Behind every goal, every save, and every pass are numbers and insights that can be broken down using metrics to better understand what’s happening on the field. This comprehensive guide explores the 10 essential data points for understanding modern football analytics.
What is Soccer Data? Soccer Analytics Dataset: The Foundation of Football Performance
You’ve probably found yourself wanting to know how many shots a player took in a match, how many tackles they made, or how many saves a goalkeeper recorded. All of this information falls under the umbrella of soccer data — also known as analytics.
For several years now, professional clubs and their staff have integrated data analysis into their daily operations. Whether it’s to prepare for a match, assess a player, or recruit new talent like a scout, data offers objective and precise insights.
Tools like Wyscout, Opta, and StatsBomb allow analysts to examine every aspect of the game:
- Offensive efficiency, through metrics like xG and chances created
- Defensive solidity, assessed via xGA and duels won
- Physical commitment, measured by distance covered and intensity of efforts
By the end of this article, you’ll understand the key metrics data analysts use today to help shape tactical decisions and player evaluation in professional football.
1. xG (Expected Goals)
Expected Goals (xG) determine how likely a shot is to score. This measure is computed using machine learning models based on past data and considering a number of elements:
- Shot placement on the pitch
- Angle toward goal
- Body components employed: strong foot, weak foot, head
- Type of assist (rebound, cross, cross, set piece, through ball)
- Defensive pressure and goalkeeping positioning
Why is xG essential?
xG aids in evaluating chance quality as opposed to just quantity. For instance, if a team only scores once despite 2. 5 xG per game on average, it could either indicate inadequate finishing or outstanding opposition goalkeeping. On the other hand, a clinical finisher such as Erling Haaland shows outstanding conversion rates since his xG (27. 4 in 2023-24 according to StatMuse)
2. xGA (Expected Goals Against)
Expected Goals Against (xGA) calculates the expected number of goals a team should concede based on the quality of chances faced.
- A well-organized defensive structure will have a low xGA
- A team facing many high-quality scoring opportunities will have a high xGA
Why is xGA essential?
xGA exposes weaknesses in defense and shows how well pressing works. Manchester United’s xGA of 65. 53 throughout the 2023–24 Premier League season, for instance, clearly showed major defensive vulnerabilities throughout their campaign.
3. xA (Expected Assists)
Expected Assists (xA) measure the probability that a given pass will result in a goal. This advanced metric accounts for:
- Pass accuracy and placement
- Angle and distance of the key pass
- Defensive pressure on the recipient
A well-executed through ball or precise cross will have a high xA, while a short sideways pass will have a minimal xA value.
Why is xA essential?
xA evaluates creative players’ contributions to chance creation — even when they don’t register a direct assist. For example, Lionel Messi recorded an xA of 15.24 during the 2022-23 season with PSG (per Understat), highlighting the quality of chances he generated for teammates.
4. Goals Per Match (GPM)
Over a given time, Goals Per Match (GPM) reveal the average number of goals scored or lost by a player or team.
- A high GPM means a strong offense
- A low GPM indicates a struggling attack
Why is GPM essential?
An intuitive standard for evaluating offensive efficiency and clinical finishing is it. Los Angeles FC averaged 1. 84 goals per game in the 2023 MLS season, for instance, pointing to regular and effective attacking play.
5. Goal Difference (GD)
Goal Difference shows the goal scored and conceded gap over a time period.
- A good goal difference shows general domination.
- A negative difference indicates flaws in defence or assault.
Why is Goal Difference essential?
GD offers a top-level perspective on a team’s general performance and composition quality. Inter Milan’s +67 goal differential (89 scored, 22 conceded) in 2023–24 demonstrates their tactical dominance over both phases of play.
6. PPDA (Passes Per Defensive Action)
Passes Per Defensive Action (PPDA) measures how intensely a team presses. It calculates the average number of passes an opponent can make before a defensive action (tackle, interception) is attempted.
- A low PPDA reflects high pressing intensity — like Liverpool under Klopp
- A high PPDA suggests a more passive defensive setup
Why is PPDA essential?
PPDA helps explain a team’s pressing strategy. In the 2023–2024 Premier League season, Liverpool had a PPDA of 9.9 (per The Analyst), confirming their aggressive gegenpressing approach.
7. OPPDA (Opponent Passes Per Defensive Action)
Opponent PPDA (OPPDA) tracks how well a team handles pressing from opponents. Unlike PPDA, which evaluates a team’s press, OPPDA looks at how much pressure a team faces.
- A low OPPDA means the team is rarely pressed
- A high OPPDA suggests vulnerability to high pressing
Why is OPPDA essential?
This metric helps gauge how well a team responds to pressure — crucial for understanding tactical decisions in possession-based systems.
8. Distance Covered
Distance Covered reflects the physical output of players during a match, especially at high intensity.
- Players often cover 10–12 km per game
- High-intensity runs (>25 km/h) indicate explosiveness and transition effort
Why is this metric essential?
It helps technical staff assess player fitness and stamina — and can also flag potential injury risks from overexertion.
9. Duel Win Rate
Duel Win Rate counts the frequency of direct encounters between a player or team across various conditions
- Defensive duels: tackles, blocks, interceptions.
- Aerial duels: aerial fights and headers
- Offensive duels: 1v1 scenarios and deft dribbles
Why is it essential?
Coaches use this indicator to exactly adjust tactical strategies depending on personal conflicts and physical match-ups. Christian Benteke, for instance, won 124 aerial duels for D. C. United in the 2024 season, therefore proving his direct play and physical ability.
10. Big Chances Created
Big Chances Created (BCC) measures the number of high-quality scoring opportunities generated by a player or team. This includes both:
- Direct assists
- Key passes leading to clear-cut chances
Why is this metric essential?
It identifies players with the creativity and vision to break down organized defenses. According to OptaPro, Lionel Messi has created a big chance every 90 minutes over the last five years — demonstrating elite playmaking ability and chance creation consistency.
Summary Table of Key Soccer Metrics
| Soccer Metric | Definition | Purpose |
|---|---|---|
| xG (Expected Goals) | Probability that a shot results in a goal, based on position and context | Evaluates offensive efficiency and chance quality |
| xGA | Expected goals conceded based on opponent shots | Measures defensive strength and risk |
| xA | The probability that a pass leads to a goal | Gauge creativity and playmaker impact |
| GPM (Goals/Match) | Average goals scored or conceded per game | Reflects offensive or defensive productivity |
| AVG (Goal Average) | Goal difference (goals scored – goals conceded) | Provides an overall performance overview |
| PPDA | Average opponent passes allowed before a defensive action | Measures pressing intensity |
| OPPDA | Passes allowed under pressure from opponents | Assess the ability to handle pressing |
| Distance Covered | Total distance (in km) a player or team runs | Tracks physical commitment and fitness |
| Duel Win Rate | Percentage of duels won (defensive, aerial, offensive) | Evaluates strength in direct confrontations |
| Chances Created | Total actions leading to shots or goals | Measures creative contributions |
Advanced Analytics and Its Usage in Modern Football
Though these ten indicators represent the most often used metrics, technological developments are driving the world of football analytics to change. Tracking data, computer vision, and machine learning breakthroughs yield new metrics every day.
Clubs and data analysts get a much more thorough grasp of the beautiful game by integrating these analytical techniques with conventional scouting methods and leveraging comprehensive databases. The data-driven approach of contemporary football guarantees that objective analysis supports tactical decisions, hence providing teams the competitive advantage necessary at the highest level.
