Brazilian Serie B Round 12: Where Data Meets Drama

As a data scientist who eats xG metrics for breakfast, I couldn’t help but geek out over Round 12 of Brazil’s second division. Let me walk you through the numbers behind the madness.

The Unpredictability Quotient

The round opened with Volta Redonda vs Avaí ending 1-1 - a result that perfectly illustrates why I love this league. My predictive model gave Avaí a 63% win probability, but football (like my Python scripts) loves throwing curveballs. The xG battle was actually 1.7 to 1.3 in Volta’s favor - sometimes the scoreboard lies.

Shocking Results That Broke My Algorithm

Botafogo-SP’s narrow 1-0 victory over Chapecoense wasn’t surprising (my model predicted a 52% home win probability), but América Mineiro conceding to lowly CRB? That made my confidence intervals tremble. The 4-0 demolition of Avaí by Atlético-MG later in the round? Expected goals say it should’ve been closer…but football isn’t played on spreadsheets (unfortunately).

Statistical Standouts

• Goal Distribution: 60% of matches had under 2.5 goals - typical for a league where defenses dominate
• Late Drama: 38% of goals came after the 75th minute, proving fitness matters as much as skill
• Home Advantage: Host teams won 45% of matches, below the usual 55% league average this season

As we look ahead, my model suggests keeping an eye on Goiás - their underlying numbers show promotion potential despite sitting mid-table. But remember folks, in Brazilian football, even the cleanest data gets muddy boots.