🎯

Fixture360 only lists fixtures from a curated set of leagues, chosen specifically to keep our prediction model accurate.

📰

Prediction vindicated as Daegu FC edge out Gangwon FC 2-1.

📝 Match Report

How It Unfolded

Daegu FC beat Gangwon FC 2-1 at DGB Daegu Bank Park, Regular Season - 1, in the K League 1. That is the final score; the rest of this report grades it against what the data forecast beforehand.

The Model vs The Result

The Poisson model went into this projecting Daegu FC 1.40 xG and Gangwon FC 1.20 xG, a combined 2.60. 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 Daegu FC attack 1.07 / defence 1.02 against Gangwon FC attack 0.99 / defence 1.06, drawn from 33/33 games (PrevSeason).

On the result, the model split it Daegu FC 41% | Draw 26% | Gangwon FC 32%, with Daegu FC to win its most likely call at 41%. The scoreboard confirmed the model's leading pick.

Goals & Markets

The model rated Over 2.5 goals at 48%. The game delivered 3, so it went over — a miss for the goals model. Over 1.5 had been 73% and landed. On both teams to score, the model sat at 53% and the match saw both sides score — another call in the model's favour. Historically the two sides average 42% Over 2.5 across their same-competition games (Daegu FC 45%, Gangwon FC 40%), a base rate that pointed the other way from today's over. Their combined BTTS history runs at 54%, which matched the both-scored outcome.

Trading Patterns vs Reality

Daegu FC's trading profile (78 games, 39 home) set some clear expectations: BTTS lands in 54% of their matches — today it did.

Gangwon FC's trading profile (78 games, 39 away) set some clear expectations: BTTS lands in 55% of their matches — today it did.

Form vs Result

The form lines were close — Daegu FC 1.23 PPG, Gangwon FC 1.31 PPG — offering no strong steer, and the Daegu FC win broke the near-deadlock.

Verdict

Grading the result against the stored data, 2 of 3 pre-match signals came in: result (hit), Over 2.5 (miss), BTTS (hit). A mixed scorecard — the data caught the broad shape of the game but not every market.

💡 Key Insights