Analyzing Fantasy Football League Player Drafting for Optimal Results

This project analyzes player data from a fantasy football league, focusing on a match between the Philadelphia Eagles and Washington Redskins. The analysis employs statistical methods, including mean, standard deviation, and linear regression, to evaluate player performance (points, weight, age, position, rank, and tries). The findings indicate that the Philadelphia Eagles had a higher average tries and a lower standard deviation compared to the Washington Redskins, suggesting a better chance of winning. The project uses line charts to visualize player ranks against points and concludes that the Eagles' results are replicable. The statistical methods used are explained, along with their advantages, and the project references relevant academic sources. This analysis provides insights into optimizing fantasy football player drafting strategies for improved team performance.

SPORTS MANAGEMENT.
The teams used in the analysis were derived from a fantasy football league schedule where
Philadelphia Eagles Club and Washington Redskins were playing against each other.
The data shows the points, weight of players, age, position, rank, and tries of each
player from the past season. Also, a fantasy football league schedule was developed,
showing the teams their logos and the time to play. The data collected was analysed
with different methods to achieve the findings below.
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,
the 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 (RT Collins, 2013).
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( X
Wan, W Wang, J Liu, and T Tong,2014).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.
The following statistical methods were used:
Mean
This is the average where an individual adds up all the available numbers and divides them
by the number of figures (AL Barabási, R Albert and H Jeong, 2012).
Calculation of mean was used because of the following advantages;
i) In the estimate of the mean, all the data is taken into account to achieve an explainable
average (Y Ephraim and D Malah, 2013).
ii) Mean can be used as an observational link during studies by students or scientists (Y
Ephraim and D Malah, 2013).
Standard Deviation.
According to G Liu, J Zhou, B Jia, F He, Y Yang and N Sun,2019), this is a method used to
show how numbers of data or information are spread out.
Standard deviation as an analysis method was also used because of the following advantages;
i) The technique tells an individual how his or her data is spread out(R Paridar, M
Mozaffarzadeh, and V Periyasamy, 2019).
ii) The method can also not be easily influenced like other methods of dispersion during any
calculations(R Paridar, M Mozaffarzadeh, and V Periyasamy, 2019).
iii) The method can be used in price data’s or information to measure the volatility(R Paridar,
M Mozaffarzadeh, and V Periyasamy, 2019).

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 (HW Lilliefors, 2017).
Linear regression method was also applied in the analysis of the data because of the
following outstanding reasons.
i) Direct regression method makes the process of estimation look effortless and
straightforward to users (MH Pesaran, Y Shin, and RP Smith, 2019).
ii) The information derived from the use of the technique can easily be interpreted without
losing meaning(X Wan, W Wang, J Liu, and T Tong, 2014).
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(C Leys, C Ley, O Klein, P Bernard and L Licata (2013). 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(D Comaniciu and P Meer 2012).

REFERENCE.
AL Barabási, R Albert and H Jeong (2012) - Physica A: Statistical Mechanics and its …,
2012 - Elsevier
C Leys, C Ley, O Klein, P Bernard and L Licata (2013) - Journal of Experimental …, 2013 -
Elsevier
D Comaniciu and P Meer 2012) - IEEE Transactions on Pattern Analysis & …, 2012 -
computer.org.
G Liu, J Zhou, B Jia, F He, Y Yang and N Sun (2019) - Applied energy, 2019 - Elsevier
HW Lilliefors (2017) - Journal of the American statistical …, 2017 - amstat.tandfonline.com
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.
R Paridar, M Mozaffarzadeh, and V Periyasamy (2019)- Journal of …, 2019 - Wiley Online
Library
X Wan, W Wang, J Liu, and T Tong (2014) - BMC medical …, 2014 -
bmcmedresmethodol.biomedcentral …
Y Ephraim and D Malah (2013) - IEEE Transactions on acoustics, speech …, 2013 -
ieeexplore.ieee.org