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FF Jaro and Gnistan share the spoils in a 1-1 draw.

📝 Match Report

How It Unfolded

The points were shared at Jakobstads Centralplan, Regular Season - 8, as FF Jaro and Gnistan drew 1-1 in the Veikkausliiga. 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 FF Jaro 1.27 xG and Gnistan 2.23 xG, a combined 3.50. The scoreboard read 1-1 for 2 actual goals. Gnistan landed 1.2 under their projected return. Those figures were built on strength ratings of FF Jaro attack 0.73 / defence 1.46 against Gnistan attack 1.01 / defence 1.08, drawn from 7/29 games (CurrentSeason).

On the result, the model split it FF Jaro 21% | Draw 20% | Gnistan 59%, with Gnistan to win its most likely call at 59%. Instead the game produced a draw, an outcome the model had rated at just 20% — a clear break from expectation and a genuine upset by the numbers.

Goals & Markets

The model rated Over 2.5 goals at 68%. The game delivered 2, so it stayed under — the opposite of the projected direction. Over 1.5 had been 86% and landed. Over 3.5 was 46% and did not. On both teams to score, the model sat at 64% and the match saw both sides score — another call in the model's favour. Historically the two sides average 25% Over 2.5 across their same-competition games (FF Jaro 0%, Gnistan 50%), a base rate that agreed with today's under. Their combined BTTS history runs at 25%, which did not match the both-scored outcome.

Form vs Result

On form, Gnistan arrived the stronger side — 2.00 PPG against 1.50. The form guide was only half-right: the stronger side did not lose, but could not convert the edge into a win. Gnistan managed 1 against a 2.00 scoring average — below par going forward.

Verdict

Grading the result against the stored data, 1 of 4 pre-match signals came in: result (miss), Over 2.5 (miss), BTTS (hit), form (miss). The data was on the wrong side of this result more often than not — a reminder that a single match sits well inside the model's variance.

💡 Key Insights