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Prediction vindicated as FC Krasnodar edge out FC Rostov 2-1.

📝 Match Report

How It Unfolded

FC Krasnodar beat FC Rostov 2-1 at Ozon Arena, Regular Season - 19, in the Premier League. With the result on the board, the sections below measure it against everything the model and the numbers projected in advance.

The Model vs The Result

The Poisson model went into this projecting FC Krasnodar 1.65 xG and FC Rostov 0.87 xG, a combined 2.52. The scoreboard read 2-1 for 3 actual goals. Both sides finished within a goal of their individual projections, so the scoreline sat close to the model's expected shape. Those figures were built on strength ratings of FC Krasnodar attack 1.31 / defence 0.95 against FC Rostov attack 0.92 / defence 0.92, drawn from 48/48 games (CurrentSeason).

On the result, the model split it FC Krasnodar 56% | Draw 25% | FC Rostov 19%, with FC Krasnodar to win its most likely call at 56%. That is exactly how it finished — the model's leading outcome was vindicated.

Goals & Markets

The model rated Over 2.5 goals at 46%. The game delivered 3, so it went over — the opposite of the projected direction. Over 1.5 had been 72% and landed. On both teams to score, the model sat at 47% and the match saw both sides score — a miss on BTTS. Historically the two sides average 47% Over 2.5 across their same-competition games (FC Krasnodar 54%, FC Rostov 40%), a base rate that pointed the other way from today's over. Their combined BTTS history runs at 48%, which did not match the both-scored outcome.

Trading Patterns vs Reality

FC Krasnodar's trading profile (48 games, 24 home) set some clear expectations: BTTS lands in 44% of their matches — today it did; they keep a clean sheet 50% of the time, and conceded here.

FC Rostov's trading profile (48 games, 24 away) set some clear expectations: BTTS lands in 52% of their matches — today it did.

Form vs Result

On form, FC Krasnodar arrived the stronger side — 2.23 PPG against 1.25. That form edge translated into the three points.

Verdict

Grading the result against the stored data, 2 of 4 pre-match signals came in: result (hit), Over 2.5 (miss), BTTS (miss), form (hit). The model got the gist right while missing on the margins.

💡 Key Insights