How to Use the Bio-Banding Tool

Getting Started: Overview

The biobanding tool helps you create maturity-matched teams quickly and efficiently. Whether you're organizing a single training session or planning a tournament, the tool handles the complexity of grouping athletes by biological development.

Before you begin, you'll need:

Athletes who have completed maturity assessments through MatCalc. The tool uses biological age, predicted adult height, and maturation category data to create balanced groups.

A clear objective for the session. Are you focusing on technical development? Creating competitive match play? Testing players in challenging scenarios? Your objective will guide how you set up the groups.

The tool gives you a streamlined approach:

Select your athletes, choose your team generation settings, and let the tool create balanced groups. You can then review and adjust using the drag and drop interface before finalizing.

The result is teams organized by maturity level with balanced physical characteristics. Simple, efficient, and focused on creating fair competition.

Selecting Athletes for Your Session

Start by choosing which athletes will participate in the session.

Filter by sport and team:

Use the sport filter at the top of the page to narrow down to relevant athletes. If you're running a football session, select football. This ensures you're only working with athletes from that sport.

Choose the teams you want to work with. These are the teams you've created in the Team Management section. You might have custom groups like "All PHV Athletes" or "Development Squad" or traditional age-group teams like "U14 Boys."

You can select multiple teams if you're running a combined session. For example, you might select both "U13 Girls" and "U14 Girls" to create bio-banded groups across age categories. Or select a single team if you're organizing internal groups within one squad.

Choose attending athletes:

Check the boxes next to athletes who will be present for the session. The tool shows you their current team, biological age, and key physical metrics to help you make informed decisions.

Use "Select All" to quickly include everyone, then deselect anyone who won't be attending. Or build your group from scratch by selecting individuals.

Understanding the athlete information:

Each athlete's name, current team, biological age, and maturation status is displayed. This helps you understand the maturity range you're working with before you start creating groups.

Athletes can be members of multiple teams. For example, an athlete might be in "U14 Squad" and also in "Late Maturers Group." The tool shows all their team memberships so you understand their context.

If you have athletes from multiple age groups or custom groups training together, you'll immediately see the developmental diversity in your squad. This informs how you'll structure the bio-banded groups.

Team Generation Settings

Once you've selected your athletes, configure how you want teams to be created.

Biological Age Range Filter (Optional):

You can optionally filter athletes by a specific biological age range before generating teams. Toggle this on if you want to create groups only for athletes within a certain maturity window.

For example, you might set 12.0-13.5 years to create a band specifically for early adolescents, even if you have older or younger athletes selected.

If the filter excludes athletes, you'll see a notification showing how many players were filtered out.

Team Generation Mode:

Choose between two approaches based on your session constraints.

Fixed number of teams works when you have a specific number of pitches or game areas. For example, "I have 4 pitches available, so I need 8 teams." Enter the number of teams, and the tool distributes athletes evenly across them.

The tool shows you a preview: "20 players ÷ 4 teams = ~5 per team" so you can verify the math before generating.

Fixed players per team works when you have a specific game format in mind. For example, "I want 5v5 matches" or "I'm running 7v7 games." Enter the number of players per team, and the tool creates as many complete teams as possible.

The tool previews: "20 players ÷ 5 per team = 4 teams" so you know what to expect.

Sort By Parameter:

Choose which metric to use as the primary sorting factor when creating teams.

Biological Age is the most common choice. Teams will be sorted so that athletes of similar biological maturity are grouped together.

Predicted Adult Height helps group athletes who are heading toward similar final sizes, even if they're currently at different stages.

Maturation Category sorts by early/on-time/late maturer classifications.

The tool uses this parameter to first sort all athletes, then distributes them into balanced teams.

Split Method:

This determines how sorted athletes are distributed across teams.

Even Distribution: This is the recommended default. After sorting, athletes are distributed in a snake draft pattern. If you have 4 teams and athletes sorted by bio age from youngest to oldest, the athletes get allocated to each team from youngest to oldest and reverses.

This creates the most balanced teams because both ends of the maturity spectrum are evenly distributed. Teams end up with similar average biological ages and similar ranges.

Grouped Ranges: Athletes are divided into consecutive blocks. First quarter of sorted athletes go to Team A, second quarter to Team B, etc.

This creates distinct maturity tiers. Team A will have all the youngest/least mature athletes, Team B the next tier up, and so on. Use this when you specifically want separate developmental levels competing against similar levels.

Random Within Bands: Athletes are sorted first, then randomized before distribution. They're then distributed in simple rotation. This maintains some of the sorting benefits while adding variety.

This creates balanced teams with less predictable distribution than snake draft. Good when you want some randomness but still respect the general maturity sorting.

Choosing the right split method:

For most bio-banded sessions, use Even Distribution. It creates the fairest, most balanced teams where all groups have similar maturity profiles.

Use Grouped Ranges only if you want distinct tiers. For example, creating a "junior bio-band" and a "senior bio-band" from the same athlete pool.

Use Random Within Bands when you want balanced teams but with less predictable player combinations. Good for keeping sessions fresh while maintaining developmental appropriateness.

Generate Teams:

Once you've configured all settings, click "Generate Teams." The tool will create balanced groups based on your specifications.

You'll see a preview showing how many teams were created and how many athletes are in each. If you don't like the result, you can change settings and regenerate.

Understanding Team Summary Stats

After generating teams, the tool displays summary statistics for each group. These help you verify that teams are appropriately balanced.

Key statistics shown:

Average Biological Age is the most important balance indicator. Teams should have similar average biological ages, typically within 0.3-0.5 years of each other. If one team averages 13.2 years and another averages 14.1 years, they're not well-matched for bio-banded competition.

Biological Age Range shows the spread within each team. A range of 0.8-1.2 years within a team is normal and healthy. You want some variation to create learning opportunities, but not so much that some athletes dominate others.

Average Height and Mass give you a sense of physical size. While biological age is the primary balancing factor, checking that teams have similar average heights confirms they're physically comparable.

Height and Mass Ranges show the physical diversity within each team. Again, some variation is expected and beneficial. Large outliers might indicate an athlete who needs reassignment.

Average Predicted Adult Height helps you understand long-term size trajectories. Teams heading toward similar adult sizes tend to develop along similar paths, even if they're at slightly different stages currently.

Using stats to refine teams:

If average biological ages differ by more than 0.5 years between teams, consider rebalancing. Move an older athlete from the high-average team to the low-average team, or vice versa.

If one team has a significantly wider biological age range than others, it might need adjustment. You want relatively consistent internal variation across all teams.

Pay attention to both current size (height, mass) and predicted size (PAH). Sometimes an athlete is currently small but headed toward a large adult height. They might fit better in a team with similar growth trajectories.

What good balance looks like:

Team averages within 0.3-0.5 years of each other. Similar internal ranges across teams (all teams have roughly 0.8-1.2 year spreads). Comparable average heights and masses. No obvious physical mismatches.

Remember, perfect balance is impossible and not the goal. The aim is appropriate challenge. Athletes should be stretched but not overwhelmed, competitive but not dominating.

Drag & Drop: Making Adjustments

After generating teams, you can use the drag and drop interface to make manual adjustments and fine-tune the groupings.

The interface layout:

The left sidebar shows all unassigned athletes. These are the players you've selected for the session. Each card displays their name, biological age, and key physical stats.

The main area shows team cards. Each team displays the current athletes, average biological age, and summary statistics.

How to use drag & drop:

Click and hold any athlete card from the sidebar. Drag it over to a team card. The team card highlights in blue when you hover over it. Release to drop the athlete into that team.

Drag athletes between teams. Click an athlete already in a team and drag them to a different team. They'll be added to the new team while staying in the original (athletes can be in multiple teams).

Remove athletes from teams. Hover over an athlete card within a team. A red X button appears. Click it to remove them from that specific team.

Why drag & drop is useful:

Visual comparison. You can see all teams at once. It's immediately obvious if one team has mostly early maturers while another has mostly late maturers.

Skill Differences. You know your athletes, you can drag higher ability players into a team with a higher biological age to increase their challenge .

Spatial thinking. Some coaches prefer to organize spatially. Moving cards between zones feels more intuitive than working through lists.

Real-time feedback. As you drag athletes around, team stats update live. You can see how each addition affects the team's average biological age and physical profile.

Easy experimentation. Try different configurations quickly. Drag a few athletes around to see how it affects balance. If you don't like it, drag them back.

Tips for efficient adjustments:

Keep the sidebar scrolled to show athletes you're actively placing. You can focus on specific maturity ranges as you build teams.

Check team stats after each few assignments. Make sure you're maintaining balance as you build teams.

If you make a mistake, just drag back. Athletes can move freely between teams until you're happy with the setup.

Common adjustments:

Moving an early maturer from a team that's skewing older to one that's slightly younger. This helps balance average biological ages.

Swapping two athletes of similar maturity between teams to improve within-team chemistry or tactical balance.

Pulling out an outlier who's significantly more or less mature than their assigned team and finding a better fit.

Finalizing and Printing Teams

Once you've created balanced maturity-matched teams, you can review, print, and export them for use in your session.

Final review checklist:

Each team card shows comprehensive information. Team name and sport at the top. Full team with each athlete's biological age and physical stats. Team averages for biological age, height, and mass.

Check that biological age ranges are appropriate. Ideally, teams should have similar average biological ages (within 0.3-0.5 years of each other). If one team's average is significantly different, consider rebalancing.

Look at the maturity distribution within each team. It's fine to have some variation. What matters is that teams are matched against each other. A team with a 0.8-year biological age range is normal.

Verify that no athlete is dramatically over or under-sized compared to their teammates. A few centimeters or kilograms difference is expected. Large outliers might need reassignment.

Printing for session use:

Click the Print button. This generates a print-optimized layout with:

Team listings on separate pages. Each team gets its own page with clear headings and athlete names in large, readable text.

Key information only. Biological age and basic stats are shown, but unnecessary interface elements are hidden.

Page breaks between teams. Easy to distribute. You can give each coach their team sheet without the others for example.

The printed format includes:

Team name and sport clearly displayed. List of athletes with biological ages. Team summary statistics for reference.

Print tips:

Print before the session starts. Have team sheets ready when athletes arrive so you can group them immediately.

Consider printing extras. One for you, one for each team, maybe one for backup. Paper is cheap. Confusion during setup is expensive.

If you're running multiple sessions, note the team configuration. Many coaches run the same bio-banded groups for 2-3 weeks before reassessing and regrouping.

What happens after printing:

The session runs with these maturity-matched groups. Athletes train with others at similar developmental stages.

Observe how the groupings work. Do athletes seem appropriately challenged? Are games competitive? Is skill development happening?

Make notes for next time. Which athletes might need to move up or down a band? Who's progressing faster than expected? These observations inform future groupings.

After several sessions, reassess maturity status. Athletes move through puberty at different rates. Someone who was "late" three months ago might now be "on-time." Update your data and regroup accordingly.