mdgoldberg
Getting Play by Play Data
I am interested in trying to predict offensive playcalls for the NFL. Is there a way to get play by play data with info about what type of play was called (run left, run right, run middle, deep pass, short pass, etc). Even just knowing if the play was a run or a pass is enough. If so, can you suggest a script that would do so?
Thanks, Sanchez
It is possible, in fact I have done a very similar project already! You can read about it here. To get play by play data, check out the nfl.BoxScore.pbp function, used as so:
from sportsref import nfl
bs = nfl.BoxScore('201602070den')
df = bs.pbp()
# df is a DataFrame of play-by-play data, where each row is a play
It's not perfect, but it will have the main categories. For what purposes are you interested in predicting playcalls?
Thanks. That article is very similar what I was planning on doing. When I ran the code you suggested, though, I got this error:
----> 1 from sportsref import nfl
2 bs = nfl.BoxScore('201602070den')
3 df = bs.pbp()
4 # df is a DataFrame of play-by-play data, where each row is a play
C:\Users\Jacob\Anaconda2\lib\site-packages\sportsref\__init__.py in <module>()
10 import decorators
11 import utils
---> 12 import nfl
13 import nba
14
C:\Users\Jacob\Anaconda2\lib\site-packages\sportsref\nfl\__init__.py in <module>()
----> 1 import finders
2 import teams
3 import players
4 import boxscores
5 import winProb
C:\Users\Jacob\Anaconda2\lib\site-packages\sportsref\nfl\finders\__init__.py in <module>()
13 # Fill in PlayerSeasonFinder docstring
14
---> 15 IOD = PSF.inputs_options_defaults()
16
17 paramStr = '\n'.join(
C:\Users\Jacob\Anaconda2\lib\site-packages\sportsref\decorators.pyc in wrapper(*args, **kwargs)
27 orig_cwd = os.getcwd()
28 os.chdir(dirPath)
---> 29 ret = func(*args, **kwargs)
30 os.chdir(orig_cwd)
31 return ret
C:\Users\Jacob\Anaconda2\lib\site-packages\sportsref\nfl\finders\PSF.pyc in inputs_options_defaults()
168 print 'Regenerating PSFConstants file'
169
--> 170 html = utils.get_html(PSF_URL)
171 doc = pq(html)
172
C:\Users\Jacob\Anaconda2\lib\site-packages\sportsref\decorators.pyc in wrapper(*args, **kwargs)
197 return ret
198 except KeyError:
--> 199 cache[key] = fun(*args, **kwargs)
200 ret = _copy(cache[key])
201 return ret
C:\Users\Jacob\Anaconda2\lib\site-packages\sportsref\decorators.pyc in wrapper(url)
147 # otherwise, download html and cache it
148 else:
--> 149 text = func(url)
150 with open(filename, 'w+') as f:
151 f.write(text.encode('ascii', 'replace'))
C:\Users\Jacob\Anaconda2\lib\site-packages\sportsref\utils.pyc in get_html(url)
23 start = time.time()
24 browser = webdriver.PhantomJS(service_args=['--load-images=false'],
---> 25 service_log_path='/dev/null')
26 browser.set_window_size(10000, 10000)
27 browser.get(url)
C:\Users\Jacob\Anaconda2\lib\site-packages\selenium\webdriver\phantomjs\webdriver.pyc in __init__(self, executable_path, port, desired_capabilities, service_args, service_log_path)
49 port=port,
50 service_args=service_args,
---> 51 log_path=service_log_path)
52 self.service.start()
53
C:\Users\Jacob\Anaconda2\lib\site-packages\selenium\webdriver\phantomjs\service.pyc in __init__(self, executable_path, port, service_args, log_path)
48 self._cookie_temp_file = None
49
---> 50 service.Service.__init__(self, executable_path, port=port, log_file=open(log_path, 'w'))
51
52 def _args_contain(self, arg):
IOError: [Errno 2] No such file or directory: '/dev/null'
Do you how to fix this error?
Out of curiosity, what are you planning on using my package for? Also, that bug should be fixed.
On Dec 19, 2016, 8:15 PM -0500, theSanchize3 [email protected], wrote:
Thanks. That article is very similar what I was planning on doing. When I ran the code you suggested, though, I got this error:
----> 1 from sportsref import nfl 2 bs = nfl.BoxScore('201602070den') 3 df = bs.pbp() 4 # df is a DataFrame of play-by-play data, where each row is a play
C:\Users\Jacob\Anaconda2\lib\site-packages\sportsref_init_.py in
() 10 import decorators 11 import utils ---> 12 import nfl 13 import nba 14 C:\Users\Jacob\Anaconda2\lib\site-packages\sportsref\nfl_init_.py in
() ----> 1 import finders 2 import teams 3 import players 4 import boxscores 5 import winProb C:\Users\Jacob\Anaconda2\lib\site-packages\sportsref\nfl\finders_init_.py in
() 13 # Fill in PlayerSeasonFinder docstring 14 ---> 15 IOD = PSF.inputs_options_defaults() 16 17 paramStr = '\n'.join( C:\Users\Jacob\Anaconda2\lib\site-packages\sportsref\decorators.pyc in wrapper(*args, **kwargs) 27 orig_cwd = os.getcwd() 28 os.chdir(dirPath) ---> 29 ret = func(*args, **kwargs) 30 os.chdir(orig_cwd) 31 return ret
C:\Users\Jacob\Anaconda2\lib\site-packages\sportsref\nfl\finders\PSF.pyc in inputs_options_defaults() 168 print 'Regenerating PSFConstants file' 169 --> 170 html = utils.get_html(PSF_URL) 171 doc = pq(html) 172
C:\Users\Jacob\Anaconda2\lib\site-packages\sportsref\decorators.pyc in wrapper(*args, **kwargs) 197 return ret 198 except KeyError: --> 199 cache[key] = fun(*args, **kwargs) 200 ret = _copy(cache[key]) 201 return ret
C:\Users\Jacob\Anaconda2\lib\site-packages\sportsref\decorators.pyc in wrapper(url) 147 # otherwise, download html and cache it 148 else: --> 149 text = func(url) 150 with open(filename, 'w+') as f: 151 f.write(text.encode('ascii', 'replace'))
C:\Users\Jacob\Anaconda2\lib\site-packages\sportsref\utils.pyc in get_html(url) 23 start = time.time() 24 browser = webdriver.PhantomJS(service_args=['--load-images=false'], ---> 25 service_log_path='/dev/null') 26 browser.set_window_size(10000, 10000) 27 browser.get(url)
C:\Users\Jacob\Anaconda2\lib\site-packages\selenium\webdriver\phantomjs\webdriver.pyc in init(self, executable_path, port, desired_capabilities, service_args, service_log_path) 49 port=port, 50 service_args=service_args, ---> 51 log_path=service_log_path) 52 self.service.start() 53
C:\Users\Jacob\Anaconda2\lib\site-packages\selenium\webdriver\phantomjs\service.pyc in init(self, executable_path, port, service_args, log_path) 48 self._cookie_temp_file = None 49 ---> 50 service.Service.init(self, executable_path, port=port, log_file=open(log_path, 'w')) 51 52 def _args_contain(self, arg):
IOError: [Errno 2] No such file or directory: '/dev/null'
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I waht to see if I can determine which coaches are the most predictable, and if i can do that, determine if predictability affects success in any way. And thank you, I'll try it again when I get a chance.