“Mansfield (1350.2 Elo, 14pts in 7 games) has a 40.17% model win probability with a +2.1% edge over market odds of 42.27%.”

“The model gives Mansfield a 40.2% win probability, slightly higher than Oxford's 33.9%, and the over 2.5 goals probability is 51.9% with a positive edge for under, but the market odds still slightly favor over, which aligns with Oxford's strong attack rating of 1.561.”

“Mansfield has a higher Elo rating (1350.2) compared to Oxford (1305.3), and our model gives them a 40.17% chance of winning, which is higher than the market's 32% for Oxford.”

“The model predicts Under 2.5 goals at 48.14%, higher than the market's 45.69%, providing a 2.45% edge.”

“The model gives double-chance 12 (no draw) a 74.09% chance versus a 25.91% chance of a draw, so DC ‘12’ is the strongest edge.”

“Model OU25 is near coin-flip (O 0.5186 / U 0.4814) yet U holds the clearest edge (+0.0245) vs market; 1X2 is tight (H 0.4017, A 0.339) with only a small away edge and BTTS similarly marginal.”

“The model gives BTTS 'No' at 44.1% vs market 42.1%, a +2.0% edge, the only positive edge in the data.”

“Model predicts a high probability of goals with OU25 at 51.86% and BTTS at 55.92%.”

“Model gives Mansfield 40.17% home win chance vs Oxford's 33.9%, and Mansfield's attack (1.561) is stronger than Oxford's defence (1.102).”

“The model gives a 2.02% edge on BTTS No (44.08% model vs 42.06% market), the highest edge among all markets.”