For Data Science MIS 0855

1. ANDREW LIN, MATTHEW MOLLER, BENJAMIN
BAXTER, DHRUVIN SHETH, DAN
DEGREGORIO
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2. Question
● You are a GM and you are trying to figure out which
attacking position player would have the most impact
on your team.
● We want to find out if there is a correlation between
the top position players and their overall success
based off wins and losses.
● This is important because it identifies which players
have the most impact on a teams record.
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3. Data
● We used 3 data sets from the 2015-2016 Season
● 2015 Week 1-Week 10 Passing by QB Statistics
• YPG, # of TD, # of INT, Completion Percentage
● 2015 Week 1-Week 10 Rushing/Receiving by RB’s
Statistics
• RushYG, RushYA, RecYG, Rec TD, Rush TD
● 2015 Week 1-Week 10 Receiving by WR/TE Statistics
• RPG, YPG, # of Rec TD, Rec, Tgt
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4. QB
(([Cmp%]/10)*1)+(([Y/G]/20)*1)+([tdtointratio]*3)
W%
100%
67%
22%
78%
89%
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5. RB
● (([Rush Y/A]/2)*5)+(([Rush Y/G]/10)*2.5)+(([Rec
Y/G]/20*1))+([totaltd]*2.5)
W%
67%
44%
78%
56%
56%
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6. WR
● ([R/G]*1)+(([Y/G]/10)*1)+(([catch%]/5))+([TD]*1.5)
W%
67%
44%
78%
50%
60%
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7. Conclusion
● Quarterbacks are the most consistently valuable
players. They have the strongest correlation between
value and win to loss ratio. The only outlier is Phillip
Rivers.
● Wide Receivers and Running Backs have similar
correlations between value and win to loss. The teams
that had the top WR’s and RB’s tended to have
winning records, but the top quarterbacks had a
higher win percentage on average.
● You would want to pick up a better quarterback in
order to increase your chances of winning.
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8. References
● http://www.pro-football-reference.com/
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