How Fifa Ratings Are Calculated

Calculate how FIFA determines player ratings based on performance metrics, position, and other factors.

FIFA ratings are the backbone of EA Sports’ FIFA video game series (now EA Sports FC), determining how players perform in-game. These ratings aren’t arbitrary—they’re calculated through a complex system that evaluates real-world performance, potential, and numerous other factors. This guide explains exactly how FIFA ratings are determined, what metrics matter most, and how you can predict a player’s rating using our interactive calculator.

The FIFA Rating System Explained

FIFA ratings range from 40 to 99, with 99 being the highest possible score reserved for the world’s absolute best players (like Lionel Messi and Cristiano Ronaldo in their primes). The calculation process involves:

1. Data Collection: EA Sports partners with Opta Sports and other data providers to gather over 300 performance metrics per player.
2. Position-Specific Weighting: Attributes are weighted differently based on position (e.g., pace matters more for wingers than goalkeepers).
3. Algorithm Processing: A proprietary algorithm (updated annually) calculates the final rating.
4. Human Review: EA’s team of 9,000+ data reviewers (including ex-players and scouts) manually adjust ratings for accuracy.
5. Dynamic Updates: Ratings are updated weekly during the season based on real-world performances.

Key Components of a FIFA Rating

Component	Weight (%)	Description
Technical Skills	40%	Dribbling, passing, shooting, ball control (position-dependent)
Physical Attributes	25%	Pace, strength, stamina, jumping, aggression
Mental Attributes	20%	Vision, composure, positioning, reactions
Reputation	10%	Club/international reputation, trophies won
Form	5%	Recent performance (last 6-12 months)

Position-Specific Rating Calculations

Not all attributes are equal. A striker’s shooting is weighted more heavily than a defender’s, while a goalkeeper’s reflexes matter more than their pace. Below is how weightings differ by position:

Outfield Players

Position	Top 3 Attributes	Weight (%)	Example Player
Striker (ST)	Shooting, Pace, Dribbling	35%, 25%, 20%	Erling Haaland (91)
Winger (LW/RW)	Pace, Dribbling, Crossing	30%, 25%, 15%	Mohamed Salah (90)
Central Midfielder (CM)	Passing, Vision, Stamina	30%, 20%, 15%	Kevin De Bruyne (91)
Center Back (CB)	Defending, Physical, Positioning	35%, 30%, 15%	Virgil van Dijk (89)
Full Back (LB/RB)	Pace, Defending, Stamina	30%, 25%, 20%	Trent Alexander-Arnold (87)

Goalkeepers (GK)

Goalkeepers are evaluated on a completely different set of attributes:

• Reflexes (30%) — Ability to react to shots.
• Diving (25%) — Reach for saves.
• Handling (20%) — Ability to catch/hold the ball.
• Positioning (15%) — Being in the right place.
• Kicking (10%) — Distribution skills.

Example: Thibaut Courtois (90 OVR) excels in reflexes (94) and diving (90) but has weaker kicking (78).

How Potential Ratings Are Calculated

Potential ratings predict a player’s future ability (usually 3-5 years ahead). EA uses:

1. Age: Younger players (16-21) have higher potential growth.
2. Current Ability: Higher current ratings limit potential upside.
3. Position: Some positions (e.g., GK) peak later than others (e.g., ST).
4. Club Training: Elite academies (e.g., La Masia, Ajax) boost potential.
5. Real-World Hype: “Wonderkids” (e.g., Jude Bellingham, Pedri) get potential boosts.

Age	Max Potential Growth	Example
16-18	+20 to +30	Kylian Mbappé (72 → 94)
19-21	+10 to +20	Phil Foden (76 → 90)
22-24	+5 to +10	Declan Rice (78 → 86)
25+	+1 to +5	Harry Kane (86 → 89)

The Role of Real-World Performance Data

EA Sports relies on over 300 data points per player, sourced from:

• Opta Sports: Tracks passes, shots, tackles, and more (source).
• InStat: Provides video analysis for scouting.
• FIFA/UEFA Stats: Official match data from governing bodies.
• Scout Networks: EA employs 9,000+ reviewers worldwide.

Key metrics include:

• For Attackers: Goals, assists, xG (expected goals), shot accuracy.
• For Midfielders: Pass completion, key passes, tackles, interceptions.
• For Defenders: Tackle success %, clearances, aerial duels won.
• For Goalkeepers: Save %, clean sheets, sweeper actions.

Example: How Erling Haaland’s 91 Rating Was Calculated

In FIFA 23, Erling Haaland received a 91 OVR based on:

• Shooting (93): 36 goals in 35 Premier League games (2022-23).
• Pace (90): Elite sprint speed (36.2 km/h recorded).
• Physical (95): 1.94m height + 88kg strength.
• Reputation (5/5): Champions League winner + Ballon d’Or nominee.
• Form (10/10): Dominant debut season at Man City.

His potential was capped at 95 due to his age (22) and already-high current rating.

Common Misconceptions About FIFA Ratings

Despite EA’s transparency, myths persist:

1. “Ratings are just based on popularity.”
   Reality: Data drives 80% of the rating; reputation accounts for only 10%. Example: Karim Benzema was underrated for years despite his Real Madrid success.
2. “Young players always have high potential.”
   Reality: Potential is tied to real-world development. Many “wonderkids” (e.g., Fred from Shaktar) never reach their predicted ceilings.
3. “Ratings update instantly after good performances.”
   Reality: EA uses a 6-12 month rolling average. A single hat-trick won’t change a rating overnight.
4. “Physical attributes are the most important.”
   Reality: For technical players (e.g., Messi, Iniesta), dribbling and vision matter more than pace or strength.

How to Improve a Player’s FIFA Rating

For real-world players (or Career Mode managers), focus on:

For Outfield Players

1. Consistent Performance: High ratings in key metrics (goals for ST, tackles for CB).
2. Trophy Wins: Domestic leagues, Champions League, or international tournaments boost reputation.
3. Big-Match Performances: Scoring in derbies or UCL finals carries more weight.
4. Versatility: Players who excel in multiple positions (e.g., Joshua Kimmich at CM/RB) get bonuses.
5. Avoid Injuries: Frequent injuries (e.g., Daniel Sturridge) lead to physical attribute penalties.

For Goalkeepers

• High save percentage (75%+).
• Consistent clean sheets in top leagues.
• Strong distribution (for modern “sweeper-keepers”).
• Big-game performances (e.g., Emiliano Martínez in the 2022 World Cup).

The Future of FIFA Ratings: AI and Machine Learning

EA is increasingly using AI-driven models to predict ratings. According to a Stanford University study on sports analytics, future FIFA ratings may incorporate:

• Biometric Data: Real-time fatigue tracking via wearables.
• Tactical AI: Evaluating a player’s adaptability to different formations.
• Predictive Potential: Machine learning to forecast career trajectories.
• Fan Sentiment Analysis: Social media buzz as a minor factor.

Example: Jude Bellingham’s rapid rise from 77 OVR in FIFA 20 to 88 in FIFA 23 was predicted by AI models analyzing his Bundesliga and Champions League data.

Frequently Asked Questions

1. Why do some players have the same overall rating but different stats?
   Overall ratings are weighted averages. A CB and ST with 85 OVR will have vastly different attribute distributions.
2. How often are ratings updated?
   Major updates occur twice yearly (pre-season and winter). Dynamic updates happen weekly for inform cards.
3. Do international performances matter more than club performances?
   Yes, but only at the highest levels (World Cup, Euros). A strong league season (e.g., Premier League) carries more weight for most players.
4. Why do some young players have lower ratings than expected?
   EA often conservatively rates young players (e.g., Gavi was 76 OVR in FIFA 22 despite his breakthrough) to account for potential stagnation.

Expert Sources and Further Reading

For deeper insights, explore these authoritative resources:

• FIFA Official Statistics — Real-world performance data used in ratings.
• UEFA Technical Reports — Tactical analysis influencing player attributes.
• MIT Sloan Sports Analytics Conference — Research on data-driven player evaluation.