Go to: Players > Filters tab on the left-hand side > Select 'Performance' dropdown > Select your criteria

The SciSports recruitment platform has the primary aim of finding players that will fit the specific criteria that users are looking for. Through filtering elements such as Player Roles, SciSkill and Leagues, users have been able to find interesting players for further live or video scouting.

In order to make these searches even more specific to what a user is looking for, we have introduced a Performance filter that enables further accuracy when searching across our database of over 220.000 players. Through being able to filter on 10 action groups, users can more accurately search for the specific type of player that they are looking for - in addition to the pre-existing filters within the platform.

This function allows you to find players who ranked in the top 50%, 33% of 10% of players in their league and position in certain timeframes: most recent/current season, any season within the last two years or any season within the last three years. By using these options based on certain criteria, users will be able to find the most relevant players in relation to what they are looking for.

An important element to remember is that the timeframe selected may result in finding, for example, a player who recently joined a club in the Bundesliga having previously ranked highly in the Jupiler Pro League. In addition, players will only show up in these filter searches once playing over 450 minutes in a specific position during a league season within the timeframe selected.

Below, we take you through a working example with specific criteria stated:

As you will see from the criteria above, we are searching for Right Backs under the age of 28 who perform well across three key areas for a Wing Back; also adding just the top 50% of players overall ensures that the players rank in at least the top half across the board too. By filtering further on SciSkill Potential and market value, the aim is to find affordable options that have notable development ahead of them.

From the snapshot above, you can see the final 10 players that match each set of our criteria sorted by SciSkill Potential in descending order. Just like in other filter searches, the top bar shows you the entire input that results in the eventual list. In this case, we have a 10-player shortlist of high performing Right Backs who are not only affordable but also rank well in key areas for that position.

Adding specific Performance filters based on what a user is looking for in a player enables a more accurate and precise search through data-driven insights.

A frequently requested addition to the SciSports recruitment platform often concerns being able to use the filter tool for finding high performing players. While this can be done through the SciSkill Index and other methods, using the Performance filter in different ways can also achieve interesting results.

In this case, a user can select the most current/recent season and input additional filters based on a range of elements. For this example, we will be scouting U23s in the Jupiler Pro League who currently rank within the top 33% of players in their specific position. As we see below, this input generates an 11-player shortlist consisting of players currently performing well for their respective teams this season.

To make this type of search valuable, users can save this type of filter within their own account. For instance, this filter may be named 'U23 JPL high performers' and enable a quick overview of promising youngsters in specific leagues of interest. Loading this saved filter upon logging into the SciSports platform ensures an immediate summary of high performers.

In sum, the Performance filter has the aim of providing further context around a specific player search. While, as we have seen, it allows an overview of leagues, the most valuable addition is being able to refine searches based on certain criteria points. This reinforces the importance of a clear strategy in player recruitment and being able to identify what is exactly needed in a squad.

Note: at present, players who do not have enough competitors in their position and league to be benchmarked against will show up in the top 10% of searches. For instance, setting all 10 action groups to only the top 10% will likely show only players who have none or very few competitors to be benchmarked against. This is often the case in positions such as Attacking Midfield where fewer players tend to reach the minute threshold in that position. To avoid only finding these players, we advise users to use the Performance filter in only the most important action groups for that position.