Juventus W vs VfL Wolfsburg W: Lineups, Predictions & Betting Tips
UEFA Women's Champions League
Juventus W vs VfL Wolfsburg W Predictions
Over 1.5
Juventus W 2 - 2 VfL Wolfsburg W
Visitor Picks (1x2) for Juventus W vs VfL Wolfsburg W
Who will win?
1
Juventus W
x
Draw
2
VfL Wolfsburg W
Juventus W take on VfL Wolfsburg W in the UEFA Champions League Women on Thursday, and we've crunched the numbers to see what's likely to happen.
Current Form
Juventus W have been decent of late: 3W 1D 1L from the last 5.
Solid stuff from VfL Wolfsburg W — 3 wins, 0 draws, 2 defeats in their last 5.
Breaking Down The Odds
The algorithm can't separate these two. Juventus W: 33.30%. VfL Wolfsburg W: 26.70%. Draw: 40.00%. Anyone's game. Scoreline prediction: 2-2.
Will We See Goals?
60.00% for BTTS. It's a maybe from the algorithm.
This should be an open game — Over 2.5 comes in at 75.00%. Over 1.5 at 80.00%, Over 3.5 at 55.00%.
Where's The Value?
Over 1.5 Goals looks like the play here — 1.57 available with a 80.00% confidence rating from our model.
The Odds
Market prices: Juventus W win 2.80, VfL Wolfsburg W win 2.15, Draw 3.60. For goals, BTTS Yes 1.50 / No 2.50, Over 2.5 at 1.33.
AI-generated match preview based on our prediction model. The algorithm analyses thousands of data points, but it's still just probabilities. Gamble responsibly and only bet what you can afford to lose.
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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