July 8, 2025
Combining Gradient Sports Player Grades with Pass Clusters
Case Studies
.webp)
.jpg)
Gradient’s Player Grades power smarter decision-making across scouting, recruitment, performance analysis, and player development. By measuring performance relative to expectation and contextualizing every action on the pitch, clubs, agencies, and data teams gain deeper insights into player impact.
Unlike traditional data, Gradient measures performance relative to expectation instead of just traits or measurable factors. The system looks at every event, creating a large sample size that eliminates bias and indentifies undervalued players while avoiding player hype. The grading process evaluates players objectively, regardless of perceived ability.
Gradient's grading process is built on a strict grading guide to turn subjective analysis into objective measurements.
.webp)
We grade each action based on quality, not just the outcome. For example, if a midfielder plays a poor through ball that ends in interception, they’ll be marked down even if the opponent miscontrols the pass and your team regains possession.
No amount of dribbling or second‑chance assist will hide a bad pass. Traditional stats like key passes or assists can be misleading. The same applies to defenders: a centre‑back who concedes few goals thanks to great saves may still earn a low grade if they lose too many duels or are out of position.
