Ternana W vs Juventus W: Lineups, Predictions & Betting Tips
Serie A Women
Ternana W vs Juventus W Predictions
Over 1.5
Ternana W 0 - 3 Juventus W
Visitor Picks (1x2) for Ternana W vs Juventus W
Who will win?
1
Ternana W
x
Draw
2
Juventus W
We've got Ternana W facing Juventus W in the Serie A Women coming up, and our model has some thoughts on how this might play out.
How Are They Looking?
It's been up and down for Ternana W: 2 wins, 1 draws, 2 losses recently.
Juventus W are ticking along nicely with 3 wins from 5 recently.
Breaking Down The Odds
Leaning towards Juventus W here with 50.00% win probability. Ternana W are at 30.00% though, so don't rule them out. Draw: 20.00%. The predicted scoreline? 0-3.
The Goals Markets
44.00% for BTTS. It's a maybe from the algorithm.
Don't expect a thriller — Over 2.5 is only at 40.00%. Over 1.5 is 60.00%, which is more realistic.
The Bet We Like
If we're putting our neck on the line, it's Over 1.5 Goals at 3.40. The model gives this a 60.00% probability.
The Odds
Market prices: Ternana W win 8.50, Juventus W win 1.25, Draw 5.00. For goals, BTTS Yes 1.91 / No 1.80, Over 2.5 at 1.04.
Match preview generated automatically using our football prediction algorithm. Data-driven doesn't mean guaranteed — always gamble responsibly.
David Shaw
Professional Sports Betting Analytics Expert & Algorithm Developer.
David Shaw is a pioneering figure in the sports betting analytics industry with over 12 years of specialized experience. He launched his first online sports data platform in 2014, quickly becoming the #1 ranked football tipster on Tipster Portal. Following the successful acquisition of his original platform, David founded FootyGuru365.com, which was also subsequently acquired as well as SoccerTips.ai.
David's crowning achievement is the development of the Betminer Algorithm - recognized as the world's most accurate football predictions algorithm. This sophisticated API now powers hundreds of major websites globally, providing cutting-edge predictions data to millions of users. He holds a degree in Computing from the University of the West of England, combining academic knowledge with real-world betting expertise.
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