A practical six-step workflow for creating a fair cohort, reading the profile and identifying players worth deeper review.
Typical workflowUpload→Filter→Analyse→Validate
The workflow
Six steps. Better context.
Talent DNA helps structure a recruitment conversation. It does not replace tactical judgement, video review, medical information or live scouting.
01
Prepare the Wyscout export
Run a player search in Wyscout for your selected season and export it as .xlsx or .csv. It is best to include all positions so Talent DNA can create every positional cohort from the same file. Keep Player and Minutes played; include Position and Age so every cohort filter is available.
More performance columns produce a richer role profile.
02
Upload it securely
Drop the export onto the Talent DNA upload area or choose it from your device. The file is read inside your browser and is never uploaded to Talent DNA.
Any missing or unusual columns are reported immediately.
03
Define a fair cohort
Set minimum and maximum minutes, age range and positional group. These filters determine which peers are used for every percentile and Rating.
Use a focused positional group and a meaningful minutes threshold.
04
Read the overview
Select a player to see their identity card, core radar, strongest traits, relative weaknesses and cohort distribution. The cohort definition sits directly beneath the Rating.
Treat the Rating as context for investigation—not a final verdict.
05
Explore the percentiles
Open Percentiles for the full role-specific profile and specialist radars. Expand or collapse categories to focus on the parts of the role you are assessing.
Hover the question marks and profile rows for metric details.
06
Compare and rate
Use Comparison to rank one metric across the cohort. Open Rating to rank the filtered group by Rating, minutes or market value, then select another player for review.
Validate statistical outliers with live or video scouting.
Video walkthroughs
See the complete workflow.
Follow both practical guides at your own pace—from creating the Wyscout file to exporting a tailored Talent DNA report.
01
Wyscout preparation
Create and export the data extract
Choose the right search, season, positions and columns, then export the spreadsheet ready for Talent DNA.
Read written summary
Open a Wyscout player search, choose the relevant competition and season, include every position you want to compare, and set a sensible minutes threshold. Add Player, Team, Position, Age and Minutes played, followed by the performance metrics required for your analysis. Export the results as an XLSX or CSV file, keeping the original column headings, then return to Talent DNA and choose that file.
02
Talent DNA reporting
Build a custom PDF report
Upload the file, filter a fair cohort, create ranked bars and scatter plots, then export the finished report.
Read written summary
Upload the Wyscout export, set the minutes, age and position filters, and select the player to review. Use Comparison or Insights to choose a ranked bar or scatter plot, then select Add to report. Rename and reorder saved comparisons if needed. When the report tray is ready, download the PDF and verify its player, cohort and metric labels before sharing it.
Reading the output
What the numbers mean
83rd percentile
The player’s raw value is equal to or higher than 83% of valid players in the active cohort.
Rating 72
The rounded average of the player’s available core metric percentiles for the current role and cohort.
n = 28
Twenty-eight players remain after the active minutes, age and position filters.
Good practice
Before making a recommendation
01Confirm the cohort reflects the real recruitment brief.
02Check that the player has enough minutes and valid data.
03Review raw values alongside percentiles.
04Use video to understand role, team style and game state.
05Record risks and counter-evidence, not only strengths.
About the creator
Built by Bill Orr. Free for the football community.
Talent DNA was created to make Wyscout exports easier to explore, explain and share. Use it freely, keep the attribution, and follow development on @TheBillOrr.