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Argentina at #1 is the cleanest “champion profile”: 6 matches, 6W-0D-0L, only 5 goals (frequency 0.83), yet still a huge 69.98 rating. That tells you your model rewards perfect results + tournament survival even when the goal count isn’t flashy — a classic “win tight games” run.

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Colombia at #2 show the other path: more goals + one draw. They have 12 goals in 6 (frequency 2.00) and go 5W-1D-0L, ending on 69.03. They scored over twice as much as Argentina, but the extra draw keeps them just behind — suggesting your rating heavily values pure win volume at the very top.

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Uruguay (#3) and Canada (#4) prove deep runs matter even with losses. Uruguay have 2 losses but still rank high because they scored 9 goals (frequency 1.50) and stayed alive for 6 matches. Canada are the “low-output grinder”: just 3 goals (frequency 0.50) yet still #4 because they reached the final stages and stacked enough results.

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The #5–#8 cluster is basically “sample size vs output.” Brazil (#5) scored 8 in 4 (frequency 2.00) but only played 4 matches, so they can’t stack the same tournament value as 6-match teams. Ecuador (#6) and Venezuela (#7) show how 4-match teams stay competitive when they score 6–8 goals and avoid heavy losses, while Panama (#8) hang around thanks to solid results despite fewer games.

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The lower half shows the model’s main penalty: low goals + fewer matches. Teams like Costa Rica (#9) and Peru (#10) sit close in rating because they played only 4 matches and didn’t score enough to offset the short run. Meanwhile Bolivia and Chile drop further due to weak records and low output — in a short tournament, your system needs either wins or goals to stay afloat, and ideally both.