La Liga · Spain
La Liga · SpainRacing SantandervElche
Racing Santander
ElcheReferee
Not appointed
0 matches on record
Fouls per game
—
League average
22.6
fouls per match, both teams
Value
No edges published on this fixture. An edge is published only when a bookmaker's price beats the model's fair price by that market's full bar — most fixtures never produce one. The value board explains every gate a candidate has to clear.
What these numbers are
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 here has been compared to a bookmaker.
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 columnClose
- 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.
- 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 v20260813-1451 · Tackles v20260813-1451 · Shots v20260813-1451 · Fouls won v20260813-1451 · Cards v20260813-1451 · Saves v20260813-1451
Model projections
Fouls14 playersHighest: Aboubacar Sangaré Traoré, 1.83 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 | Model /90 | Exp. mins | Projected | Over 1.5 | n | Distribution |
|---|---|---|---|---|---|---|---|
| Aboubacar Sangaré TraoréDEF | Elche | 3.64 | 45provisional | 1.83 | 49% | 7 | 029% 122% 218% 314% 49% 55% 6+3% |
| José Antonio Morente OlivaFWD | Elche | 2.26 | 72provisional | 1.81 | 52% | 11 | 020% 128% 224% 315% 48% 53% 6+2% |
| Víctor Chust GarcíaDEF | Elche | 2.03 | 70provisional | 1.57 | 45% | 27 | 027% 129% 221% 313% 46% 53% 6+1% |
| German Valera KarabinaiteFWD | Elche | 1.62 | 80provisional | 1.43 | 42% | 33 | 026% 132% 223% 312% 45% 51% 6+1% |
| Gonzalo Villar del FraileMID | Elche | 2.00 | 60provisional | 1.33 | 37% | 8 | 034% 129% 219% 311% 45% 52% 6+1% |
| David AffengruberDEF | Elche | 1.41 | 82provisional | 1.28 | 37% | 35 | 029% 134% 222% 310% 43% 51% 6+0% |
| Pedro Bigas RigoDEF | Elche | 1.48 | 74provisional | 1.21 | 34% | 25 | 033% 133% 221% 39% 43% 51% 6+0% |
| Martim Carvalho NetoMID | Elche | 1.98 | 54provisional | 1.19 | 33% | 20 | 034% 133% 220% 39% 43% 51% 6+0% |
| Marc Aguado PallaresMID | Elche | 1.41 | 72provisional | 1.13 | 31% | 31 | 035% 134% 220% 38% 43% 51% 6+0% |
| Grady DianganaFWD | Elche | 2.17 | 47provisional | 1.12 | 31% | 13 | 038% 131% 218% 38% 43% 51% 6+0% |
10 of 14 players shown, ranked by projection. Show all 14 →
Tackles14 playersHighest: Víctor Chust García, 2.65 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.
| Player | Team | Model /90 | Exp. mins | Projected | Over 1.5 | n | Distribution |
|---|---|---|---|---|---|---|---|
| Víctor Chust GarcíaDEF | Elche | 3.42 | 70provisional | 2.65 | 64% | 27 | 016% 120% 218% 315% 411% 58% 6+11% |
| David AffengruberDEF | Elche | 2.85 | 82provisional | 2.60 | 68% | 35 | 012% 120% 222% 318% 412% 58% 6+8% |
| Marc Aguado PallaresMID | Elche | 2.54 | 72provisional | 2.03 | 55% | 31 | 020% 125% 222% 316% 49% 55% 6+4% |
| German Valera KarabinaiteFWD | Elche | 2.27 | 80provisional | 2.01 | 56% | 33 | 019% 125% 223% 316% 49% 55% 6+3% |
| Aboubacar Sangaré TraoréDEF | Elche | 3.88 | 45provisional | 1.95 | 50% | 7 | 029% 121% 217% 313% 49% 55% 6+6% |
| Pedro Bigas RigoDEF | Elche | 2.28 | 74provisional | 1.88 | 52% | 25 | 022% 126% 222% 315% 48% 54% 6+3% |
| José Antonio Morente OlivaFWD | Elche | 2.26 | 72provisional | 1.80 | 50% | 11 | 022% 128% 222% 314% 48% 54% 6+2% |
| Gonzalo Villar del FraileMID | Elche | 2.71 | 60provisional | 1.80 | 48% | 8 | 028% 125% 219% 313% 48% 54% 6+4% |
| Martim Carvalho NetoMID | Elche | 2.51 | 54provisional | 1.51 | 42% | 20 | 028% 130% 221% 311% 46% 52% 6+2% |
| Grady DianganaFWD | Elche | 2.14 | 47provisional | 1.11 | 30% | 13 | 040% 130% 217% 38% 43% 51% 6+1% |
10 of 14 players shown, ranked by projection. Show all 14 →
Shots14 playersHighest: José Antonio Morente Oliva, 1.61 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 | Model /90 | Exp. mins | Projected | Over 1.5 | n | Distribution |
|---|---|---|---|---|---|---|---|
| José Antonio Morente OlivaFWD | Elche | 2.02 | 72provisional | 1.61 | 46% | 11 | 024% 130% 223% 313% 46% 52% 6+1% |
| Lucas CepedaFWD | Elche | 3.28 | 40provisional | 1.45 | 36% | 4 | 038% 126% 215% 39% 46% 53% 6+3% |
| German Valera KarabinaiteFWD | Elche | 1.60 | 80provisional | 1.42 | 41% | 33 | 027% 132% 222% 312% 45% 52% 6+1% |
| Grady DianganaFWD | Elche | 2.28 | 47provisional | 1.18 | 33% | 13 | 037% 130% 218% 39% 44% 51% 6+1% |
| Gonzalo Villar del FraileMID | Elche | 1.15 | 60provisional | 0.77 | 19% | 8 | 051% 130% 213% 35% 41% 5+0% |
| Martim Carvalho NetoMID | Elche | 1.16 | 54provisional | 0.70 | 16% | 20 | 052% 132% 212% 33% 41% 5+0% |
| David AffengruberDEF | Elche | 0.58 | 82provisional | 0.53 | 10% | 35 | 060% 130% 28% 32% 4+0% |
| Pedro Bigas RigoDEF | Elche | 0.61 | 74provisional | 0.50 | 10% | 25 | 062% 129% 28% 32% 4+0% |
| Víctor Chust GarcíaDEF | Elche | 0.56 | 70provisional | 0.43 | 8% | 27 | 066% 126% 26% 31% 4+0% |
| Aboubacar Sangaré TraoréDEF | Elche | 0.65 | 45provisional | 0.33 | 5% | 7 | 074% 121% 25% 31% 4+0% |
10 of 14 players shown, ranked by projection. Show all 14 →
Fouls won14 playersHighest: German Valera Karabinaite, 2.51 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.
| Player | Team | Model /90 | Exp. mins | Projected | Over 1.5 | n | Distribution |
|---|---|---|---|---|---|---|---|
| German Valera KarabinaiteFWD | Elche | 2.84 | 80provisional | 2.51 | 68% | 33 | 012% 120% 222% 319% 413% 57% 6+6% |
| Gonzalo Villar del FraileMID | Elche | 3.08 | 60provisional | 2.05 | 54% | 8 | 023% 123% 219% 314% 410% 56% 6+5% |
| José Antonio Morente OlivaFWD | Elche | 1.56 | 72provisional | 1.24 | 35% | 11 | 032% 133% 220% 39% 43% 51% 6+0% |
| Grady DianganaFWD | Elche | 2.34 | 47provisional | 1.21 | 33% | 13 | 036% 130% 218% 39% 44% 51% 6+1% |
| David AffengruberDEF | Elche | 1.27 | 82provisional | 1.16 | 32% | 35 | 034% 134% 220% 38% 43% 51% 6+0% |
| Lucas CepedaFWD | Elche | 2.33 | 40provisional | 1.03 | 27% | 4 | 047% 127% 213% 37% 44% 52% 6+1% |
| Marc Aguado PallaresMID | Elche | 1.09 | 72provisional | 0.87 | 22% | 31 | 044% 133% 215% 35% 41% 5+0% |
| Pedro Bigas RigoDEF | Elche | 1.05 | 74provisional | 0.86 | 22% | 25 | 045% 133% 215% 35% 41% 5+0% |
| Aboubacar Sangaré TraoréDEF | Elche | 1.66 | 45provisional | 0.83 | 22% | 7 | 050% 128% 214% 36% 42% 50% 6+0% |
| Martim Carvalho NetoMID | Elche | 1.31 | 54provisional | 0.79 | 19% | 20 | 048% 133% 213% 34% 41% 5+0% |
10 of 14 players shown, ranked by projection. Show all 14 →
Cards14 playersHighest: Víctor Chust García, 0.30 expectedshowhide
Known defect — Prices ANY card — yellow, second yellow or straight red — matching how books settle "to be shown a card". The trends column counts the same thing.
What drives it — Fouls first, then how readily the referee reaches for a card. Two officials averaging four cards a match can do it for opposite reasons. See what has actually happened.
| Player | Team | Model /90 | Exp. mins | Projected | Over 0.5 | n | Distribution |
|---|---|---|---|---|---|---|---|
| Víctor Chust GarcíaDEF | Elche | 0.39 | 70provisional | 0.30 | 26% | 27 | 074% 121% 24% 3+1% |
| Aboubacar Sangaré TraoréDEF | Elche | 0.57 | 45provisional | 0.29 | 24% | 7 | 076% 120% 24% 3+1% |
| David AffengruberDEF | Elche | 0.28 | 82provisional | 0.26 | 23% | 35 | 077% 120% 23% 3+0% |
| Pedro Bigas RigoDEF | Elche | 0.27 | 74provisional | 0.22 | 19% | 25 | 081% 117% 22% 3+0% |
| José Antonio Morente OlivaFWD | Elche | 0.27 | 72provisional | 0.21 | 19% | 11 | 081% 117% 22% 3+0% |
| Gonzalo Villar del FraileMID | Elche | 0.32 | 60provisional | 0.21 | 18% | 8 | 082% 116% 22% 3+0% |
| German Valera KarabinaiteFWD | Elche | 0.21 | 80provisional | 0.19 | 17% | 33 | 083% 115% 22% 3+0% |
| Marc Aguado PallaresMID | Elche | 0.23 | 72provisional | 0.18 | 16% | 31 | 084% 115% 21% 3+0% |
| Grady DianganaFWD | Elche | 0.32 | 47provisional | 0.17 | 15% | 13 | 085% 113% 21% 3+0% |
| Martim Carvalho NetoMID | Elche | 0.26 | 54provisional | 0.16 | 15% | 20 | 085% 113% 2+1% |
10 of 14 players shown, ranked by projection. Show all 14 →
Saves1 playersHighest: Matías Ezequiel Dituro, 3.43 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 | Model /90 | Exp. mins | Projected | Over 2.5 | n | Distribution |
|---|---|---|---|---|---|---|---|
| Matías Ezequiel DituroGK | Elche | 3.43 | 90provisional | 3.43 | 63% | 22 | 05% 113% 219% 320% 416% 512% 6+16% |
1 of 7 markets have no projection for this fixture.