© 2018 by Sportsline SciTech - Spinned off from Sportsline Asia

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GET IN TOUCH:

Tel: +852 25302110

Email: success@sportsline.tech

CONTACT US:

21/F, 102 Austin Road, Tsimshatsui

Kowloon, Hong Kong

FEATURED PROJECT

How SciTech empower you to next level...

Enterprise Engine

We help National Sports Associations and Private Organisation to build and optimise infrastructure for sports science and enterprise-level analytics

Individual Engine

Hardware Integration

Our Individual Engine with proprietary Performance Index can help you to relate your heart rate, power, training pattern and condition to training, performance and injury

SciTech AIAI Engine communicates with all hardwares to generate second level insights.  Connect with us for more information

We geared up Hong Kong Lee Man Football Club with Sports Science and Medicine - for the debut season 2017-18

Index for Enterprise

It makes perfect sense for us to correlate and stratify ALL metrics towards Performance Index:

  • Tactical Index

  • Management Index

  • Scout Index

  • Fans Engagement Index

  • Financial Index

Hardware Integration

Enterprise Engine

We empower everybody to make informed decision in sports and wellness,  with stratified data and actionable insights, from multiple perspectives

X - Performance
Y - Sports and Wellness Business

X_test - Predictor and Analytics

 

#Assumed you have, X (performance) and Y (sportsbusiness) for training data set and x_test(predictorandanalytics) of test_dataset

# Create logistic regression object

model = LogisticRegression()

# Train the model using the training sets and check score

model.fit(X, y)

model.score(X, y)

#Equation coefficient and Intercept

print('Coefficient: \n', model.coef_)

print('Intercept: \n', model.intercept_)

#Predict Output

predicted= model.predict(x_test)