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# Expected Goals and Expected Assists

In this day and age, many coaches have changed their basic outlook towards the game and are more focused on advanced statistics to assess the growth of a player and the team as a whole. Since the scoreline of a match isn’t enough to measure their performance, the system of Expected Goals and Expected Assists is used for an in-depth analysis.

## What is Expected Goals (xG) ?

Expected goals(xG) tells us the quality of an attempt and its probability of finding the net, rather than the actual outcome of the shot.

## How is Expected Goals calculated?

It is calculated by comparing it to thousands of shots recorded earlier based on factors such as distance, position of defenders, type and speed of pass, type of shot, shot angles and various other aspects.

Putting it simply, each shot is assigned a particular value between 0 and 1, with 1 being the highest chance of scoring and 0 the lowest.

Say, if a player decides to take a long shot from outside the box, then its probability of finding a way past the keeper would definitely be less than 1, maybe even less than 0.1 based on past data for similar situations.

Similarly, if a player is provided with a chance to simply tuck in the ball, then the probability of scoring would be somewhere towards the upper limit, say 0.8 or 0.9.

However, even if a player is too close to the goal, the chance of scoring depends on various other factors such as the defenders’ reach, the pass the player receives and the power of the shot, thus lowering the value of xG considerably.

## What is Expected Assists (xA)?

The Expected assists(xA) basically assesses the creative output of a player by measuring the chance of a key pass becoming an assist. It depends on various factors such as the positioning of the finisher, the speed of the through ball, the kind of pass and other things.

According to Opta, the expected assists model is independent of whether a shot was taken and converted or not, but rather relies on the quality of the pass.

## How is Expected Assists(xA) calculated?

Expected Assists is calculated by relying on the quality of the chances created by the player rather than than the conversion rate. Hence, a player who may have a low number of assists throughout a season, can still have a high value of xA.

This analysis comes in handy when differentiating between players with the same number of assists, as the concept of xA allows us to see how many genuine chances had been created by a player irrespective of whether these chances ended up in the back of the net or not.

Thus one can conclude that the player with a higher xA value has been more consistent and thorough with his playmaking for a particular set of matches.

## What are the benefits of Expected Goals (xG) and Expected Assists (xA)?

The primary benefit of this feature is that it enables an analyst to make an accurate assessment of where a player was lacking in his technique such that it eventually led to him failing to score, thus providing a basis for improvement.

Many managers rely on data provided through Expected goals and Expected assists to mark the weaknesses of their team’s particular style of play which could prove to be problematic against a particular opponent.

## What is the importance of Expected Goals (xG) and Expected Assists (xA)?

Although football is a game which tries to resist change, the use of such modernized techniques is essential to help a player grow and reach his maximum potential.

The xG and xA metrics help us assess a player on a deeper level and avoid judging his skills based on simple statistics like goals and assists.

These methods have established a way to analyse the judgement and creativity of a player, going beyond the simple assessment techniques based on one’s perception of a players playing style and not on the thorough statistics. This is the reason behind these methods becoming an instant hit amongst football fanatics.

These metrics help assess the strengths and weaknesses of individuals, providing enough matter to help them work on their shortcomings, by providing them the data representing the flaws in their technique, which barred them from achieving their said target.

All in all, these new assessment methods of xG and xA have provided players the option to learn and work on themselves by keeping a constant track of their mistakes and positive points, thus enhancing their productivity considerably.

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