Case Study – SKILLCORNER & COACHINSIDE

Integration of SkillCorner into COACHINSIDE

The integration of SkillCorner’s physical data into COACHINSIDE opens up new possibilities for clubs and coaches to analyze players and teams based on objective metrics. This extends traditional performance indicators by incorporating physical insights in a structured and use-case-specific way. Within COACHINSIDE, access to physical data depends on the respective setup: COACHINSIDE-only customers are provided with Total Distance at coach level, while clubs working jointly with COACHINSIDE and SkillCorner can access a broader set of physical metrics within the defined workflows. These include, for example, total distance, number of sprints, sprint distance and speed ranges. This structured access ensures that insights are always aligned with the specific analytical context and data agreements. Therefore, for clubs that do not yet have access to advanced physical data, it can be highly beneficial to consider adding a SkillCorner data package to unlock the full analytical potential within COACHINSIDE.

Player Match: The Physical Fit Between Player and Coach

A key feature is the COACHINSIDE Player Match, which shows how well a player fits the position-specific requirements of a coach. A particularly valuable aspect is the ability to directly compare a player’s physical metrics with the demands of the coach’s playing style. This makes it possible to identify players whose running performance, sprint frequency and speed match the tactical requirements of a specific system. Based on these physical KPIs, a score between 0 and 100% is calculated, clearly indicating at a glance how well a player and coach fit together.

Physical Data and Tactical Patterns under Claudio Giráldez

In his last two seasons at RC Celta, Claudio Giráldez’s teams showed a clear and recognizable data pattern that combines tactical flexibility with distinct physical characteristics. While his teams applied structured pressing phases and mixed game styles, the physical data reveals a consistent profile: high total running distances (ranking among the top teams in the league) paired with comparatively lower sprint numbers. This indicates a game model that relies more on collective movement, positioning, and intensity over longer phases rather than frequent high-intensity sprint actions.

This interpretation is further supported by the pressing data. With PPDA values of 10.23 (15th in the league) in the 2024/25 season and 12.56 (19th) in 2025/26, Giráldez’s teams pressed less actively compared to other teams. Instead of aggressive high pressing, the data suggests a more compact defensive approach, characterized by deeper positioning, allowing the opponent more possession, and shifting collectively within a structured block. This tactical behavior naturally leads to higher overall running distances, as players continuously adjust their positioning and maintain compactness.

By integrating SkillCorner’s physical data, these patterns become measurable and comparable, linking tactical decisions with the underlying physical demands placed on players. This reinforces the idea that physical metrics gain real value when interpreted within the context of a team’s playing style and the coach’s tactical framework.

Practical Application: Identifying Player Profiles

In practice, the benefits of integrating physical data become particularly clear. Players with high sprint numbers and strong acceleration profiles tend to be better suited for high-intensity pressing. Players with high PSV99 speed and those who cover large distances would fit well into transition-based game models. By combining data from COACHINSIDE and SkillCorner, clubs are able to make more objective decisions in areas such as transfers, squad planning, coach scouting and coach performance.

Benefits for Squad and Club Planning

The COACHINSIDE Player Match allows clubs to present the fit between players and a coach’s playing style in a more transparent way. With the integration of SkillCorner’s physical data, decisions in scouting, transfers, and long-term squad planning can be prepared and evaluated in a more data-driven manner. This approach is not only about short-term performance assessments but also about developing a clearer understanding of which player profiles best suit the desired game model in the long term. The connection between coaching requirements and objective performance data helps clubs develop their squads more strategically and align player profiles more precisely with a coach’s demands.

The Value of Physical Data in Modern Football

The integration of SkillCorner data into COACHINSIDE demonstrates the value that physical performance data can provide in modern football. It adds an important dimension to existing analysis and enables clubs to connect playing styles, player profiles and coaching requirements in a more comprehensive way. As a result, data becomes a crucial tool for better understanding sporting decisions and supporting more sustainable, well-informed strategies.

COACHINSIDE is the leading platform for professional measurement and analysis of coach performance. Since 2023, clubs, associations, agencies and media partners worldwide have used COACHINSIDE to close the gap between coach scouting and player scouting.

SKILLCORNER is the global leader in AI-driven sports data, providing automated player and ball tracking (including extrapolation of off-camera player position) from any single camera source including broadcast, tactical or wide-angle video.