Pes 4 Database (2025)

PES 4 Database — Overview and Guide

Part 3: The Hidden Gems – Master League Bargains

The true longevity of the PES 4 database lies in the Master League mode. Scouts would generate young players, but the database included real-life future superstars who were teenagers in 2004, available for pennies.

The Complete Guide to the PES 4 Database: Rosters, Legends, and the Last Great "Old School" Masterpiece

Release Date: November 2004 (Europe) / August 2005 (North America, as World Soccer: Winning Eleven 8 International) Developer: Konami Computer Entertainment Tokyo (KCET)

In the pantheon of football video games, few entries command the respect and nostalgia of Pro Evolution Soccer 4 (PES 4). For many fans, this was the title that perfected the balance between arcade fun and football simulation. It was the last game before the next-gen consoles (Xbox 360/PS3) changed the landscape, and crucially, it was the final PES to feature many legendary players in their absolute prime.

Today, the PES 4 database is more than just a list of names and numbers. It is a time capsule, a tactical bible, and a source of endless fascination for modders, retro gamers, and football historians.

This article provides an exhaustive breakdown of the PES 4 database—covering its structure, the legendary players, hidden gems, iconic teams, and why it remains the gold standard for football game data 20 years later.

Use Cases

If you want, I can:

(Reminder: specify platform if you want a precise tool list or a sample file.)

The request for a "PES 4 database" paper appears to refer to Pro Evolution Soccer 4 (PES 4)

, a classic football simulation video game. In the context of game research or data analysis, a "database" typically refers to the player attributes, team rosters, and historical stats contained within the game's files.

Below is a structured "paper" summarizing the technical and historical significance of the PES 4 database. Technical Analysis: The PES 4 Player and Team Database 1. Introduction Released in 2004, Pro Evolution Soccer 4 (known as Winning Eleven 8

in Japan) marked a significant leap in sports simulation through its expanded database. It was the first in the series to include licensed leagues (Eredivisie, Serie A, and La Liga), which necessitated a more robust and detailed data structure to manage thousands of authentic player profiles. 2. Database Structure and Data Points

The PES 4 database functions as a relational collection of attributes. Each player record consists of over 30 distinct variables, categorized to influence in-game physics and AI behavior: Physical Attributes: Height, weight, age, and "footedness."

Performance Stats: Precision values for speed, acceleration, shot power, and stamina (rated 1–99). pes 4 database

Special Abilities: "Star" traits like "Middle Shooting," "Playmaking," or "1-on-1 Scoring" that trigger specific animations or AI logic.

Condition/Consistency: Hidden variables determining the "arrow" direction (form) before a match. 3. Evolution of Scouting and Accuracy

During this era, the PES database was curated by a dedicated network of researchers and fans. This manual data entry resulted in:

Cult Icons: Certain players, like Adriano (Inter Milan) or Obafemi Martins, became legendary due to high "Shot Power" or "Speed" stats that exceeded their real-world counterparts, a phenomenon often discussed in gaming retrospectives.

Dynamic Data: The introduction of the "Master League" growth system allowed the database to be dynamic, with player stats evolving over simulated seasons based on age-related decline or development curves. 4. Impact on Modern Game Design

The PES 4 database established the blueprint for modern "Option Files"—user-generated database edits that allow the community to bypass licensing restrictions by manually updating team names, kits, and stats. This community-driven database management remains a cornerstone of the series' longevity. 5. Conclusion

The PES 4 database was more than a list of names; it was a complex mathematical engine that defined the gameplay "feel." Its balance of realistic attributes and "arcade-style" power players created a competitive meta-game that many fans still consider the pinnacle of the series.

If you are looking for a complete player database for Pro Evolution Soccer 4

(PES 4), several online archives maintain detailed lists of player stats, real names, and hidden attributes extracted from original game files. Core Database Attributes

A typical PES 4 database text file includes the following data fields for each player: ID, Name, Age, Height, Weight, Nationality, and Foot. Primary Stats:

Attack, Defence, Body Balance, Stamina, Top Speed, Acceleration, and Response. Technical Skills:

Dribble Accuracy/Speed, Short/Long Pass Accuracy/Speed, Shot Accuracy/Power/Technique, and Free Kick Accuracy. Special Traits: PES 4 Database — Overview and Guide Part

Header, Jump, Technique, Mentality, Teamwork, Consistency, and Condition. Top Rated Players in PES 4

According to historical database records, the highest-rated players (Overall Rating 90+) typically include classic legends and prime stars of the 2004–2005 era: Thierry Henry : Often ranked at the top for pace and finishing. (Inter Milan)

: Renowned for having one of the highest shot power ratings (99). Zinedine Zidane (Real Madrid) : Peak technical and passing stats. Oliver Kahn Gianluigi Buffon

: The leading goalkeepers with high response and keeper skill values. Database Resources & Tools Online Searchable DB: Sites like WEPESStats

allow you to filter the full PES 4 roster by team, nationality, or specific stats like speed or jump. Correct Name Lists:

Because PES 4 lacked certain licenses, databases often provide "Correct Name" text files to replace fake names (e.g., changing " Naldarinho Ronaldinho Editing Tools: For PC users, the database is often managed via an Option File

(EDIT00000000). Specialized "PES 4 Editors" are used to export these stats into CSV or TXT formats for external viewing. list of players from a particular team, or are you looking for a on how to edit the database files? Pro Evolution Soccer 4 Database

Introduction

The PES 4 (Player Evaluation System 4) database is a comprehensive repository of data used to evaluate and analyze player performance in various sports, particularly football (soccer). The database contains a vast array of data points, including player statistics, team performance metrics, and scouting reports. This report provides an overview of the PES 4 database, its features, and its applications.

Database Structure

The PES 4 database is structured into several modules, each focusing on a specific aspect of player evaluation:

  1. Player Master Database: This module contains detailed information on over 100,000 players worldwide, including their biographical data, career history, and current team affiliations.
  2. Performance Database: This module stores a vast array of performance metrics, including:
    • Match-by-match statistics (e.g., goals scored, assists, tackles won)
    • Seasonal statistics (e.g., total goals, assists, appearances)
    • Advanced metrics (e.g., expected goals, expected assists, passing accuracy)
  3. Scouting Database: This module contains scouting reports on players, including:
    • Technical abilities (e.g., dribbling, passing, shooting)
    • Physical attributes (e.g., speed, strength, agility)
    • Tactical awareness and positioning
  4. Team Performance Database: This module stores team-level performance metrics, including:
    • Match-by-match results and statistics
    • Seasonal standings and statistics
    • Team possession and passing statistics

Key Features

The PES 4 database offers several key features that make it a valuable resource for football clubs, scouts, and analysts:

  1. Advanced Data Analysis: The database provides a range of advanced metrics and statistical models to analyze player and team performance.
  2. Customizable Reporting: Users can create custom reports and dashboards to focus on specific areas of interest.
  3. Scouting Tools: The database includes a range of scouting tools, including player comparison and identification of potential transfer targets.
  4. Integration with Other Systems: The PES 4 database can be integrated with other systems, such as video analysis software and talent identification platforms.

Applications

The PES 4 database has a range of applications across the football industry:

  1. Talent Identification: Clubs and scouts use the database to identify top talent and potential transfer targets.
  2. Player Evaluation: Coaches and analysts use the database to evaluate player performance and develop strategies for improvement.
  3. Team Building: Clubs use the database to build and optimize their squads, identifying areas of strength and weakness.
  4. Broadcasting and Media: Media outlets use the database to provide insightful commentary and analysis during matches.

Conclusion

The PES 4 database is a powerful tool for football clubs, scouts, and analysts. Its comprehensive data and advanced features make it an essential resource for evaluating player and team performance. As the football industry continues to evolve, the PES 4 database is likely to play an increasingly important role in shaping decision-making and strategy.

Recommendations

Based on this report, we recommend:

  1. Regular Updates: Regularly update the database to ensure data accuracy and relevance.
  2. Training and Support: Provide training and support for users to maximize the database's potential.
  3. Integration with Other Systems: Explore opportunities to integrate the PES 4 database with other systems and tools.

Limitations

This report has several limitations:

  1. Data Quality: The accuracy and completeness of the data in the PES 4 database depend on various factors, including data collection methods and sources.
  2. Scope: The report focuses on the PES 4 database and its applications in football, but does not consider other sports or industries.

Future Research Directions

Future research could explore:

  1. Data Visualization: Developing innovative data visualization techniques to communicate complex data insights.
  2. Machine Learning: Applying machine learning algorithms to predict player and team performance.
  3. Comparative Analysis: Comparing the PES 4 database with other player evaluation systems.

Best Practices

2.2 Data Categories

| Field | Example Values | Storage Type | |-------|----------------|---------------| | Identity | Name, Shirt Name, Face ID | String / Hex Pointer | | Technical | Attack, Defence, Balance, Stamina | Integer (0–99) | | Speed | Accelerate, Top Speed, Agility | Integer (0–99) | | Power | Shot, Jump, Header, Kicking Power | Integer (0–99) | | Psychology | Consistency, Condition, Weak Foot Accuracy | Integer (1–8) | | Special Abilities | Dribbling, Positioning, Playmaking, 1-touch Pass | Boolean flags (0/1) | Use Cases