This document describes disruptive predictive analytics methods for competitive advantage in business and sports. It discusses using proven predictive models and prescriptive solutions to alert clients to unseen risks and opportunities, and provide recipes for better results. Case studies show how the methods successfully predicted performance trends in Arsenal FC and the English Premier League with 78% accuracy based on past results. It also outlines predictive models for trends in team and player performance statistics.

1. DISRUPTIVE METHODS
FOR
COMPETITIVE ADVANTAGE
WWW.CEMSENGEZER.COM
BLACK BOX ANALYTICS

2. AGENDA
 Mission description
 Proven cases with the method

3. MISSION DESCRIPTION
 proven prediction solutions for competitve advantages:
 national, international leagues
 for better decisions: alerting unseen risks/opportunities with known methods
 prescriptive solutions:
 recipes for better results with unconventional methodologies
 revision to current business models
 view support to working models

4. FOCUS:
reliable prediction
reliable recipes
reliable optimization
UNIQUE SOLUTIONS TO BUSINESS

5. NATIONAL TEAM CASE
best time for brands to invest: low volatility uptrend in long term
bargain investment: high ROI

6. ARSENAL CASE (EUL, ECL)
still “under 100”: warning for
coming risks&opportunities with
different natures than past
“under 100” region (2012) => lower
performance, for next years (see
falling red curve)

7. ARSENAL CASE (EPL)
falling “under 100” alerting high
risk : need of different recipes to
recover in long term
“underestimated” EPL teams have
“-1 value” => better succes in next
years

8. TEST WITH PAST RESULTS
(Seasonal Prediction : %78)
 Similar results for lower leagues
EPL
final ranking 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006
Ars enal 5 2 3 4 4 3 4 3 4 3 4 4
Bournemouth 9 16
Brighton&HA
Burnley 16 19 18
C. Palace 14 15 10 11
Chels ea 1 10 1 3 3 6 2 1 3 2 2 1
Everton 7 11 11 5 6 7 7 8 5 5 7 11
Hudders field T.
Leices ter City 12 1 4
Liverpool 4 8 6 2 7 8 6 7 2 4 3 3
M. City 3 4 2 1 2 1 3 5 10 9 14 15
M. United 6 5 4 7 1 2 1 2 1 1 1 2
New Cas tle U. 18 15 10 16 5 12 18 12 13 7
Southampton 8 6 7 8 14
Stoke City 13 9 9 9 13 14 13 11 12
Swans ea 15 12 8 12 9 11
Tottenham 2 3 5 6 5 4 5 4 8 11 5 5
Watford 17 13
WBA 10 14 13 17 8 10 11
WHU 11 7 12 13 10
Seasonal prediction average: 78%

9. SPORTIVE ASSETS (TEAM/PLAYER):
TREND PREDICTION -PAST TEST
RESULTS-
Predicted matchs # >5,15< >15,40< >40,70< 70+
Trend reliability (main trend) %60 %70 %75 %85
League (trend) %50 %70 %70 %85
Non League(trend) %50 %70 %70 %85
weekday(trend) %50 %65 %70 %85
weekend (trend) %50 %65 %70 %85
# of wins (trend) %50 %60 %65 %70
# of non wins(trend) %55 %60 %65 %70
# of goal scored(trend) %55 %60 %65 %70
# of goal conceded (trend) %55 %60 %60 %70
goal margin(trend) %55 %55 %65 %70
PREDICITON SUCCESS RATIO: AVERAGE FOR WHOLE LEAGUES

10. Personal
 Web site: www.cemsengezer.com
 New method-model support for competitive advantage
 : www.sportsmedicineturkey.com/en/about-us/our-consultants
 Instructor on “Sports Math” for new method development
 : http://sem.medipol.edu.tr/Egitim/Icerik/104
 Financial markets commentator:
 www.paraborsa.net