Chapecoense-sc – Vasco DA Gama

What are the outcome probabilities for Chapecoense-sc vs Vasco DA Gama?

Ahead of this Serie A meeting, the 11Stat model distributes the three-way outcome as follows: Chapecoense-sc win 39%, draw 25%, Vasco DA Gama win 36%. Because the three probabilities always sum to 100%, each figure can be read directly as the model's estimated likelihood of that result — a 39% rating means the model expects Chapecoense-sc to win roughly that often if this exact match were replayed many times. No single number here implies certainty; the gap between the three values is what signals how one-sided or open the model considers the contest.

the 11Stat model assigns Chapecoense-sc a 39% probability of beating Vasco DA Gama in Serie A.

the 11Stat model rates the draw at 25% and an Vasco DA Gama win at 36% for this fixture.

3 of 4 independent engines in the 11Stat model point to a Chapecoense-sc win, producing a confidence score of 5.8/10.

How do xG and recent form shape the model's read?

Underlying these percentages is each side's attacking and defensive profile, expressed through expected goals (xG). The 11Stat model weighs how many quality chances Chapecoense-sc and Vasco DA Gama have been creating and conceding in recent matches, adjusts for opponent strength and venue, and blends in short-term form momentum.

How many independent engines agree on this match?

The 11Stat model is not a single algorithm. It runs 4 independent engines — including Poisson and Dixon-Coles goal models, an Elo-and-form engine, and an advanced bivariate simulation layer — and compares their outputs before publishing anything. For Chapecoense-sc vs Vasco DA Gama, 3 of 4 engines converge on a Chapecoense-sc win, which feeds directly into the overall confidence score of 5.8/10. Strong cross-engine agreement raises confidence; disagreement between engines is treated as a warning sign that the match carries more uncertainty than the headline probabilities alone suggest.

What does a confidence score of 5.8/10 actually mean?

The confidence score summarizes how much internal evidence supports the model's leading outcome — it reflects engine consensus, data completeness, and how well-calibrated the model has been in comparable Serie A fixtures. A score of 5.8/10 is a measure of analytical conviction, not a promise about the result: even high-confidence projections lose regularly, exactly as their probabilities imply. 11Stat publishes this score so readers can distinguish matches where the models broadly agree from matches where the projection rests on thinner or conflicting evidence.

How does the 11Stat model calculate these probabilities?

Each probability is produced by simulating the match thousands of times. Goal-based engines estimate scoring rates for Chapecoense-sc and Vasco DA Gama from xG, historical goal data, and venue effects, then run Monte-Carlo simulations across every plausible scoreline to derive win, draw, and loss frequencies. A separate Elo-and-form engine cross-checks the result from a team-strength perspective. Finally, a calibration layer — continuously validated against thousands of settled fixtures — adjusts the raw outputs so that, over time, matches rated at 39% genuinely resolve that way about 39% of the time. The output is a probability estimate for analytical and research purposes, not advice of any kind.