the methodology page.
1 of 7 markets have no projection for this fixture. A market with no projection is a market the job could not fill, not one the page chose to hide.