Professional teams have been using data to aid the opposition analysis process for a number of years now. As data becomes cheaper, more accurate, and knowledge of how it can impact pre-game preparations increases, we’re seeing amateur, semi-professional and college teams begin to use it too.


There’s many advantages to using data in the scouting process. These include:

     

      • Many games can be incorporated into a report in relatively little time compared to watching them.

      • Every event is recorded, which would be impossible for the human brain to remember.

      • There is no bias in the numbers


    On the other hand data does have its shortcomings, and if used incorrectly can be detrimental to a team’s preparations. Almost all match data lacks and subjectivity and context around some events.

    For example, lots of data providers don’t include any information about the number of defenders inside the box at the time of an incomplete cross. And without watching video or having tracking data and a world-class data model, nobody can say confidently whether the decision to cross was a good one.

    Standard event data (passes, shots etc.) only shows what happens to the ball, and doesn’t not record events that don’t happen. For example, it won’t tell you if a fullback doesn’t track his runner on a cross to the back post, or if a player loses his man on a corner kick.

    When we use data it’s important to constructively ask critical questions and attempt to provide context to statistics. For example, if a team crosses more than most others we may want to include this in a report to our Head Coach. But if in fact one player on this team leads the league in crossing, and the rest cross at an average rate, this could make a huge difference to our preparations, especially if this player is injured or suspended.

    In this instance a good base of soccer-specific statistical knowledge is useful, but adding some realism and critical thinking about the realities of being a Coach will really boost the impact of the data.

    Here’s Philadelphia Union General Manager Ernst Tanner discussing the use of data in their processes:

     

     

    A report that includes some key statistics as well as traditional video or live scouting is becoming more prevalent in the modern game.

    For the task for this module we’re going to use Stats Perform data to profile two contrasting teams in attack.

    Please download the task document and excel spreadsheet below and work through the task.

    Attacking Profiles Task
    Attacking Profiles Task Data

    Once this task is complete, please record the findings in the comments section below along with any thoughts on the use of data in analyzing attacks.

    Responses

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    1. Very contrasting styles in the next two matches:

      NYCFC – Risk-averse in the possession, using high-volume, low-risk passes to create scoring opportunities, with a minimal emphasis on long passes, including crosses and finishes. They are very proficient with their passing retention and shot quality, but could struggle if forced to play direct.

      Houston – Will look to play forward passes often, particularly in the final third with crosses. They are very proficient in the air and will aim to create a high volume of chances via headers, but should not aim to have large amounts of possession or complete a high percentage of their passes in comparison to many of our other opponents. Defensively, we may need to prepare to have more defensive numbers in goal-scoring areas to counter their high number of shots from close to goal.

      Data is a great metric to use alongside other analytic tools. While it make lack certain nuance in regards to common in-game actions, it provides a great framework for understanding a team’s philosophy in their attack.

    2. When playing New York City:
      – expect them to possess the ball
      – expect them to cross less than most opponents and
      – mostly retain possession in the final third to work the ball into the box

      When playing Houston
      – expect them to be direct in possession,
      – expect them play long balls
      – expect them to cross the ball often and attempt shots from headers

    3. New york city is a possesion based side that patiently wotk the ball into opposition final third
      Houston Dynamo is a direct side that look to create chances through crosses and posses aerial threat.

    4. Data is increasingly used in football to analyze player performance, team strategy, and game outcomes. Teams use data to identify player strengths and weaknesses, track player progress, and make informed decisions about player recruitment and development. Data analysis can also help teams optimize their game strategies by identifying patterns and trends in player and team performance.
      Here New york fc play a possession game with high range of passes and building game by shots passes and attacking inside the box giving them option for more shots on target.
      Houston playing style is counter attacking with less passes and relying on more crosses and indirect passes having a high range of head goals.

    5. The data shows the most passing teams, the most cross-players, the most possession, or depending on direct play…
      Data is really very important

    6. Houston: possesses the ball more, less crosses
      New York: more direct in their style of play, more crosses

    7. Houston Dynamo: Favors playing long, direct passes; their strength is in crosses and box-to-box headers. They are among the lowest five in the league for total passes because this style does not call for many passes.
      New York City: They keep possession and play a lot of shots, most of which are on target, with a high proportion of ball retention in the attacking third. They play indirect short passes and aim to move opponents about with these passes.

    8. Data combined with Excel or any other Database software or statistical software can be used to compare and find high or low performers . you can also see patterns or find strenghts and weakness of teams or individuals

    9. Data is becoming very important in modern Football and making the managers job easier for example looking at Bretford and Brighton they are well know for using data and its shown by both of their league positions and recruitment that it is working efficiently

    10. Data has become very important in modern football because it provides important information with much easy and it saves time and resources

    11. Data has become a necessary tool in Football because gives us the opportunity to read and understand model games and playing styles. We must be accurate and ensure that we pick the right data according to our needs to play against our opponents. Only the more relevant is the key to successfully using data, and it can attach with video analysis.

    12. Using data in analyzing the opposition attack will likely reinforce the key principles or trends that are displayed in the game. In addition, the data will provide a complex level of detail with minimal effort and time. The data alone cannot provide the solutions. Data and video analysis are simultaneously needed in order to provide the best picture possible. I think it is also important to not let the data over complicate the report to the coach or the players. Their time and capacity is relatively limited. Therefore, the analysis report should only include the most important pieces. Too much data could cause confusion and become a huge distraction.