Also see Gruev betting, spreads & statistics.
Gruev
MIDIlia Gruev · Leeds · £5.0m · 0.0% owned · 1 pts
Why we rank Gruev here
- ▸Away vs CHE: we project LEE for 0.72 goals (our difficulty 4.0/5)
- ▸9% start probability, 9 expected minutes
- ▸Underlying: 0.07 xG90, 0.09 xA90 (shrunk to 1 mins of data)
- ▸Bonus model: 0.02 expected bonus points
- ▸Risk 50/100 — Flagged: 100% chance of playing
- ▸1.8 xPts over the next 5 GWs at £5.0m (0.37 xPts/£m)
Points breakdown — GW11 at CHE
| Appearance points | 0.29 |
| Goal points | 0.02 |
| Assist points | 0.01 |
| Clean sheet points | 0.02 |
| Save points | 0.00 |
| Defensive contribution | 0.00 |
| Bonus points | 0.02 |
| Goals conceded | 0.00 |
| Cards / other | -0.02 |
| Predicted FPL points | 0.3 |
Card minutes (yellow-minute spread)
Loading card-minute prices…
What is a yellow-minute price?
A card-minute (or "yellow-minute") spread pays out on the clock time of a player's booking, not on whether he is booked. If Gruev is shown a yellow card in the 60th minute, the market settles at 60. A red card settles higher (bookmakers use a fixed larger value), and if he is never carded the market settles at 0 — so the price is always a blend of how likely a booking is and how late it would arrive.
You buy at the higher number if you think he is more likely to be carded than the quote implies, and sell at the lower number if you think he stays clean. Profit or loss is your stake multiplied by the difference between the settled minute and your line, so losses can be far bigger than the stake — most bookmakers void the bet if the player does not appear.
Our number comes from his booking rate per 90, shrunk toward a positional average, adjusted for expected minutes, opponent and referee-style match context, then simulated to get an average settled minute. See the full spread breakdown.
Fixture-by-fixture projection
| GW | Opp | xMins | P(goal) | P(CS) | xPts |
|---|---|---|---|---|---|
| 11 | CHE (A) | 9.4 | 0% | 2% | 0.3 |
| 12 | COV (H) | 9.4 | 1% | 5% | 0.4 |
| 13 | MCI (A) | 9.4 | 0% | 2% | 0.3 |
| 14 | IPS (H) | 9.4 | 1% | 4% | 0.4 |
| 15 | LIV (A) | 9.4 | 0% | 2% | 0.3 |
Next Gameweek distribution
Underlying data (per 90, shrunk)
Recent matches
| GW | Opp | Min | G | A | xG | Pts |
|---|---|---|---|---|---|---|
| 1 | NFO (A) | 0 | 0 | 0 | 0.00 | 0 |
| 2 | BRE (H) | 0 | 0 | 0 | 0.00 | 0 |
| 3 | BHA (A) | 0 | 0 | 0 | 0.00 | 0 |
| 4 | NEW (H) | 0 | 0 | 0 | 0.00 | 0 |
| 5 | CRY (H) | 0 | 0 | 0 | 0.00 | 0 |
| 6 | ARS (A) | 0 | 0 | 0 | 0.00 | 0 |
| 7 | MUN (H) | 0 | 0 | 0 | 0.00 | 0 |
| 8 | SUN (A) | 0 | 0 | 0 | 0.00 | 0 |
| 9 | BOU (A) | 0 | 0 | 0 | 0.00 | 0 |
| 10 | TOT (H) | 1 | 0 | 0 | 0.00 | 1 |
Data — · Model —. FPL projections are estimates, not guarantees. How the model works · Spread betting model · Free bet offers