FM22: THE 900 CLUB — EXPLORING THE DATA HUB

In today’s post, I will be using the data hub with the view to walking you through the team’s performance, for those of you who have been following my content you will already know of the added value which the Data Hub has brought to my saves and the positive impact which these minor tweaks have delivered.

Playing this Lecce save with a specific focus in relation to positional roles and outputs, really adds a layer of clarity in relation to what I am expecting from individuals within the system making the analysis easier.

This is certainly a good starting point before even attempting to interpret the data, sit back and think to yourself what is your game model/philosophy, this is essential in my opinion in using the hub as a stepping stone aiding you to get from A to B.

In my opinion the general performance visualisation is a great place to start, you can then look to analyse the ‘Team Attacking’ and ‘Team Defending’ radars which will influence the decisions made when setting both team and player instructions both with and without possession.

The attacking radar speaks volumes and highlights just how effective we have been in relation to playing the attacking brand of football which is associated with Zemanlandia. Our twogoals per game is nearly double that of the Serie B average of 1.30 and our 241 shots taken leads the league by 97 (Brescia 144) and is significant over the average of 12.20.

Sports Interactive have certainly made FM user friendly as the visualisations and comments guide you to areas of need, clearly the ‘Attacking Efficieny’ radar shows that our ‘Shots on Target Ratio’ is significantly below par, so we can use the ‘Data Hub’ to use data to aid our decision making process.

Given the fact that we are on a ten game streak, there is no need to make any massive adjustments to the playing style. However, that's not to say that we can not explore minor tweaks to make us even more effective.

Firstly, looking at the ‘Shot Map’ which spans over the last five matches, you will note a significant volume of shots are from outside the area, this is represented in the average xG per shot for this period being 0.08.

The above visual shows the xG values from a basic expected goals model which considers only two features (shot distance and shot angle). As it is expected, the closer the shots is made the higher the xG value, therefore if we are looking to increase our expected goals per shot ratio we need to decrease the distance to goal and decrease the volume of chances from the lower side of the xG scale.

Now, the context is that we are playing with an attacking mentality and ‘In possession’ have the team instruction to shoot on sight, therefore you would expect to see us taking more shots than other teams.

Now at this point many of you would say, why don't you just take that off or play with ‘Work Ball Into Box’, the answer would be that I don’t want to stop players shooting when they feel they have the opportunity to score, I just want to scale it back a little through minor tweaks, with the view to improving our ratio, in turn increasing our chances of scoring from shots.

Drilling down into the ‘Player’ tab you we can start to focus on who are the volume shooters who take a more of a scatter gun approach to their finishing rather than precision.

Firstly, looking at the forwards you will note that three players are in fact scoring above the leagues average (Asencio, Rodriguez and Strefezza) whilst Coda operating as the ‘Target Forward’ has a lower xG per shot ratio, this is due to a large proportion of his sots coming from headers, which if my understanding is correct draws down a lesser xG score than a shot from the foot.

Moving onto the next visualisation ‘The Midfield’ you can start to see exactly where the issue is stemming from as four of the five players all have an xG per shot under the league average.

I opted to put the in-game data into excel, I do like a spreadsheet and feel that the data reads better in this format.

You will note that ALL midfielders have an xG per shot of below 0.9and have scored a combined xG per shot of 0.06, this is the area in which we need to adjust in order to improve our expected goals to shots ratio.

My two central midfielders have the player instructions to get further forward, this instruction is defined in the game as the following;

“Get Further Forward encourages players to seek to make an impact on the game in the advanced areas by increasing the number of rate of forward runs they make whilst mainlining their place within the overall structure of the team.”

I feel that the above image is a good example of this player instruction as both Listkowski and Helgason are making entries into the attacking third of the pitch.

The players role within my team are to pick up any second balls headed away from the oppositions central defenders with the view to recycling the ball and maintaining the attacking momentum.

Clearly with the shoot on sight and attacking mentality these players are choosing to express themselves by taking on the shot, therefore I am going to instruct them to ‘Shoot Less Often’ with the view to attempting to keep them a little more disciplined with their choices.

The Results

The xG per shot for the first ten games of the season averaged 0.09, whilst the average xG per shot after the tactical tweak was 0.12. an increase in 0.03. This is reflected in the pink trend line in the graph above.

Looking at the raw data above you will note that since the tweak our xG per shot is yet to dip to below 0.10, whilst the average shots has in fact increased from 24.1 across the first ten games to 26 across games 11–15 .

I hope you have found this example of just how good the use of the Data Hub can be to make refined changes to your tactics and hopefully give you the marginal gain you need to take your team to the next level.