Hybrid Conferencee

International Conference on Machine Learning Applications in Sports Analytics (ICMLASA - 26)

20th - 21st October 2026 | Mecca, Saudi Arabia

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Conference Notifications:

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Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in Mecca. Submit your research by today to participate in one of the top conferences."
Certificate of Presentation:
"Present your research and receive a Certificate of Presentation to recognise your valuable contribution to the conference."
Abstract Submissions Open:
"Abstract submissions for the Mecca event are now open! Don’t miss the chance to present your research. Submit now."
Networking with Global Experts:
"Engage with researchers and professionals from around the world at the Mecca conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Mecca, featuring global leaders and innovators sharing their knowledge."
Best Paper & Best Paper Presentation Award:
"Submit your paper and stand a chance to win the Best Paper Presentation Award. The winner will be recognized at the conference in Mecca."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICMLASA aims to explore emerging trends and future directions in research and innovation. It provides a collaborative platform for researchers and professionals to share ideas that shape the future of their respective domains.

The conference highlights advancements in Sports Technology, encouraging innovative, solution-oriented research that addresses global challenges and technological evolution.

Authors are invited to submit papers addressing, but not limited to, the following areas:

01
Machine learning techniques in sports analytics
02
Predictive models for game outcomes
03
Data mining for sports performance insights
04
AI applications in sports strategy
05
Real-time analytics for coaching decisions
06
Player performance evaluation using ML
07
Challenges in sports data analysis
08
Machine learning for injury prediction
09
Statistical methods in sports analytics
10
Impact of ML on fan engagement
11
Visualization of machine learning results
12
Case studies of ML in sports
13
Ethical considerations in sports analytics
14
Future trends in sports machine learning
15
Collaborative filtering for player recommendations
16
Natural language processing in sports journalism
17
Data-driven decision making in sports
18
Integration of ML with IoT data
19
Performance optimization using machine learning
20
AI-driven scouting and recruitment strategies