This document discusses analyzing play-by-play data from NFL games from 2002-2012 that was released by Advanced NFL Stats. It contains over 470,000 individual play entries and details analyzing the data using tools like MapReduce, Hive, and examining factors like weather, stadiums, player arrests and their effects on games. Examples of analyses shown include the percentage of different play types in varying game situations and weather conditions.

1. 1
Headline Goes Here
Speaker Name or Subhead Goes Here
DO NOT USE PUBLICLY
PRIOR TO 10/23/12
Doing Data Science on the
NFL Play by Play Dataset
Jesse Anderson | Curriculum Developer and Instructor
July 2013 v2

2. Plays
2
• Advanced NFL
stats released all
Play by Play since
2002 season
• 2,898 total games
• 471,392 plays

3. Full Play Entry
3
20121119_CHI@SF,3,1
7,48,SF,CHI,3,2,76,20,
0,(2:48) C.Kaepernick
pass short right to
M.Crabtree to SF 25
for 1 yard (C.Tillman).
Caught at SF 25. 0-yds
YAC,0,3,0,27,7 ,2012

4. Play Description
4
(2:48) C.Kaepernick
pass short right to
M.Crabtree to SF
25 for 1 yard
(C.Tillman). Caught
at SF 25. 0-yds YAC

5. There's A Chart for That
5

6. There's A Custom MapReduce Behind That
6
public class IncompletesMapper extends
Mapper<LongWritable, Text, Text, PassWritable> {
@Override
public void map(LongWritable key, Text value, Context context) throws
IOException, InterruptedException {
String line = value.toString();
if (line.contains("incomplete")) {
Matcher matcher = incompletePass.matcher(line);
if (matcher.find()) {
context.write(new Text(matcher.group(1) + "-" +
matcher.group(2)), new PassWritable(1,Integer.parseInt(matcher.group(3))));

7. 7
The Hive Story
Enter the Query

8. Queryable Data
8
Give me every run
play by New Orleans in
the 2010 season

9. From the Data: Fourth Downs
9
15% of 4th down
plays weren't kicks

10. Play by Play Pieces
10
(2:48) C.Kaepernick
pass short right to
M.Crabtree to SF
25 for 1 yard
(C.Tillman). Caught
at SF 25. 0-yds YAC

11. From the Data: Sacks
11
QB sacks and
scrambles
double on 3rd downs

12. Hive
• Abstraction on top of
MapReduce
• Allows queries using a SQL-like
language
12

13. Hive Query
13
Give me every run by
New Orleans in the
2010 season:
SELECT * FROM
playbyplay WHERE
playtype = "RUN"
and year = 2010
and game like
"%NO%";

14. From the Data: Yards to Go
14
With 1 yard to go, 65%
of plays are runs

15. 15
Lost in data
Algorithm Alone

16. Data Janitorial
16

17. From the Data: Number of Plays By Yard Line
17
Direction of Offense

18. Stadium
18

19. Figuring Out Stadium
19
20121119_CHI@SF
Date Played Away Team Home Team

20. From the Data: Stadium Attendance
20
Stadiums with the smallest
capacities average the best
scores 20.55-17.79

21. Stadium Data
21
Stadium The capacity of the stadium
Expanded Capacity The expanded capacity of the stadium
Location The location of the stadium
Playing Surface The type of grass, etc that the stadium has
Is Artificial Is the playing surface artificial
Team The name of the team that plays at the stadium
Roof Type The type of roof in the stadium (None, Retractable, Dome)
Elevation The elevation of the stadium

22. From the Data: Stadium Elevation
22
There is a 1%
increase in passes at
Mile High versus sea
level stadiums

23. Weather
23
1,015 games had weather

24. From the Data: Fumble
24
Games with weather
have a fumble 93%
of the time
compared to 56%
without

25. Weather Data
25
STATION Station identifier
STATION NAME Station location name
READING DATE Date of reading
PRCP Precipitation
AWND Average daily wind speed
WV20 Fog, ice fog, or freezing fog (may include heavy fog)
TMAX
Maximum temperature
TMIN Minimum temperature

26. From the Data: Home Field Advantage
26
Baltimore has the
biggest weather
advantage 22-14

27. Arrests
27

28. Arrest Data
28
Season Player Arrested in (February to February)
Team Team person played on
Player Name of player Arrested
Player Arrested Was a player in the play arrested that season
Offense Player Arrested Offense had player arrested in season
Defense Player Arrested Defense had player arrested in season
Home Team Player Arrested Home Team had player arrested in season
Away Team Player Arrested Away Team had player arrested in season

29. Whenever there are
arrests either in the
home team, away team
or both, the home team
29
From 2002 to 2012, each
team had many arrests.
From to a low in 2002 of
56% to a
HIGH OFWINS
Arrest = Win?

30. 30

31. 31

32. 32
The Low Downs
• /me - http://www.jesse-anderson.com
• @jessetanderson
• Code - https://github.com/eljefe6a/nfldata
*I am not in any way affiliated with the NFL or any Team

33. 33

34. From the Data: Weather
34
Wind had the most effect on
games
At calm winds 41% pass and
37% run
At >30 MPH 34% pass and 46%
run

35. From the Data: Field Goals
35
Weather only increases
misses by %1
14% of Field Goals are
missed
21% of Field Goals are
missed 30-39 MPH
average winds