KMC vs Coastal Union: match statistics

The synthetic favorite is Coastal Union — I predict an away win. Coastal sit 9th with 25 goals this season versus KMC’s 13, KMC being 16th. In the last 5 matches Coastal scored 5 goals and average 1.4 points per game, while KMC also scored 5 goals in their last five but have 0 points (5 losses). Chance metrics are mixed: KMC at home has higher xG (1.41) and more shots (8.27, 3.27 on target), but a low conversion rate of 5% and only 0.45 goals per game on average, whereas Coastal away have xG 1.10, 6.92 shots and better 10% conversion yielding 0.69 goals. Defensively KMC concede 1.09 at home versus Coastal conceding 1.54 away, but high shutout percentages for both (KMC 64% at home vs Coastal 69% away) point to few goals; weighing Coastal’s higher league position and attacking efficiency I assign 25% to the home win, 30% to a draw and 45% to an away win.

KMC at home has BTTS in 69% of matches and only 8% of games without scoring; their goals average is 1.23 with xG 1.33, indicating the hosts regularly create and convert chances. Coastal Union away have a seasonal BTTS of only 23%, a 69% share of matches without a goal and on average 0.69 goals scored per game, which weakens their ability to score. On the other hand KMC have recently weakened defensively—they conceded 12 goals in the last 5 matches (2.4 per match) and have recent xG against of 1.7, while the visitors in their last 5 matches have xG_for 1.19 and scored 5 goals (1.0 per match), so Coastal Union have a real chance to score. Considering the hosts' clear BTTS rate of 69% versus the visitors' weaker seasonal scoring profile of 0.69 and the xG relationships (1.33 for the hosts vs 1.54 xG against the visitors), I favor the BTTS "Yes" scenario with an estimated 60% vs 40% for "No".

I estimate expected goals at 1.44 for KMC and 1.30 for Coastal Union (total 2.74), calculated as the average of home xG 1.33 with xG conceded vs visitors 1.54 and away xG 1.10 with xG conceded vs hosts 1.50. That xG total (≈2.74) translates into model probabilities: Over 1.5 ≈76%, Over 2.5 ≈52% and Over 3.5 ≈30% (corresponding Under: 24%, 48%, 70%). Seasonal stats support Over 1.5 — hosts have Over 1.5 in 77% of matches, visitors in 69% — whereas seasonal Over 2.5 is only 31% (hosts) and 38% (guests), which explains why higher lines lose edge. Additionally, hosts average 8.63 shots and 3.13 on target per match with a 13% conversion, visitors 6.92 shots and 2.31 on target with 10% — and in the last 5 fixtures hosts conceded 12 goals (2.4 avg) versus 6 for visitors (1.2), increasing the risk of goals. For these reasons the strongest data signal is a play on Over 1.5, since both the xG model (2.74) and seasonal Over 1.5 rates (77%/69%) provide an edge at an estimated probability of about 76%.

Data analysis shows KMC's advantage in the first half: hosts led at the break in 6 matches (50%), while Coastal Union did so in only 2 (15%), with first-half goal averages of 0.92 for KMC versus 0.38 for the visitors. Over the full match KMC has a 38% win rate at home, Coastal only 15%; seasonal goal averages are 1.23 (KMC) against 0.69 (Coastal), and xG is 1.33 versus 1.10, with 3.13 shots on target vs 2.31 and conversion rates of 13% vs 10%. Given that a host lead at the break occurs in about 50% of matches and hosts are effective at maintaining the result, I assign the highest probability to the 1/1 (HT/FT: home/home) scenario (38%). Alternatives are draw at half-time and KMC win (X/1 11%) or draw/draw (X/X 9%), since a half-time draw for KMC appears in 3 instances (25%). Scenarios with the away side leading at the break and winning ultimately (2/2 15%) are assessed as less likely due to only 15% overall away wins and Coastal conceding on average 1.54 goals per match, despite the visitors averaging 1.0 goals in second halves.