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.
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.
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.
Houston Dynamo:
They are in the top five percentile of passes forward and long balls , this shows that Dynamo like to play a more direct game, particularly in wide areas as they are also in the top fiver percentile for total crosses and cross/pass percentage. Which in turn proves why they are also in the top 5 percentile for headed shots (2.64 p/g). However they are in the bottom five percentile in total passes attempted and passing percentage, which shows that they are a low possession team, they look to cross the ball into the box rather than attempt a 1 v 1 or take a shot from distance.
New York City FC:
The data shows that they are in the top five percentile of total passes attempted and passes, passes in the final third, 1 v 1 into the box, and shots on target which presents that they are a high possession team and like to keep the ball. Being in the bottom five percentile in passes forward, cross/pass and headed shots shows that they do not look to play direct or take the risk of losing the ball through a long ball, or a cross inside the box.
With the use of this data, we are able to foresee how an opponent is likey to play without watching the game film.
Houston Dynamo:The first thing that jumps out from the statistics is the amount of crosses combined with the % of longer passes and average pass distance. These metrics combined really highlights that the Dynamo were a direct team who did not want to break teams down utilizing possession. On the opposite end of the spectrum, the Dynamo are ranking towards the bottom in terms of total number of passes and 1v1 duels. This highlights the lack of technical ability, most likely in their central midfield.
It’s interesting when you look at the roster from 2016, it confirms what the statistics painted. The Dynamo utilized target forwards such as Will Bruin, Mauro Manotas, and a wide target man, Andrew Wenger, who lack technique but were good at attacking crosses. Couple these players with USMNT international left back Damarcus Beasley, and you see that they wanted to utilize his crossing ability. It did not help that this was also a season of upheaval with head coach Owen Coyle getting sacked halfway through the season. With the interim coach not having the license to change too much, they were left utilizing Coyle’s lacking squad.
NYCFC:NYCFC was one of the original ventures for City Football Group in their multi-club model. It goes to show that they built a squad that fits their ethos of play. This was a team that ranked at the top of completed passes, passing completion, and completed passes in the final third. These statistics show that they were a team that wanted to use possession to break down opponents. For CFG, they know that crosses and longer passes lead to lower percentage completion, so they look to avoid these as much as possible. Their squad is built upon players who are highly technical and tactically astute.The data shows that teams ended up figuring this out because in terms of shots taken, they were near the furthest away from goal for their average shot. They probably have to utilize some longer shots from time to time to draw out their opponent and open space for their attacking players in the final third.
Let’s start with New York City :
-The data makes you imagine that this team is coached by Pep Guardiola ! It demonstrates that they are a team that relies heavily on ball possession (High Percentage of Total Passes Attempted), whose players always look to keep the ball on the floor (Low Percentage of Long Balls and Headed Shots), are very patient and do not rush to attempt on goal (Low Percentage of Passes Forward), and are most of the time facing low blocks (High Percentage of Final Third Passes), trying to break them down and move them out of position through passing and keeping possession for long periods of time (High Percentage of Passing, Low Percentage of Forward Passes).
But at the same time, they seemingly attempt a lot of shots far from goal (High Average Shot Distance) possibly because the low blocks they often face makes it hard for them to reduce the distance between their oppositions’ nets and their players.
Houston Dynamo :
-A direct team that always looks to play forward (High Percentage of Passes Forward), seemingly relies heavily on long balls towards the flanks where the ball gets crossed into the box for the attackers to head it into the net (High Percentage of Average Pass Distance, Long Balls, Total Crosses, Cross/Pass and Headed Shots). Apparently, the reason behind the coaching staff relying on this unentertaining and uninspiring style of play is probably because they don’t have quality players at their disposal (Low Percentage of 1v1 attempted).
Finally, i don’t think there’s much to be said about data’s usage more than what was said in this module, yes it’s important, and we were able to guess both teams’ style of play but at the same time, it’s simply not enough, or to be more accurate, it’s not detailed enough, take the data we just worked on for example, we don’t know the players positionning on the pitch, we don’t know which side they prefer to attack, which players play or receive the long balls etc, Data without context keeps you guessing and prevents you from making informed decisions.
NYCFC
Patient in possession, NYCFC is a team that prefers to dictate the tempo of the match by maintaining possession of the ball while minimally playing longer distance passes. With a majority of their goal scoring opportunities being created centrally and shots coming from further distances, defensively, it is key for teams facing NYCFC to not drop their last defensive line further than need be and to maintain vertically compact blocks.
HOUSTON DYNAMO
As for Houston, they are a team that is very direct in their approach with a high percentage of forward and long passes. Their playing style is dependent on their midfielders being able to recover loose or second balls as well as players operating in wide areas being able to find early crosses. Teams facing Houston should expect to have their backlines on the half turn, expecting to aerially win longer balls and possibly create a numerical superiority centrally in order to recover loose balls.
Regarding the use of data in analyzing attacks, while there is value in intuition and subjective opinions and assumptions, data is objective and can provide us with key details in determining tendencies and trends that opponents have when attacking and allows us to figure out a better way to defensively organize our teams as well as how we can prepare our teams in transition to attack.
The date shows that NYCFC like to possess the ball, are patient in going forward are good with getting shots on target as well as like to shoot from distance. They tend to keep the ball on the ground with short simple passes vs. longer pass.
Houston Dynamo are a direct longer passing team that likely get the ball wide and cross the ball into the box. They prefer this route over playing short simple high percentage passes or taking players on in 1v1 situations.
New York City is a more possession based team, completing a lot of shorter passes and taking less risks with the ball, not being afraid to go backwards. They look to play through the middle of the field and do not cross it often. They also take a lot of shots. The Houston Dynamo are far more direct, opting for more long passes which they complete a lower percentage of. They also look to cross as much as possible, resulting in a high number of head attempts on goal.
New York City – Possession-based team that keeps the ball on the ground and is indirect, taking fewer risks when passing, looking for ground passes rather than crosses (which results in fewer headers). More inclination than the average of their opponents.
Houston Dynamo – Direct team (less possession than average) with low passing accuracy and many long balls, creating chances through crosses (resulting in more headed shots),
NYCFC
Play a lower percentage of passes forward than most teams (indirect in possession):
Could be an opportunity to press them, make them uncomfortable and possibly win the ball higher up the field, Or opponent could sit in a mid block, conserve energy and wait to counter on a turnover, issue with that is long spells of defending could tire the team and when they do win the ball, they don’t have the energy to go forward
Have a high amount of total passes per game (possess the ball)
A high number of passes with a low % of forward passes will not be dangerous against an organized defensive unit, seems you wouldn’t be giving up a lot of high quality chances
High passing accuracy
If a lot of the passes are not forward, and its pass/pass/pass, this will not scare too many opponents and they will probably not give away a lot of quality chances
Have a low number of crosses compared to possession (cross/pass%)
Possession and an indirect style doesn’t lend for many crosses as its not a high percentage situation, they like high percentage passes and keeping the ball
Tend to shoot from further out than most teams
Makes sense if they are more about possession and keeping the ball and are not always looking to advance the ball and break lines
Few headed shots
For a team that likes to pass/pass/pass, crosses are low percentage, which would lend to less headed shots
Don’t play many long balls (long ball %)
An indirect possession team that looks to play safe passes will not look to play long direct balls to target players, it is not their style of play, they would rather play the safe, shorter pass
High share of final third passes compared to opponents
Their style is to pass/pass/pass, that style goes from back to front, maybe consider being a little more direct and look to take more chances on goal
Houston
Play a higher percentage of passes forward than most teams (direct in possession)
You will need to be organized defensively in the transition (Preventive defending), so a long ball doesn’t turn into a quick counter attack
Have a low amount of total passes per game (do not possess the ball)
Will need to be good at the chaos (winning 1st and 2nd balls), having good attacking structure, so in loss of possession, you are able to defend this direct style of play
Low passing accuracy
Long passes are less accurate, an opportunity to win the 1st/2nd balls, and dictate the pace and flow of the game
Attempt more crosses per game than most teams
Team is used to playing longer direct passes, so they will get ball into more advanced positions of the field to be able to get crosses into the box
Have a high number of crosses compared to possession (cross/pass%)
Very opposite of NYCFC, two very different styles, more direct play forward will get ball into advanced areas to have opportunities to cross
Shoot from closer to goal than most teams
More direct balls closer to goal will allow for more shots closer to the opponents goal
Many headed shots
Direct style, longer passes, more balls in the attacking 1/3, will allow for more balls into wide areas to cross
Play many long balls (long ball %)
When playing against this style, dealing with the chaos and winning 1st and 2nd balls is key, can you win the chaos, get the ball down and implement how you want the game to go
A thought I have is that it is one thing to have opposition data and to make inferences from it, though the next step is to then establish a plan for how to counteract the opposition based on those inferences. This will therefore be applied to Houston Dynamo and New York City:
Houston Dynamo
-Given Houston Dynamo’s low amount of passes though high amount of passes forward and crosses, there is the potential that Houston Dynamo are less compact when they loose the ball as they would rely less on players being in closer (rest defence) distances that would be seen with shorter passes. A plan we can therefore adopt is to look to be more direct in our attacking transitions, as they are likely to be even less compact than most teams in their attack-defence transitions which we can capitalise on.
New York City
-Given their low amount of headed shots and relatively low amount of crosses (which is low but not in the bottom 5 as a metric comparatively), we should be particularly compact in the centre of the pitch so that we can force them out wide and cause them to play more crosses which they are less effective at due to their low metrics in these crosses resulting in headers/overall efficacy.
Of course with both of these proposed plans, a team will have to consider the extent to which they alter their own style of play or not. On one hand, the given plans and adjusting a team’s style of play may be beneficial to best counter the opposition. However, this also has to be weighed up against whether it causes our own team to play in a way that we are less familiarised with, or it diverges too greatly from our principles, style of play, or game model. This demonstrates how these considerations need to be made in terms of opposition analysis, though generally which the task demonstrated, there is no denying the value of using data and metrics to understand an opponent’s style of play in order to best exploit them.
Houston appears to be playing direct football, as they use long balls to arrive in the final third of the opposition and aerial balls to attempt to score. They are heavenly dependent on long passes between the units and show that they have strong individuals physically giving them an advantage in the air to win aerial duals. I stand to question the technical ability of the players and their 1v1 duals on the ground
New York City
New York City is a possession-based team that plays short passes and combinations and rarely attempts to play long balls as they are poor with it. The higher passing rate in a short distance shows the security of progressing as a unit and holding on to the ball in the final third until they find or create a chance to shoot. Their accuracy at goal is very high by shooting from the final third as they are also rated with passes in the final phase.
They show to be very poor aerially and with long balls showing they are heavily dependent on the short passes. and rarely score with aerial balls. New York City appears to be a very technically and tactically good team. They are also collectively based.
NYCFC:
– Want to keep possession and keep the ball moving around the field but don’t thread the needle and move the ball forward as they rank in the bottom 5 in % of passes forward (38.40%)
– Tend to put lots of shots on target but from a distance
– When in the final third, they tend not to cross the ball in the box, which could be the reason why they rank in the bottom 5 in headed shots and % of shots with their head
Houston Dynamo:
– Very direct in passing metrics as they rank in the bottom 5 in total passes & passing % but in the top 5 in forward passes
– When attacking, wingers cross the ball to forwards, with Houston being in the top 5 in total crosses & headed shots, with the average shot distance being lower than the rest (17.9 yards)
– Play lots of long balls across the field (long ball % – 20.90) & (avg passing distance – 22.6 yards)
Overall, the data can show us certain trends our opponents do on the pitch. With NYCFC, we should be ready for them to try to keep the ball & complete lots of short passes to keep the ball moving. When getting close to goal, don’t be surprised if a midfielder or forward hits a shot from a distance. With Houston, it’s the opposite, as they love to play direct balls forward in very few passes and then cross the ball into the box. All this data can help analysts solidify their findings after watching videos on a team & can help get points across to your team.
The data shows NYCFC:
• Play a high amount of passes per game (381.77) and have a high passing accuracy (78.3%) but they also play a lower percentage of passes forward than most teams (38.4%)
• Have a low number of crosses compared to possession (cross/pass: 15%)
• The low number of crosses may also explain why they have such few headed shots (1.36 per game)
• Tend to shoot from further out than most teams (average shot distance – 20.4 yards)
• Don’t play many long balls (14.3%)
• High share of final third passes compared to opponents (57%)
For Houston Dynamo, the data shows:
• They are a direct team as they play a higher percentage of passes forward than most teams (45.5%)
• Low passing accuracy (~71%)
• Attempt more crosses per game than most teams (19.91 per game)
• Have a high number of crosses compared to possession (cross/pass: 20.8%)
• Shoot from closer to goal than most teams (17.9 yards)
• High crossing numbers and closer range of shooting may show why they have many headed shots per game (2.64)
• Play many long balls (long ball 20.9%)
These findings show that if we play NYCFC we could expect them to try to dominate and retain possession, dictate the tempo and we could expect them do shoot from long distance (we could identify these players from video analysis).
If we play Houston Dynamo we could expect them to be more direct, perhaps play more on the counter and transition and deliver the ball into the box when they have the opportunity.
The data provided helps us to put together our report and allow the Head Coach to identify areas to work on in training in preparation for the game to nullify their threat and exploit their weaknesses.
NYCFC
– Bottom 5 in percentage of forward passes, cross/pass %, headed shots, long ball %, average pass distance, % of shots with head.
– With these findings, it seems that they value having a lot of possession rather than being direct. Having a low percentage of headed shots correlates to the low number of crosses, since they are both in the bottom 5.
-They top 5 in total passes, pass %, average shot distance, shots on target, and shared number of final third passes.
– Meaning they are looking to break opponents down through their passing in the final third and using cut backs to help with better shot choices within the box.
Houston Dynamo
– Bottom 5 in total passes, pass %, average shot distance, 1v1 attempts, and 1v1 attempts in the box
– These finding show that they are not a possession oriented team
– Top 5 in % of forward passes, total crosses, cross/pass %, headed shots, long ball %, average pass distance, and % of shots with head
-Meaning they are looking to be direct to get behind the back line and getting crosses into the box. Having a good % of shots with head comes from the amount of crosses being serviced
It’s interesting to see how different styles of play work for other teams and how one team can have a lot of success in certain areas while another team may struggle in those same areas
NYCFC
– Bottom 5 in % of passes forward
– Top 5 in total passes attempted
These numbers here alone can tell you alot about how the team will look to play and ways we can approach how we play against them. In this case we should be able to press them more aggressively knowing they will not look to bypass our lines as much
Houston
– High % of passes forward
– Low % of total passes
– High amount of crosses
– High amount of long balls
These numbers also give you a very good idea of what kind of game you will be playing. Houston will look to bypass lines and play many more direct passes. They will also try to flood the box with crosses. Keys to playing against Houston will be dealing with 2nd balls after the initial long ball is made, as well as how we defend our box.
Using this data is very important to save time when making a game plan for the next opponent. Assuming the sample size is large enough we could easily make a general plan for the game and what to focus on in training for the week.
For example against NYCFC you could tell your midfield to be tighter to your direct opponent when the defenders are in possession because they tend to make shorter passes and will connect up the field that way. Against Houston the midfield does not need to be as tight, as the defenders will more than likely look to bypass our line into their attacking half. The focus would be more on dealing with 2nd balls and defending entry passes rather than closing down our direct opponent and winning balls
New York City FC
-Bottom 5 in % of passes forward, indicating that they are indirect in their attack.
-Top 5 in the league in total passes attempted and passing %. This indicates that they have a high rate of possession in their matches.
– Low amount of crosses compared to passes. This shows that they do not look to create the majority of their chances via crosses.
– Take a high amount of shots from outside the box.
-Low amount of headed shots. This is due to their low amounts of crosses.
-Bottom 5 in the league in long balls played. This shows that they would rather connect shorter higher percentage passes instead of more direct long balls.
-Top 5 in the league for share of final third passes in the league.
Houston
-Top 5 in the league for % of passes forward. This suggests that they opt for more direct attacks.
-Bottom 5 in the total passes and passing %, which indicates that they do not possess the ball compared to the other MLS Teams.
-Among the top crossing teams in the league
-Have a high cross/pass %
-Average shot distance is shorter than majority of teams.
-Top 5 in headed shots. This data makes sense since they cross the ball frequently.
-Top 5 in the league for long ball %.
Houston Dynamo:
Being in the top five percentile of passes forward and long balls, this shows that Houston Dynamo likes to play a direct game, however they are in the bottom five percentile in total passes attempted and passing percentage, which shows that they they are a low possession team, they look to cross the ball into the box rather than attempt a 1 v 1 or take a shot from distance.
New York City FC:
As they are in top five percentile of total passes attempted and passes, and passes in the final third, as well as 1 v 1 into the box, and shots on target shows that they are high possession team and likes to keep the ball, and like to switch the ball from the strong side to the weak side, which allows them to open up the opponents and gives them the opportunity to play through the middle in the final third of the pitch. Being in the bottom five percentile in passes forward, cross/pass and headed shots shows that they do not look to play direct or take the risk of losing the ball through a long ball, or a cross inside the box.
With the use of data, we are able to foresee how an opponent likes to play without watching the game film, and make predictions of the type of the opponents played against.
NYCFC:
Bottom five in % of passes forward
Top five in total passes
Top five in passing %
The data suggests that NYCFC likes to pass the ball a lot and keep it as much as they can. Due to the fact that they are bottom five in passes forward, the data would suggest that we wouldn’t have to worry too much about vertical passes, more so them trying to keep the ball in tight spaces and wear us out.
Houston:
Second in the league in forward passes
Last in the league in number of passes
Second last in the league in passing %
The data suggests that Houston likes to play forward, vertical and doesn’t like to spend too much time keeping the ball in their own half. They try to play vertical and get balls to their attacking players quicker.
The use of date is becoming more and more useful in analysis, with easy to digest graphics coming from some of the top providers. It helps remove bias and provides objective support to the subjective portions of a report.
Houston Dynamo:
-Play very direct and look to get the ball forward as fast as possible, as they rank in the top 5 in the league for passes forward, pass distance and long ball %. As well as the bottom 5 for total passes attempted and passing %.
-They refrain from taking many long shots, as they are in the bottom 5 for shot distance in the league
-In more advanced positions, they attempt a lot of crosses and are a threat aerially, as they are in the top 5 for crosses, cross/pass %, headed shots and % of shots with head.
New York City:
-They are patient with the ball and look to have the majority of the possession, as they rank in the top 5 for total passes attempted, passing % and are in the bottom 5 for passes forward, long ball % and passing distance.
-They do not attempt to score with the head too often, as they are in the bottom 5 for headed shots.
-They are in the top 5 in the league for shot distance, which means they are willing to shoot from range if the opportunity arises.
NYC:
– They are very patient and indirect in possession. They rank in the top 5 for Total Passes and bottom 5 for % of Passes Forward, Average Pass Distance, and Long Ball %.
– In the final third it’s clear they take less risk as they are bottom 5 for Cross/Pass % and % of Shots with the Head. They also are top 5 for Share of Final 1/3 Passes which reflects their patience and avoidance of losing possession.
Houston:
– They are a direct team. They are top 5 for % of Passes Forward, Pass Distance, and Long Ball %. They are also bottom 5 for Total Passes.
– In the final third they don’t mind taking risks as they are top 5 for Cross/Pass %, Headed Shots, and % of Shots with Head.
Houston score highly in the forward passes and crosses section, suggesting they like to play down the flanks. They have a low shot distance rate and high headed shots rate, which suggests that once the ball is played down the flank it is crossed in high. Their Long Pass score is high which indicates they may like to switch play to the opposite flank.
New York City score high in the passing and passing accuracy metrics, suggesting that they play a short passing game. They have a high average shot distance rate, coupled with shot accuracy, which suggests they have some gifted players who can shoot accurately from range. They score low on pass distance, number of long balls and headed shots, suggesting they like to pass through the middle.
I enjoy using stats to build a picture but feel they need to be supported by context such as imagery/video
Firstly Houston Dynamo:
-Team that likes to play aerially
– rank on the lower end in terms of total passes, accuracy and higher on the longball and average pass distance which suggests they adopt a more direct approach
– high headed shots and accuracy suggests they may have physical players who look for the headers or flick ons
-low percentage on 1v1 attempted may indicate that they’re crossers are not aggressively trying to work closer angles to cross and may be more willing to cross from deep
NYC:
– The high # of passes and accuracy suggests that they are more patient in possession
– additionally the fact that they rank low in passes fwd and high in passes in the final 3rd suggests that they are indirect and likely work the ball for favorable angles to shoot from (rank high in shots distance and shots)
The use of data is no doubt helpful in getting an idea of what a team might look to do when playing them and can provide a starting point for when watching footage of the team in question. However data does have it’s limitations. For example the data provided here can give a brief idea of how a team wants to play but then it becomes up to the analyst to add the required
NYC has more prudent style of play, aiming to control the ball, and they don’t prefer direct attack on the opponents (% od forward passes = 38,40%), they don’t have much vertical passing intentions and they not make effort to surprise the opponents with through balls and long balls (Long ball % = 14.30%). As a result, NYC doesn’t make chances by crossing the ball in the box (Cross/Pass % = 15.10%) and they are among the 5 teams with lowest percentage of head shots performed (% of shots with head = 8.40%). Also, they are not efficient in producing big chances, and don’t attempt much to gain advantage through 1v1 dribbling in the final 3rd (1v1 in the box = 2.27), which is average compared to the other teams in MLS.
NYC style is characterized with combined play, by making a lot of short horizontal and precise passes (Passing = 78.30%) and producing many relations between the players in order to move the rival structure and advance towards the rival playing field , progressively passing through the pressure lines, which enables them to avoid risk of losing the ball in their half and maintain a dominance in ball possession, especially emphasized in their final third (Share of Final Third Passes = 57.00%). NYC main strength is the ability to endanger the opposition goal by making shots from distance (Average shot distance = 20.4, 3rd rank), combined with executing very precise shots within the goal (Shots on target = 11.73, highest perimeter value in MLS).
Contrary to NYC, Houston Dynamo football club has a more direct style of attack, with the 2nd highest rank in MLS for the parameter % of Passes forward = 45,50%, showing aggressive intention to move towards the opponent’s goal. Their Long ball % parameter = 20.90%, highest in MLS, shows great ability to scan the field, find open teammates and make passes that other teams won’t try (highest Average pass distance = 22.6). This style provides them the opportunity to catch the opponent “off guard”, i.e. by surprise. Ability to quickly convey the ball to the finishing zones, contributes for Houston Dynamo to be among the 5 teams with highest Total Crosses = 19.91 and Cross/Pass % = 20.80%. Efficiently creating chances in the opponent’s box, they shot closer to goal than most teams in MLS, having low Average shot Distance of only 17.9, very high number of Head shots per game = 2.64, sharing the 1st rank with New York RB and the best MLS ranked % of Shots with head = 22.60%.
Houston Dynamo’s low passing accuracy Passing % = 71.60% and the lowest Total Pass Attempted = 333.55 shows that they don’t want the ball to circulate in their possession i.e., they don’t like safe play, but instead they prefer frequently targeting the players in their final 1/3 who then try to cross the ball in the box. The average Share of final third passes = 47.60% shows that they don’t choose to retain possession in the final third. Houston Dynamo doesn’t demonstrate high ability to perform through balls, with average parameter Through ball = 0.91.
By analysing attacking data, we can spotlight tendencies in an opponent’s gameplay such as the tendency to concentrate 60% of their attacks down the left flank. Pass accuracy metrics, can help us to highlight how well a player maintains possession and contributes to the team’s attacking buildup. This data, usually captured through video technology and subsequent analysis, can help identify areas for skill development and inform about tactical decision-making. Also, the attacking play data helps in determination of the corridor through which there are chances for play against, areas from which the shoots are executed, total number of the offensive actions during the match, etc. This data gives us the opportunity to determine of characteristics of the opponent attack, (rhythm of the play, built up phase general tactic planning, built up conception of the game), i.e. their style of play during the different stages of the attack, start, progression, finishing, offensive set pieces, etc. Rather than focusing on just goals scored, we would look at shots on target percentage, off-ball movements, pressing actions, and expected goals (xG). Our forwards would be those who take their chances efficiently and contribute to the team even when they are not scoring.
One of the most relevant examples of successful use of data analytics in soccer is the unexpected success of Leicester City FC during the 2015-16 English Premier League season, when Leicester, which had only narrowly avoided relegation the previous season, made history by winning the Premier League title, a success which is partly made by the club’s innovative use of data analytics. The club focused on effective counterattacks, using data to analyse when and where to press the opposition to win back the ball.
Houston Dynamo:
-Team that likes to play aerially
– rank on the lower end in terms of total passes, accuracy and higher on the longball and average pass distance which suggests they adopt a more direct approach
– high headed shots and accuracy suggests they may have physical players who look for the headers or flick ons
-low percentage on 1v1 attempted may indicate that they’re crossers are not aggressively trying to work closer angles to cross and may be more willing to cross from deep
NYC:
– The high # of passes and accuracy suggests that they are more patient in possession
– additionally the fact that they rank low in passes fwd and high in passes in the final 3rd suggests that they are indirect and likely work the ball for favorable angles to shoot from (rank high in shots distance and shots)
The use of data is no doubt helpful in getting an idea of what a team might look to do when playing them and can provide a starting point for when watching footage of the team in question. However data does have it’s limitations. For example the data provided here can give a brief idea of how a team wants to play but then it becomes up to the analyst to add the required context to turn the raw data into useful information such as the areas on the pitch NYC likes to shoot from and areas Houston likes to target with the long ball.
When playing New York City, we can expect them to possess the ball, cross less than most
opponents and instead choose to retain possession in the final third to work the ball into the box.
When playing Houston on the other hand, we can expect them to be direct in possession, play
long balls, cross the ball often and attempt shots from headers.
I found this exercise interesting as it takes into account mean data rather than data from a single match. This would highlight trends across multiple games which then would make a tendency something more likely to be used in a future game. The data then can be matched to video examples to identify details of these tendencies.
NYC is a team that is characterized by their patient possession. They tend to keep possession of the ball and play longer passes less often than most teams in the league. In terms of their chance creation, they tend to shoot from further out than most teams, and create fewer chances from crosses in the air.
Houston Dynamo is comparatively direct in their possession. Their play is on average, more direct than most teams in the league. The Dynamo create more chances than most teams through crosses in the air.
One thing that I think is especially helpful about data is that it has no bias. A video analyst may come into watching a game with a preconceived notion about a teams play style based on reputation that may not be entirely accurate. Data is a helpful unbiased tool that takes into account a large selection of games that can help direct the eye of a video analyst for what to look for in eyes-on opposition scouting.
Based on the data NYCFC looks to be a team who wants to control possession. They are one of the best teams of the league in passes attempted and passing accuracy.
They are also one of the lowest teams in percentage of passes forward, long balls and average pass distance what makes me think they try to get into the final third with patience and short passes instead of attacking faster and use more direct balls.
In the last third, data shows that probably NYCFC will look more for short combinations or shoots from long distance to try to create chances, instead of looking for crosses from the sides.
It’s also important to remark that they have success in their way of playing, at least in the attacking phase, because they have the most shots on target by game in the whole league.
On the other hand, Houston Dynamo looks to be the opposite. A team that plays more direct and long balls to progress and get into the final third. They are the lowest team in the league in passes attempted per game.
In the last third they will look for crosses and headers. They accumulate the most headed shots per game and the highest percentage of shots with the head in the whole league. At the same time Houston Dynamo is one of the lowest teams in 1vs1 situations attempted and 1vs1 situations in the box, but one of the highest in total crosses per game or crosses per pass. In the final third, as soon as they can they look for crosses, instead of 1vs1 situations or short combinations.
The use of data in those cases can help us a lot to have an overall picture of the opponent’s tendencies. After that is the analyst who should break down this tendencies and look into the more important tactical aspects, which can really influence in our preparation for the game.
There are many things that happen in the games that data can’t explain. Data can’t replace the analyst duties of watching the opponent’s games and try to understand what they do, how they do it and why they do it. Game understanding + relevant data to explain what’s going on in the field is the best combination for opposition analysis.
NYCFC tend to be indirect in possession but tend have a lot of possession and are accurate in their passing. They tend to shoot from a farther distance and are more accurate in their finishing. They also look to have a majority of passes in the final third. They will have fewer crosses and will look to combine passes in final third for chance creation as their passes tend to be of shorter distance. They will also look to cross aerially less than other opponents.
Houston tend to be more direct and vertical in their passing and in final third will look to cross often. These crosses can be varied but they have a big strength in attacking aerial cross with headers. They will not look to keep possession as much as other teams and in attacking situations will look for 1v1s less often instead opting for crosses.
As Ernst Tanner says in the video, data can be reliable source to find out team and player trends for upcoming opponents. Then we can video that supports the findings from data to provide a more soccer specific interpretation of the data. However, this task showed quickly how data can help streamline the process of watching multiple videos and generating findings from the process. The subjective and tactical analysis should not be the only part of the opposition analysis, nor should the collection of data. However, the combination of both into a singular process can help create a more accurate and efficient picture when planning for upcoming opponents.
Incorporating data can help you get a vague understanding of a teams playing style and give you some overarching themes to look for once you dive into video. NYCFC for example appears to possess the ball heavily and look to out-possess opponents, based on their # of passes and % completed, as well as their share of final third passes. You can also draw that they look to circulate the ball and will shoot from distance when unable to break the opposition down after long periods, due to their low % of headed shots and crosses, as well their higher than average shot distance. Houston represents an inverse philosophy, being in the bottom 5 of pass quantity and pass completion, while being in the top 5 of cross/pass ratio, total crosses, and headed shots. While the data can give us an overarching understanding of their style, it is paramount that we use video to find the details, such as structure, buildup, and pressing shapes.
The organization of data can be useful to see overarching themes about a team’s style of play, analyzing where they oppose a threat or can be exposed to their weaknesses. Distinguishing top 5/bottom 5 can help evaluate if numbers are in the norm, above average, or below average. This can help determine if we need to pay attention to a specific variable or not. For example….
New York RB Stats (Top 5): – Possible Strengths
– % of passes forward
– total passes attempted
– total crosses
– headed shots
– shots on target
– % of shots in the box
– Share of final third passes
– % of shots with head
– Big Chances created
– 1v1s in the box
New York RB Stats (Bottom 5): – Possible Weaknesses
– passing %
– average shot distance
– through balls
– long balls/long ball %
– average pass distance
As much as numbers are helpful, they always need to be contextualized and assessed through critical questions that the coaching staff can pose. Doing so, one can end with the following outcome…
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
New York City FC: Top 5 in amount of passes attempted as well as passing percentage which indicates they are a possession based team. They are also top 5 in share of final third passes which shows they like to keep possession in the final third before trying to find a chance on goal. They are bottom 5 in both crosses and headed shots which shows they like to keep the ball on the ground when attacking and creating chances. They are also bottom 5 for long balls and length of passes which shows they are not very direct which could lead us to think that we could disrupt them by pressing high up the field and trying to force them to play longer passes.
Houston Dynamo: Top 5 in long ball percent, average pass length, total crosses, cross to pass percent and headers. This gives us a great idea that they are a very direct team who looks to cross early and have the ability to create chances from these crosses with headed shots. They are bottom 5 in total passes and passing percent which further shows that they will look to go direct quickly to get into crossing positions.
Teams like Columbus Crew and Seattle Sounders had the lowest percentage of passes forward, while boasting the highest number of passes and possession numbers. Despite this, Columbus landed in the upper middle of the pack with regards to most shooting numbers, despite scoring the lowest in passes forward. Seattle’s attack had less success in correlation with their lack of forward passes. Sounders, Fire, Whitecaps, Dynamo and Orlando City all ranked pretty high for percentage of crosses attempted despite very different numbers in other passing categories, indicating varying methods to get to similar results.
New York City and Houston Dynamo represent two opposing philosophies, with the former using controlled possession (total passes attempted, passing accuracy%) preferring accurate short passes (low avg passing distance) to progress through the thirds (low through balls but high share of passes in final third, law volume of crosses and cross/pass%), while the latter use sharp long balls (high avg pass distance and long ball%) to put players in positions to cross (high amount of total crosses, high cross/pass%), and many of their shots are headers (% of shots with head)
New York:
Top 5 in:
Total Passes Attempted
Pass Completion percentage
Average Shot Distance
Total Shot On Target
Final 3rd Passes
Bottom 5 in:
Percentage of headed shots
Average Pass distance
Long Ball percentage
Headed Shots
Cross/Pass %
Percent of forward Passes
Which shows that New York City have a very possession style of play.
Houston top 5 :
percent of forward passes
Cross/Pass %
Total Crosses
Headed Shots
Average pass distance
Long balls percentage
Shots with head
Bottom 5:
1v1 in box
1v1 attempted
average shot distance
passing percentage
Total passes attempted.
This shows that Houston likes to use the width when building up and fast build up with plenty of crosses into box and are quite direct.
Color coding does make a difference in establishing better awareness of data. Here are the findings for both teams – NYCFC and Houston Dynamo.
NYCFC have an effective playing style that refers to these attributes:
Bottom five in % of passes forward
Top five in total passes
Top five in passing %
NYCFC like to passes the ball and create chances in front of the net. They limit their crosses into the box. They build-up through the thirds and depend on player technique to retain the ball making shorter passes to work into the box.
Houston Dynamo attributes:
Second in the league in forward passes
Last in the league in number of passes
Second to last in the league in passing %
Houston’s style of play is more direct. They use long balls often to get behind the defensive line. They tend to move the ball quickly and get forward without much possession play. Crosses into the box will be often for their attack.
New York City
Top 5:
Total passes attempted
Passing %
Average shot distance
Shots on target
Share of final Third Passes
Bottom 5:
% of passes forward
Cross/pass %
Headed shots
Long ball %
Average pass distance
% of shots with head
NYCFC- team with possession style of play:
Short passing with high accuracy, building through the thirds, combination play in the final 1/3 to create chances
Fewer long balls and crosses
*Houston Dynamo
Top 5:
% of passes forward
Total crosses
Cross/pass %
Headed shots
Long ball %
Average pass distance
% of shots with head
Bottom 5:
Total passes attempted
Passing %
Average shot distance
1v1’s attempted
1v1’s in the box
Houston Dynamo- team with direct style of play.
Lack of build up play, long balls to get behind opponents back line, chances mostly created from crosses.
Colour coding is such an easy and effective way to visualize data, it makes a spreadsheet go from a big file with numbers to a mini league table.
From the data we can see NYC has a lower shot distance, pass distance and long passes, and on the flip side the are that the top for final third passes, total passes and pass success rate, suggesting that they play a more possession based, short passing game, trying to play through the opponent with combinations to create chances in the final third.
On the other hand we can see Houston is top in long pass attempted, pass distance, high headed shots, shots in the box, and crosses, whereas they are bottom at passes attempted, pass accuracy, suggesting that they play a more direct style, trying to play the ball long and high, preferably to a target man to head the ball in the box.
I really like the idea of splitting the groups into top, middle of the pack, bottom.
Using this data we can understand tendencies that clubs have while they play, which helps us plan for what the may plan to do during a game, and what their strengths and weaknesses are.
NYCFC:
Bottom five in % of passes forward
Top five in total passes
Top five in passing %
The data suggests that NYCFC likes to pass the ball a lot and keep it as much as they can. Due to the fact that they are bottom five in passes forward, the data would suggest that we wouldn’t have to worry too much about vertical passes, more so them trying to keep the ball in tight spaces and wear us out.
Houston:
Second in the league in forward passes
Last in the league in number of passes
Second last in the league in passing %
The data suggests that Houston likes to play forward, vertical and doesn’t like to spend too much time keeping the ball in their own half. They try to play vertical and get balls to their attacking players quicker.
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.
New York City
High possession of the ball and big chances created on the 1v1 in the box. The team gets the final third with a great combination of passing.
Houston Dynamo
The team moves the ball by passing into the final third, high percentage of crossing and headed shots, as well as they play long balls often
I found it interesting how we approached the scouting of tendencies for both teams. Surely there was another way to look at tendencies but it comes down to what recourses you have and also how important it is for you personally to find out certain attacking tendencies. For me, it was very helpful to see which approach to analyzing attacking tendencies can work because everything is kind of new and I thought it put me on a good path to a better understanding of what’s possible. The challenging part for me was it to not directly jump to conclusions based on the data we got. For example, NYCFC doesn’t play a lot of forward passes but they have a higher percentage than other MLS teams in possession and they also connect their passes more often than not. When just looking at the low percentage for forward passes it’s easy to say that NYCFC isn’t good at breaking lines or playing possession style. One explanation might be though that, NYCF plays a long entry ball into the opponent’s half where they connect the majority of passes, and thats where their higher percentage for passes connected comes from. In reality, we don’t know exactly what happened based on one statistic and I had to remind myself that this statistic is only one piece of the bigger picture.
These are my notes from the data.
NYCFC
Passes Forward: Have a low percentage of passes forward. Therefore they play sideways or backward. More indirect in possession, potentially go for second balls.
Total passes attempted: Higher percentage. They want to keep the ball and play in possession.
Passing accuracy: Very High percentage within league. They connect the majority of their passes.
Total crosses: No extreme here.
Cross Pass Percentage: Low in crosses but high in passes.
Average Shot Distance: Shoot from further out than other teams.
Headed Shots: Low amount, since fewer crosses. More shots with feet.
Shots on Target: High percentage, they’re hitting the target more often than not.
Shots on Target within Box: More shots from or around Box.
Long Ball percentage: Don’t play a lot of long balls. More shorter passes.
Share of final third passes: High percentage. A lot of passes within opponents half.
Shots with head: Low amount, since fewer crosses. More shoots with feet.
1 vs 1 in Box: Lower in percentage. Shoot or pass instead.
Houston
% Passes Forward: High percentage. Direct style of play? !
Total passes attempted: Low amount, direct style of play.
Passing accuracy%: Low in percentage, don’t connect many pass other teams.
Total Crosses: More crosses than other teams. Few Passes Forward lead to crosses fast
Cross Pass %: High, a lot more crosses than passes
Average Shot distance: Low, shoot closer to goal due to more crosses
Headed shots: High, due to crosses which are also received
Shots on Target: Equal shots or headers on target
1 vs 1 attempts: Low, due to more crosses or shots rather than dribbling
Long ball accuracy: High, crosses arrive at the target.
Average pass length: High, direct style of play. Higher amount of air balls
1 vs 1 in box: High, means crosses are being received. Either headed or dribble
NEW YORK CITY
Top 5
– Total Passes Attempted
– Passing %
– Average Shot Distance
– Shots On Target
– Share of Final Third Passes
Bottom 5
– % of Passes Fwd
– Cross/Pass %
– Headed Shots
– Long Ball %
– Average Pass Distance
– % of Shots With Head
HOUSTON DYNAMO
Top 5
– % of Passes Fwd
– Total Crosses
– Cross/Pass %
– Headed Shots
– Long Ball %
– Average Pass Distance
– % of Shots With Head
Bottom 5
– Total Passes Attempted
– Passing %
– Average Shot Distance
– 1v1’s Attempted
– 1v1’s In The Box
NYC
Will build methodically, attempting to create scoring chances by isolating 1v1s around the top of the box. Minimal direct or vertical play in the air
Houston
Will play with more verticality than most teams. Will bypass buildup play in their own half, reliant on getting balls into wide channels, and creating chances from crosses.
NYCFC Top 5 in:
-Total passes attempted
-Passing percentage
-Average shot distance
-Shots on target
-Share of final third passes
Bottom 5 in:
-Passes forward
-Cross/pass percentage
-Headed shots
-Long ball percentage
-Average pass distance
-Number of shots with head
Houston Top 5 in:
-Percentage of passes forward
-Total crosses
-Cross / pass percentage
-Headed shots
-Long ball percentage
-Average pass distance
-Percentage of shots with head
Bottom 5 in:
-Total passes attempted
-Pass percentage
-Average shot distance
-1v1’s attempted
-1v1’s in the box
NYC
Top 5 in: Total passes
Average Shots
Shots on target
Share of final 3rd passes
Bottom 5: Percentage of passes forward
Long ball percentage
Cross/pass percentage
Average pass distance
Headed shots
Percentage of shots with head
Houston
Top 5: Percentage of passes forward
Total crosses
Cross / pass percentage
Headed shots
Long ball percentage
Average pass distance
Percentage of shots with head
Bottom 5: Total passes attempted
Pass percentage
Average shot distance
1v1’s attempted
1v1’s in the box
Once these findings are presented to the coach, the next step would be to find the video clips of these key moments. With Houston being in the top 5 for Percentage of shots with head, I would be looking at how the Strikers position themselves as the ball is about to be crossed in, their movement during the ball flight, and how deep they start. Similarly for NYC, since they have a high number of average shot and shots on target, I would be looking at who they’re key players for shots and what areas they typically occupy. Also important to look at how they get their receive and get their shot off (are they receiving deeper and not being pressured or are they finding space through short combinations with teammates?).
My thoughts on data in the game is that it can reveal the overall tendencies of teams based on certain stats. I believe it is important not to get caught up in every stat as it won’t provide overall context as stated early in this section.
I do like how you can identify how direct or indirect a team is, what types of chances on goal they typically create, and a general idea of where most of their passes might be going.
I would like to think there are some stats that could be created to determine some more trends of a team. For example, data collected on the amount of time spent in each vertical channel of the field might indicate how often a team plays side to side or switches play versus playing on the same side of the field. Also collected data on amount of passes attempted into final third, OR “where passes originate then played in behind the last line” could be good indicators of team trends and WHEN they want to get into the final third or in behind.
I think that data collection could improve effectiveness of training planning and scouting with more game related intentions in mind when coming up with what data we want to collect. I would find it extremely interesting if there was attacking data collected on “Area of field teams begin to play in behind the last line most often”. This might reveal a team’s intentions of where they want to attract their opponent, how direct they might be and when, and where you might want to risk pressing them versus being aware of them trying to get forward… I believe data could be fantastic, specially if more context was applied to certain data gathered!
NYCFC
Bottom 5 in % Pass Fwd
Top 5 Total Passes Attempted
Top 5 Passing %
Bottom 5 Cross/Pass %
Top 5 Average Shot Distance
Bottom 5 Headed Shots
Top 5 Shots On Target
Bottom 5 Long Ball %
Bottom 5 Average Pass Distance
Top 5 Share of Final Third Passes
Bottom 5 % of Shots With Head
With the data, we can conclude that NYCFC are a short passing team with a high passing accuracy. They have a low percent of forward passing than others. They favor taking long shots and they don’t have many opportunities from headers. They tend to have a high number of shots on target and a high number of passes in the final third.
Houston
Top % of Passes Fwd
Bottom Total Passes Attempted
Bottom Passing %
Top Total Crosses
Top Cross/Pass %
Bottom Average Shot Distance
Top Headed Shots
Bottom 1v1’s Attempted
Top Long Ball %
Top Average Pass Distance
Top % of Shots With Head
Bottom 1v1’s In The Box
With this data, we can see that Houston is one of the top teams in the league in terms of forward passing. They don’t attempt too many passes and don’t have a good passing accuracy in the league. They do cross the ball more often than most and have the highest opportunities in headers. They are a long ball team and prefer long distance passes. Their shots tend to come from close range as opposed to long distance.
# NEW YORK CITY
– low % of passes forward
– high % of total passes
– high passing %
– low cross/pass %
– high average shot distance
– low headed shots
– high shots on target
– low long ball %
– low average pass distance
– high share of final third passes
– low % of shots with head
Based on the data we can deduct that New York City are a possession based team, indirect in possession who are threatening in the final third. They have few headed shots and like to shoot from distance.
# Houston Dynamo
– high % of forward passes
– low % of total passes
– low passing %
– high % total crosses
– high cross/pass %
– low average shot
– high headed shot
– low 1v1s attempted
– high long ball %
– high average pass distance
– high % of shots with head
– low 1v1s in box
Houston Dynamo are direct in possession and look to shoot close to goal, often looking for crossing opportunities and have lots of shots with headers.
Real Salt Lake
Play a higher percentage of passes forward than most teams
Play a lower total number of passes than most teams
Have a lower passing percentage than most teams
Have a lower number of shots on target than most teams
Have a higher number of shots in the box than most teams
La Galaxy:
Are in the middle of the league in passing forwards
Rank Low in average shots
Rank better than most of league in shots in box
Rank better than most of the league in through balls and big chances created