Course Project: Fantasy Football Schedule and Player Analysis
VerifiedAdded on 2022/12/19
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Project
AI Summary
This project analyzes a fantasy football schedule, comparing the Washington Redskins and Philadelphia Eagles. It utilizes statistical methods including mean, standard deviation, and linear regression to evaluate player performance and predict match outcomes. The analysis calculates the mean and sta...

SPORTS
MANAGEMENT
Fantasy football
Schedule
PRESENTED BY:
DATE:
MANAGEMENT
Fantasy football
Schedule
PRESENTED BY:
DATE:
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MEAN
This is the average where an individual adds up all the available
numbers and divides them by the number of figures.
This is the average where an individual adds up all the available
numbers and divides them by the number of figures.

Advantages of Mean
i) In the estimate of the mean, all the data is taken into account to
achieve an explainable average.
ii) Mean can be used as an observational link during studies by
students or scientists
i) In the estimate of the mean, all the data is taken into account to
achieve an explainable average.
ii) Mean can be used as an observational link during studies by
students or scientists
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Standard Deviation
This is a method used to show how numbers of data or information
are spread out.
This is a method used to show how numbers of data or information
are spread out.
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Advantages of Standard Deviation.
i) The technique tells an individual how his or her data is spread out.
ii) The method can also not be easily influenced like other methods of
dispersion during any calculations.
iii) The method can be used in price data’s or information to measure
the volatility.
i) The technique tells an individual how his or her data is spread out.
ii) The method can also not be easily influenced like other methods of
dispersion during any calculations.
iii) The method can be used in price data’s or information to measure
the volatility.

Linear Regression.
This is a method in statistics used to show the relationship between
an independent variable and a dependent variable. This method is
also the most and basic used in predictive analysis among scientists
and students.
This is a method in statistics used to show the relationship between
an independent variable and a dependent variable. This method is
also the most and basic used in predictive analysis among scientists
and students.
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Advantages of Linear Regression.
i) Direct regression method makes the process of estimation look
effortless and straightforward to users.
ii) The information derived from the use of the technique can easily
be interpreted without losing meaning.
i) Direct regression method makes the process of estimation look
effortless and straightforward to users.
ii) The information derived from the use of the technique can easily
be interpreted without losing meaning.
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Findings.
From the data collected from Washington redskins the mean was calculated, and it was
49.7735849 compared to that of Philadelphia Eagles which was 50.1886792 this meant that
in the football fantasy league schedule Philadelphia Eagles would easily win the match
because it had a better average of the tries made by it is players. Also standard deviation
was used as a statistical method, Philadelphia Eagles had a standard mean of 28.3815357
while that of Washington redskins was 30.4238248.From the above standard deviation got
from the two teams Philadelphia Eagle team had a smaller standard deviation meaning the
points of data in the group are very close to the mean.
Linear regression method was also used from the method data for Washington Redskins
achieved a p-value of 4.2686E-25 while that of Philadelphia Eagles was 4.8966E-21.When
you compared the above figures from the actual intercept p values you find that the p-value
of Philadelphia eagles was close to the exact p-value achieved meaning that the results of
the team in terms of tries scored by each player are replicable.
Line charts were also drawn to show the ranks of the different players against their points in
the NFL. From the above statistical methods in the football fantasy league developed
Philadelphia Eagles against Washington Redskins match the Eagles team has a better chance
to win.
From the data collected from Washington redskins the mean was calculated, and it was
49.7735849 compared to that of Philadelphia Eagles which was 50.1886792 this meant that
in the football fantasy league schedule Philadelphia Eagles would easily win the match
because it had a better average of the tries made by it is players. Also standard deviation
was used as a statistical method, Philadelphia Eagles had a standard mean of 28.3815357
while that of Washington redskins was 30.4238248.From the above standard deviation got
from the two teams Philadelphia Eagle team had a smaller standard deviation meaning the
points of data in the group are very close to the mean.
Linear regression method was also used from the method data for Washington Redskins
achieved a p-value of 4.2686E-25 while that of Philadelphia Eagles was 4.8966E-21.When
you compared the above figures from the actual intercept p values you find that the p-value
of Philadelphia eagles was close to the exact p-value achieved meaning that the results of
the team in terms of tries scored by each player are replicable.
Line charts were also drawn to show the ranks of the different players against their points in
the NFL. From the above statistical methods in the football fantasy league developed
Philadelphia Eagles against Washington Redskins match the Eagles team has a better chance
to win.

Conclusions.
In conclusions mean calculated in data sets of the teams derived from
the fantasy football schedule generally is used to represent the symbolic
value as it can be used as observation in comparisons among different
amounts of data. The standard deviation also, in this case, has been
calculated. Usual, a low standard deviation is used to and explains that
the points of data are very close to the meanwhile a higher standard
deviation explains that the data value provided is very spread along
with a massive data. Linear regression was used, where an actual p-
value of Philadelphia Eagle’s fantasy league team was 6.7531E-28 while
that of the best lag was 4.8966E-21. This meant that the result achieved
in the tries and point of the different players of the Philadelphia Eagles
was replicable and also a substantial p-value less than 0.05 indicates
solid evidence against the null hypothesis and that suggest that an
alternative hypothesis, in any case, can be used.
In conclusions mean calculated in data sets of the teams derived from
the fantasy football schedule generally is used to represent the symbolic
value as it can be used as observation in comparisons among different
amounts of data. The standard deviation also, in this case, has been
calculated. Usual, a low standard deviation is used to and explains that
the points of data are very close to the meanwhile a higher standard
deviation explains that the data value provided is very spread along
with a massive data. Linear regression was used, where an actual p-
value of Philadelphia Eagle’s fantasy league team was 6.7531E-28 while
that of the best lag was 4.8966E-21. This meant that the result achieved
in the tries and point of the different players of the Philadelphia Eagles
was replicable and also a substantial p-value less than 0.05 indicates
solid evidence against the null hypothesis and that suggest that an
alternative hypothesis, in any case, can be used.
You're viewing a preview
Unlock full access by subscribing today!

References.
A Bangor, P Kortum and J Miller (2009) - Journal of usability studies, 2009 - dl.acm.org.
AL Barabási, R Albert and H Jeong (2012) - Physica A: Statistical Mechanics and its …, 2012 -
Elsevier
BM Byrne, RJ Shavelson, and B Muthén (2009) - Psychological bulletin, 2009 - psycnet.apa.org.
D Comaniciu and P Meer 2012) - IEEE Transactions on Pattern Analysis & …, 2012 - computer.org.
HW Lilliefors (2017) - Journal of the American statistical …, 2017 - amstat.tandfonline.com
MP Seah and WA Dench (2009) - Surface and interface analysis, 2009 - Wiley Online Library
MH Pesaran, Y Shin and RP Smith (2019) - Journal of the American Statistical …, 2019 - Taylor &
Francis
RT Collins (2013) - 2013 IEEE Computer Society Conference on …, 2013 - ieeexplore.ieee.org.
Y Yamamoto, MJ Yin, KM Lin and RB Gaynor (2009) - Journal of Biological Chemistry, 2009 –
ASBMB.
Y Ephraim and D Malah (2013) - IEEE Transactions on acoustics, speech …, 2013 -
ieeexplore.ieee.org
A Bangor, P Kortum and J Miller (2009) - Journal of usability studies, 2009 - dl.acm.org.
AL Barabási, R Albert and H Jeong (2012) - Physica A: Statistical Mechanics and its …, 2012 -
Elsevier
BM Byrne, RJ Shavelson, and B Muthén (2009) - Psychological bulletin, 2009 - psycnet.apa.org.
D Comaniciu and P Meer 2012) - IEEE Transactions on Pattern Analysis & …, 2012 - computer.org.
HW Lilliefors (2017) - Journal of the American statistical …, 2017 - amstat.tandfonline.com
MP Seah and WA Dench (2009) - Surface and interface analysis, 2009 - Wiley Online Library
MH Pesaran, Y Shin and RP Smith (2019) - Journal of the American Statistical …, 2019 - Taylor &
Francis
RT Collins (2013) - 2013 IEEE Computer Society Conference on …, 2013 - ieeexplore.ieee.org.
Y Yamamoto, MJ Yin, KM Lin and RB Gaynor (2009) - Journal of Biological Chemistry, 2009 –
ASBMB.
Y Ephraim and D Malah (2013) - IEEE Transactions on acoustics, speech …, 2013 -
ieeexplore.ieee.org
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