Use Case: Analyzing GPS Load by Match Day (Game Day) Phase

In elite sport, performance isn’t built on Match Day (or “Game Day,” depending on where in the world you’re playing!)—it’s built across the week. That’s why performance staff rely on Match Day periodization frameworks to guide training intensity and recovery. But planning is only half the equation. To execute with precision, you need to know:

What’s actually happening across MD– and MD+ (or GD– and GD+)?

For many teams, GPS data is accessible—but it’s difficult to segment by match day, position group, or individual athlete. Most systems lack the flexibility to compare load trends over time or to quickly validate whether the week aligned with the plan.

With the Performance Optimization Solution in iP: Intelligence Platform, sports science teams can automatically segment and visualize GPS metrics by match day phase—no spreadsheets, no custom queries, no delays.

The Challenge

You’re collecting GPS load data daily. But without the ability to break it down by training day context (e.g., MD–1, MD+2), it’s hard to:

• Verify if load distributions match the intended training model
• Identify load spikes or inconsistencies across the week
• Compare team/squad-level vs. positional trends
• Monitor longitudinal load patterns without exporting data 

The result? Planned periodization may not match actual load, and small imbalances can lead to poor readiness, elevated injury risk, or performance drop-offs.

What We Hear from Sports Science Teams

• “We can see total load, but we can’t easily segment it by match day phase.”
• “Every week we’re exporting GPS data to Excel just to validate the plan.”
• “We need to see MD–1 and MD–2 trends across positions, not just individual snapshots.”
• “There’s no easy way to align session intent with actual output—at scale.”

The reality is: most platforms are good at capturing data. But not at putting it in the right context.

The Solution: From Raw Metrics to Performance Insight

With the Performance Optimization Solution in iP, GPS load data becomes dynamic and contextualized—so you can validate periodization week by week, across squads and seasons.

With Self-Service Reporting in iP: Intelligence Platform, performance staff can segment metrics like total distance, high-speed running, accelerations, or player load by Match Day Phase—then analyze trends, flag anomalies, and adjust sessions in minutes.

What You Can Do in Performance Optimization

Visualize Weekly Load Patterns by MD+/–

• Use XY or bar charts to plot the average load across each match day phase
• Compare load distribution by squad, position group, or individual
• Validate that high-load days align with the plan and that MD–1 is tapering as intended 

Monitor Longitudinal Trends

• Track MD–1 or MD+2 load across multiple weeks to spot rising or declining patterns
• Pivot by athlete, unit, or time period to adjust based on fatigue or readiness metrics 

Support Training Adjustments with Data

• Flag unexpected spikes in MD–2 or MD+1 output
• Reinforce plan alignment during performance or MDT meetings
• Bring consistency to week-to-week planning with visual proof of execution
  
  

See the Match Day Load Workflow