What a window counts
Hit rates count the most recent completed games, newest first — reaching back into earlier seasons when the current one is short, and into games for a previous club, including in another league we cover.
All markets last 10 games
Compared with an Eredivisie forward, 25/26, 2,950 appearances
Five selections from the player report, free in your inbox
Picked from 298 selections across 77 matches on this week’s slate, each with its record and the market price.
Confirmed by a link. Unsubscribe in one click. Or open the player report.
Over the last 10 Eredivisie games, Miguel Rodríguez has hit 1+ shot on target in 50% (5 of 10), 1+ total shot in 80%, 1+ foul committed in 60%, 1+ foul won in 80%, and been booked in 20% (2 of 10). These are raw hit rates from completed matches, not odds.
Comparable wingers
Miguel Rodríguez has no Eredivisie record yet, so this profile is drawn from the UEFA Europa League 25/26 season. These are the closest 5 Eredivisie wingers by standing within their own league — not by matching output, which does not carry across leagues. A reference for the rates above, not a forecast.
| Player | Apps | Shots/90 | Fouls/90 |
|---|---|---|---|
| Miguel RodríguezDeportivo AlavésUEFA Europa League | 8 | 1.90 | 2.04 |
| Yoann CathlineFC Utrecht | 8 | 2.40 | 1.48 |
| Anis Hadj MoussaFeyenoord | 7 | 3.21 | 0.58 |
| Ruben van BommelPSV Eindhoven | 8 | 2.71 | 2.20 |
| Mathis SurayGo Ahead Eagles | 8 | 1.93 | 0.90 |
| Ivan PerišićPSV Eindhoven | 8 | 2.64 | 0.53 |
| These 5, combined | 2.56 | 1.11 |
No close match — the nearest profile sits well outside the usual range, so read these five as the closest available rather than as like-for-like.
Recent matches
The last 10 games Miguel Rodríguez featured in — minutes and the counts that settle these markets.
| Match | Min | SoT | Shots | Fouls | Won | Tck | Cards |
|---|---|---|---|---|---|---|---|
| @ Heracles Almelo6 Mar | 22 | 0 | 0 | 0 | 2 | 0 | 0 |
| AZ Alkmaar1 Mar | 13 | 1 | 1 | 1 | 0 | 0 | 0 |
| @ FC Groningen14 Feb | 28 | 0 | 1 | 0 | 2 | 2 | 0 |
| Feyenoord8 Feb | 17 | 1 | 1 | 2 | 1 | 0 | 2 |
| @ SC Heerenveen1 Feb | 18 | 1 | 2 | 0 | 2 | 0 | 0 |
| Sparta Rotterdam25 Jan | 90 | 0 | 5 | 3 | 4 | 0 | 0 |
| @ FC Volendam18 Jan | 87 | 1 | 2 | 2 | 2 | 1 | 1 |
| PSV Eindhoven21 Dec | 90 | 0 | 5 | 0 | 2 | 3 | 0 |
| @ NAC Breda14 Dec | 68 | 0 | 0 | 1 | 2 | 1 | 0 |
| FC Twente7 Dec | 90 | 1 | 2 | 1 | 0 | 2 | 0 |
Raw counts from every match on record, across 6 current Eredivisie officials — the model applies each official's overall card tendency, not this split. All Eredivisie referees
Frequently asked
How often does Miguel Rodríguez have a shot on target?
Over the last 10 Eredivisie games, Miguel Rodríguez has hit 1+ shot on target in 50% (5 of 10). That's the raw hit rate from completed matches; SharpXI's model turns it into a true probability by adjusting for the opponent and expected minutes, then compares it with the bookmaker's price as offered.
How many shots on target does Miguel Rodríguez average?
Across the last 10 Eredivisie games, Miguel Rodríguez is averaging 0.86 shots on target and 3.27 total shots per 90 minutes. SharpXI treats that as a starting rate, then adjusts for the opponent and expected minutes before pricing a 1+ or 2+ line.
How often does Miguel Rodríguez get booked?
Miguel Rodríguez is averaging 0.52 cards per 90 over the last 10 games. Bookings swing heavily on the referee, so the model multiplies a player's base rate by each official's card tendency — the biggest single lever in the to-be-carded market.
Does Miguel Rodríguez commit or win more fouls?
Over the last 10 games Miguel Rodríguez commits 1.72 fouls per 90 and wins 2.93 — winning more than committing. Fouls committed and fouls won are separate markets, each modelled from the player's rate and the opponent faced.
Which player markets does SharpXI model for Miguel Rodríguez?
Shots on target, total shots, fouls committed, fouls won and to be carded — each as a true probability, compared with the bookmaker's price as offered. Miguel Rodríguez plays as a forward.
Rates shown are raw counts from public match data for context; the model adds shrinkage, opponent and referee factors before flagging value, and compares against the bookmaker's price as offered — player markets are priced one side only, so that price still carries the bookmaker's margin. 18+ — please gamble responsibly.