Investigating the Relationship Between Birth Time Frame and National Football League Quarterback Success

by: Vincent L. Burrell

Many have postulated that children born after January one and before May of the same year have a distinct advantage in sports and various other activities. The belief is that being born earlier in the year provided an enormous advantage compared to those youths born later in the year--June thru December. Malcolm Gladwell, gained notoriety in his book Outliers, noted for youth hockey players in Canada, players that were born earlier in the year provided an enormous step up compared to those children born later in the year. This leads to those children born in earlier months of a given year with distinct mental and physical growth advantages as well as significantly larger experiential banks over their peers born in later months. Gladwell found evidence that these advantages lead to higher rates of success in youth hockey for those youths born earlier in a year than their younger counterparts born in the middle and end of that same year.

Gladwell’s research led to parents planning the birth of their children between the months of January and May of each year. In an attempt, to “Red Shirt” their children for school, thus gaining an advantage over other children in school. The term Red Shirt is used in collegiate sports to give athletes five years of National Collegiate Athletic Association (NCAA) eligibility. A NCAA athlete can be Red Shirted their first year of college to gain one additional year of collegiate sports eligibility. Parents are trying the same thing with their children. The advantage is gained because a Red Shirt child is older than their counterparts when entering school, thus gaining a size and experience advantage.

This sounds plausible; however, for the position of a National Football League (NFL) quarterback (QB) the advantage is between your ears (your thinking ability) and shoulder blades (your heart). I postulate that children born between March 21 – April 19, July 23 – Aug 22, and November 22 – December 23 are genetically pre-dispositioned to handle the quick thinking and fearlessness needed to succeed as a NFL QB. I phrase these dates as “Fire Sign” birth dates. An explanation of each are detailed below.

March 21 thru April 19 - Creative and ambitious, there is nothing they cannot accomplish in life only if motivated enough. Ready to take on challenges, good in times of crisis, they are innovators that can give the initiative energy for any type of endeavor and cause. When they build some tact and awareness of other people’s needs, they become incredible managers and leaders, with a talent to give others energy and reason to fight for a shared goal.

July 23 – Aug 22 - With so much energy, they always strive for greatness. Whether they succeed or not depends mostly on how they focus their energy, and remain calm in a time of need. In general, they are natural born leaders and will fully grasp the importance of respect in their professional relationships. If they have the same respect for those above them on the success scale, as for those below, they will have a chance to move very far and be loved by everyone they work for, and who works for them.

November 22 – December 23 - Once a they feel where their direction should lead, they strive high and tend to achieve truly great things in their professional path. People born in this time frame have a broad mind and they are able to change perspective with ease, until they find the right version of events or reasons for anything they want to examine. Highly adjustable and with a deep understanding for different people and in general. In a team, this is someone who will give everything they’ve got for others to succeed (leadership). I have followed the most successful QBs in the NFL and have noticed a trend. The traits mentioned above are closely related to what NFL QBs need to succeed. According to experts listed below are 12 qualities of Top-level NFL Quarterbacks.

The qualities of an elite NFL quarterback include:

  1. Combination of superior arm strength and pinpoint accuracy
  2. Sixth sense connection with receivers, ability to place the ball where only the receiver can get it
  3. Learns the offensive system and runs it with unfettered poise
  4. Studies film; able to read opponent's defensive schemes and anticipate their likely moves
  5. Able to stay calm while under pressure and make wise decisions about how best to distribute the ball
  6. Ability to quickly scan the entire field to find the most open receiver
  7. Mastery of the 2-minute offense
  8. Demonstrates leadership on the field; motivates and makes other players better
  9. Openly shares his appreciation and all success with the other members on the team
  10. The ability to lead a team back to victory in the fourth quarter.
  11. Rises to the occasion in all games; even more so in big games
  12. Win Championships.

I will sample approximately 250 NFL QBs, past and present. I postulate that members born on the dates listed below are genetically pre-disposed to excel as a NFL QBs.

March 21 thru April 19 July 23 – Aug 22 November 22 – December 23.


In [10]:
# import packages 
import pandas as pd                   # data management
import matplotlib.pyplot as plt       # graphics
import urllib
import numpy as np

# IPython command, puts plots in notebook 
%matplotlib inline

# check Python version 
import datetime as dt 
import sys
#versino 2.7
#print('Today is', dt.date.today())
#print('What version of Python are we running? \n', sys.version, sep='')

The following data was gathered from http://www.pro-football-reference.com/leaders/pass_yds_career.htm and provides National Football League (NFL) Quarterback (QB) statistics since the inception of the NFL.


In [12]:
player = pd.read_csv('QBStats3.csv', header=0, delimiter=",")

In [13]:
player.set_index('Rank')


Out[13]:
Player Yds Years Tm Birthday
Rank
1 Peyton Manning 71940 1998-2015 2TM Mar, 24
2 Brett Favre+ 71838 1991-2010 4TM Oct, 10
3 Drew Brees 66111 2001-2016 2TM Jan, 15
4 Tom Brady 61582 2000-2016 nwe Aug, 3
5 Dan Marino+ 61361 1983-1999 mia Sep, 15
6 John Elway+ 51475 1983-1998 den Jun, 28
7 Warren Moon+ 49325 1984-2000 4TM Nov, 18
8 Eli Manning 48218 2004-2016 nyg Jan, 3
9 Fran Tarkenton+ 47003 1961-1978 2TM Feb, 3
10 Ben Roethlisberger 46814 2004-2016 pit Mar, 2
11 Vinny Testaverde 46233 1987-2007 7TM Nov, 13
12 Philip Rivers 45833 2004-2016 sdg Dec, 8
13 Drew Bledsoe 44611 1993-2006 3TM Feb, 14
14 Carson Palmer 44269 2004-2016 3TM Dec, 27
15 Dan Fouts+ 43040 1973-1987 sdg Jun, 10
16 Kerry Collins 40922 1995-2011 6TM Dec, 30
17 Joe Montana+ 40551 1979-1994 2TM Jun, 11
18 Johnny Unitas+ 40239 1956-1973 2TM May, 7
19 Dave Krieg 38147 1980-1998 6TM Oct, 20
20 Boomer Esiason 37920 1984-1997 3TM Aug, 17
21 Matt Ryan 37701 2008-2016 atl May, 17
22 Donovan McNabb 37276 1999-2011 3TM Nov, 25
23 Aaron Rodgers 36827 2005-2016 gnb Dec, 2
24 Matt Hasselbeck 36638 1999-2015 4TM Sep, 25
25 Jim Kelly+ 35467 1986-1996 buf Feb, 14
26 Jim Everett 34837 1986-1997 3TM Jan, 3
27 Jim Hart 34665 1966-1984 2TM Apr, 29
28 Steve DeBerg 34241 1978-1998 6TM Jan, 19
29 Tony Romo 34183 2004-2016 dal Apr, 21
30 John Hadl 33503 1962-1977 4TM Feb, 15
... ... ... ... ... ...
221 Bob Avellini 7111 1975-1984 chi Aug, 28
222 Randy Wright 7106 1984-1988 gnb Jan, 21
223 Adrian Burk 7001 1950-1956 2TM Dec, 14
224 Dave Wilson 6987 1981-1988 nor Apr, 27
225 Steve Spurrier 6878 1967-1976 2TM Apr, 20
226 Steve Pelluer 6870 1984-1990 2TM Jul, 29
227 Christian Ponder 6658 2011-2014 min Feb, 25
228 Bobby Douglass 6493 1969-1978 4TM Jun, 22
229 Brandon Weeden 6462 2012-2015 3TM Oct, 14
230 Scott Brunner 6457 1980-1985 2TM Mar, 24
231 Hugh Millen 6440 1987-1995 4TM Nov, 22
232 Steve Ramsey 6437 1970-1976 2TM Apr, 22
233 Jim Miller 6387 1995-2002 2TM Feb, 9
234 Ty Detmer 6351 1993-2003 5TM Oct, 30
235 Dennis Shaw 6347 1970-1975 2TM Mar, 3
236 Quincy Carter 6337 2001-2004 2TM Oct, 13
237 Damon Huard 6303 1998-2008 3TM Jul, 9
238 Johnny Lujack 6295 1948-1951 chi Jan, 4
239 J.P. Losman 6271 2004-2011 3TM Mar, 12
240 Jack Concannon 6270 1964-1975 4TM Feb, 25
241 Tyrod Taylor 6257 2011-2016 2TM Aug, 3
242 Marcus Mariota 6244 2015-2016 oti Oct, 30
243 Jeff Kemp 6230 1981-1991 4TM Jul, 11
244 David Whitehurst 6205 1977-1983 gnb Apr, 27
245 Jacky Lee 6191 1960-1969 3TM Jul, 11
246 Teddy Bridgewater 6150 2014-2015 min Nov, 10
247 Matt Moore 6077 2007-2016 2TM Aug, 9
248 Frank Reich 6075 1985-1998 4TM Dec, 4
249 Trent Edwards 6033 2007-2012 3TM Oct, 30
250 Geno Smith 5962 2013-2016 nyj Oct, 10

250 rows × 5 columns


In [14]:
zodiac = pd.read_csv('QBStats4.csv', header=0, delimiter=",")

In [15]:
zodiac.set_index('Month Range')


Out[15]:
Range_Number Sign Designation Characterization
Month Range
March 21 - April 19 1 Aries Fire Sign
April 20 - May 20 2 Taurus Earth
May 21 - June 20 3 Gemini Air
June 21 - July 22 4 Cancer Water
July 23 - August 22 5 Leo Fire Sign
August 23 - September 22 6 Virgo Earth
September 23 - October 22 7 Libra Air
October 23 - November 21 8 Scorpio Water
November 22 - December 21 9 Sagittarius Fire Sign
December 22 - January 19 10 Capricorn Earth
January 20 - February 18 11 Aquarius Air
February 19 - March 20 12 Pisces Water

In [16]:
player_size = player["Rank"].size
    zodiac_size = zodiac["Range_Number"].size
    player_with_zodiac = []
    month_len = [31,  59,  90,  120,  151,  181,  212,  243,  273,  303,  333,  364]
    months = ["January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December"]
    months_abbr = ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]

In [17]:
for i in range(0, player_size):
    birth = player["Birthday"][i].split(",")
    month = birth[0].strip()
    day = birth[1].strip()
    index = months_abbr.index(month)
    if index == 0:
        birth_index = int(day)
    else:
        birth_index = month_len[index-1]+int(day)
    for j in range(0, zodiac_size):
        month_range = zodiac["Month Range"][j].split("-")
        start = month_range[0].strip().split(" ")
        end = month_range[1].strip().split(" ")
        start_month = start[0].strip()
        start_day = start[1].strip()

        start_index = months.index(start_month)
        if start_index == 0:
            left_index = int(start_day)
        else:
            left_index = month_len[start_index - 1] + int(start_day)

        end_month = end[0].strip()
        end_day = end[1].strip()

        end_index = months.index(end_month)
        if end_index == 0:
            right_index = int(end_day)
        else:
            right_index = month_len[end_index - 1] + int(end_day)

        if (left_index <= birth_index <= right_index) or (left_index > right_index and (left_index <= birth_index <= 364 or birth_index <= right_index)):
            player_with_zodiac.append({"name": player["Player"][i], "yds": player["Yds"][i], "sign": zodiac["Sign Designation"][j]})
            break

In [18]:
for i in range(0, zodiac_size):
    players = []
    yards = []
    #print zodiac["Sign Designation"][i]
    for each in player_with_zodiac:
        if each["sign"] == zodiac["Sign Designation"][i]:
            players.append(each["name"])
            yards.append(each["yds"])

    y_pos = np.arange(len(players))
    plt.bar(y_pos, yards, 0.4,align='center', alpha=0.5)
    plt.xticks(y_pos, players, rotation=90)

    plt.ylabel('Yards')
    plt.title(zodiac["Sign Designation"][i])
    plt.show()


Conclusion

Based on the data, it was discovered there is no one zodiac sign that dominates the passing leaders. Currently Peyton Manning is the passing leader with 71,940 yards passing and he is an Aries, which is a fire sign. However, the second most yards thrown by a quarterback is Brett Favre, and he falls under the sign of Libra, which is an air sign. Of the top ten passing leaders you have two fire signs, two air signs, three earth signs, and three water signs.