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024. LET'S INTERPRET TEAM PERFORMANCE WITH OFFENSIVE/DEFENSIVE PROFILE & GD-P CONVERSION

By fully-leveraging 4 team-driven datapoints ▫ PTS-G, GF-G, GA-G and GD-G ▫ we unlock enhanced benchmarking across ECNL's 1,600+ teams.
024. LET'S INTERPRET TEAM PERFORMANCE WITH OFFENSIVE/DEFENSIVE PROFILE & GD-P CONVERSION

The Offensive Defensive (OffDef) Profile highlights a team's ability to both score goals and not concede them:

  • By combining GF-G and GA-G together into your visuals, a richer set of insights are available.

The Goal-Differential-to-Points Conversion (GD-P) highlights the ability to win, irrespective of goal dynamics. GD-P Conversion surfaces many subtleties, including dominating teams winning inside a relatively-weak conference (more on that in a future episode).

Consumed together, the OffDef Profile and GD-P Conversion go a long-way in describing the relative performance of ECNL's 1,600+ teams (Girls, Boys, Age Groups). In-order to further-enhance that description, we also differentiate teams into 3 tiers (ie: Top, Mid, Bottom) across different dimensions (ie: conferences, nationwide, age groups, etc.).

Let's assess this snapshot of the entire 2023-24 ECNL regular season:

... and consider these big-picture takeaways:

  • On average, the Top Tier (ie: the top 33% best teams) concede less-than 2-goals per-game.
  • If a team often scores 3-or-more goals per game, then it's a Top Tier team.
  • If, on average, a team concedes 4-or-more goals per-game, then only on rare occasions will it score twice in a single game.

Here's the equivalent GD-P Conversion:

... and these takeaways:

  • Top Tier teams generally-deliver season performances of 2.00+ PTS-G.
    • As a reference (more on this in another episode), in the English Premier League, PTS-G season averages of 2+ are often-limited to its Top 3 (ie: 3/20= 15% of teams).
  • Top Tier teams deliver positive GD-G, and ≈half of Mid Tier also achieve this milestone.
  • Many Top Tier teams achieve full-season PTS-G similar to other Top Tier teams... but require ≈50% less GD-G.

The above is presented as an initial framework that we'll use - and enhance! - as we pursue our storytelling journey inside the ECNL.

Richard - From SoccerAnalytix