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Sanfrecce Hiroshima (K) vs INAC Kobe Leonessa (K) Prediction — Model Probabilities
The bookmaker priced every market fairly — no dependable value at these odds, so skipping is the disciplined play.
Our call is our best estimate of the outcome; a value flag is a separate, rarer judgement about the price.
Edge (pp): green = we see more probability than the market · gold = essentially even (±0.5pp) · red = we see less. The Decision above outranks any single row: the engine backs well-supported edges, not merely big ones.
Sanfrecce Hiroshima (K) v INAC Kobe Leonessa (K) — Team-Based Signals
Sanfrecce Hiroshima (K) vs INAC Kobe Leonessa (K) Head-to-Head — Last 4 Meetings
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Sanfrecce Hiroshima (K) 2-1 INAC Kobe Leonessa (K) — Actual Match Statistics
Sanfrecce Hiroshima (K) edged past INAC Kobe Leonessa (K) 2-1. Half-time: 1-0.
Our pre-match lean was INAC Kobe Leonessa (K) at 44%, but a lead that slim is closer to a coin-flip than a call — and it fell the other way. The goals read — under 2.5 goals (56%), no to both teams scoring (55%) — went the other way, though.
On the day, Sanfrecce Hiroshima (K) had 49% of the ball to INAC Kobe Leonessa (K)'s 51%, shots finished 13-9.
Coming into the game, across their last 4 meetings in our records, Sanfrecce Hiroshima (K) had the better of it with 2 wins, 1 drawn. Those games averaged 1.00 goals for Sanfrecce Hiroshima (K) and 0.50 for INAC Kobe Leonessa (K).
What was the final score of Sanfrecce Hiroshima (K) vs INAC Kobe Leonessa (K)?
Sanfrecce Hiroshima (K) 2-1 INAC Kobe Leonessa (K) in the Japan - WE League Women's on 17/08/2025. The analysis above shows what our model predicted before kick-off next to what actually happened.
What did the model predict for Sanfrecce Hiroshima (K) vs INAC Kobe Leonessa (K)?
Before kick-off our model rated an INAC Kobe Leonessa (K) win the most likely single outcome at about 44%, with the full match-result split Sanfrecce Hiroshima (K) 30%, draw 27%, INAC Kobe Leonessa (K) 44%. The final score 2-1 went against our main leads this time — single matches are noisy by nature; our accuracy is measured across thousands of predictions, not one result.