Santos Laguna W vs Tijuana W
Liga MX Femenil
Santos Laguna W vs Tijuana W Predictions
Home Win
Santos Laguna W 1 - 2 Tijuana W
Visitor Picks (1x2) for Santos Laguna W vs Tijuana W
Who will win?
1
Santos Laguna W
x
Draw
2
Tijuana W
Wednesday brings us Santos Laguna W vs Tijuana W in the Liga MX Femenil. Let's dig into the data and see where the value might be.
Form Check
Santos Laguna W are a mixed bag lately: 1W 2D 2L from the last 5.
Tijuana W have been decent of late: 3W 0D 2L from the last 5. Back-to-back wins have steadied the ship.
Who Wins This?
Leaning towards Tijuana W here with 53.30% win probability. Santos Laguna W are at 20.00% though, so don't rule them out. Draw: 26.70%. Scoreline prediction: 1-2.
Goals, Goals, Goals?
70.00% for Both Teams to Score. Yeah, we fancy both nets to bulge in this one.
This should be an open game — Over 2.5 comes in at 70.00%. Over 1.5 at 70.00%, Over 3.5 at 30.00%.
The Bet We Like
Both Teams to Score looks like the play here — 1.62 available with a 70.00% confidence rating from our model.
The Odds
Here's how the bookies see it — Santos Laguna W 3.30, Draw 3.60, Tijuana W 1.85. BTTS priced at 1.62 Yes / 2.20 No. Over 2.5 Goals is 1.25.
This preview was generated by our prediction algorithm. It crunches historical data, form, and stats to give you the numbers — but football being football, anything can happen. Bet 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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