Vegas Lines

OLD REPO -- SCRAPER NO LONGER WORKS. USE THE bettoR PACKAGE. Now the bettoR scraper function no longer works.

This function is used to scrape the historical Vegas Lines for NFL and NBA games

# Load libraries
library(lubridate)
library(tidyverse)
library(rvest)
library(magrittr)
library(knitr)

The magic

# this is the function
GetLines <- function(sport = "NBA", year, type = "both") {
  
  options(stringsAsFactors = FALSE)
  sport <- tolower(sport)
  
  # Get team urls and names
  url <- paste0("http://www.covers.com/pageLoader/pageLoader.aspx?page=/data/", sport, "/teams/teams.html")
  html <- suppressWarnings(readLines(url))
  links <- html[grep(paste0("/data/", sport, "/teams/team[0-9]"), html)]
  links <- unique(gsub(paste0('.*/data/', sport,'/teams/([^\"]*)\"[ ]*>([^<]*).*'), '\\1,\\2', links))
  links <- strsplit(links, ',')
  
  # Create URL stems for getting team records
  url.base <- paste(gsub("SPORT", sport, "http://www.covers.com/pageLoader/pageLoader.aspx?page=/data/SPORT/teams/pastresults/"), year - 1, '-', year, '/', sep = '')
  full.lines <- data.frame()
  
  # Put all team records in one data frame
  for (i in 1:length(links)) {
    
    url <- paste(url.base, links[[i]][1], sep = "")
    tables <- read_html(url) %>% html_table(header = TRUE, fill = TRUE) 
    
    # Get appropriate data: regular season, playoffs, or both
    if (type == 'regular season') {
      
      if (length(tables) == 0) {  # If the team didn't exist at the time, make an empty df
        temp <- data.frame(matrix(nrow = 1, ncol = 6, data = 0))
        temp <- temp[-1, ]
      } else {
        if (sport == 'nfl') {
          temp <- tables[[length(tables) - 1]]  # Regular season is always the second to last table
        } else if (sport == 'nba') {
          temp <- tables[[length(tables)]]      # Regular season is always the last table
        }
      }
      
    } else if (type == 'playoffs') {
      
      if (length(tables) == 1) {  # If the team didn't make the playoffs, make an empty df
        temp <- data.frame(matrix(nrow = 1, ncol = 6, data = 0))
        temp <- temp[-1, ]
      } else {
        temp <- tables[[1]]
      }
      
    } else {
      
      if (length(tables) == 0) {  # If the team didn't exist at the time, make an empty df
        temp <- data.frame(matrix(nrow = 1, ncol = 6, data = 0))
        temp <- temp[-1, ]
      } else {
        if (sport == 'nfl') {
          if (length(tables) == 2) {
            temp <- tables[[1]]
          } else {
            temp <- rbind(tables[[1]], tables[[2]])
          }
        } else if (sport == 'nba') {
          if (length(tables) == 1) {
            temp <- tables[[1]]
          } else {
            temp <- rbind(tables[[1]], tables[[2]])
          }
        }
      }
      
    }
    
    colnames(temp) <- c("date", "away.team", "score", "type", "home.line", "over.under")
    
    if (nrow(temp) > 0) {   # Add home team if the df has any info (we didn't ask for playoffs from a team that didn't make it)
      temp$home.team <- links[[i]][2]
    }
    
    try(full.lines <- rbind(full.lines, temp), silent = FALSE)
  }
  
  # Extra formatting for NFL df
  if (sport == 'nfl') {
    full.lines <- full.lines %>% filter(score != "BYE") 
    full.lines$date <- gsub("[A-Za-z ]*", "", full.lines$date)
  }
  
  # Format date
  full.lines$date <- mdy(full.lines$date)
  
  # Remove away games (the odds exist for home team already)
  full.lines <- full.lines[-grep('@', full.lines$away.team), ]
  
  # Create home score and away score columns
  full.lines$home.score <- as.numeric(gsub('[^0-9]*([0-9]+)-([0-9]+)[^0-9]*', '\\1', full.lines$score))
  full.lines$away.score <- as.numeric(gsub('[^0-9]*([0-9]+)-([0-9]+)[^0-9]*', '\\2', full.lines$score))
  
  # Fix line and over/under
  full.lines$home.line <- as.numeric(gsub('[^0-9\\.-]', '', full.lines$home.line))
  full.lines$over.under <- as.numeric(gsub('[^0-9\\.-]', '', full.lines$over.under))
  
  # Reorder columns, sort by date, and return
  full.lines <- full.lines[, c('date', 'type', 'home.team', 'away.team', 'home.score', 'away.score', 'home.line', 'over.under')]
  full.lines <- full.lines[order(full.lines$date), ]
  return(full.lines)
}

This is how to use the function

Parameters:

• sport: As of right now, only NFL and NBA have been fully tested... I will be adding NHL, NCAAF, NCAAB, and MLB eventually.
  • "NBA"
  • "NFL"
• year: season. (2012 would return the data from the 2011-2012 season)
• type:
  • "regular season"
  • "playoffs"
  • "both"

# example
NFL.2017 <- GetLines(sport = "NFL", year = 2017, type = "both")

Jackpot!!

kable(NFL.2017)

	date	type	home.team	away.team	home.score	away.score	home.line	over.under
217	2016-09-08	Week 1	Denver	Carolina	21	20	3.0	40.5
68	2016-09-11	Week 1	N.Y. Jets	Cincinnati	22	23	-1.0	42.0
84	2016-09-11	Week 1	Baltimore	Buffalo	13	7	-3.0	44.5
153	2016-09-11	Week 1	Houston	Chicago	23	14	-5.5	43.0
169	2016-09-11	Week 1	Indianapolis	Detroit	35	39	-2.5	51.0
185	2016-09-11	Week 1	Jacksonville	Green Bay	23	27	3.5	47.0
201	2016-09-11	Week 1	Tennessee	Minnesota	16	25	2.5	40.0
234	2016-09-11	Week 1	Kansas City	L.A. Chargers	33	27	-6.5	45.5
284	2016-09-11	Week 1	Dallas	N.Y. Giants	19	20	-1.0	47.5
317	2016-09-11	Week 1	Philadelphia	Cleveland	29	10	-4.0	41.5
420	2016-09-11	Week 1	Atlanta	Tampa Bay	24	31	-2.5	46.5
452	2016-09-11	Week 1	New Orleans	Oakland	34	35	-2.5	50.0
484	2016-09-11	Week 1	Arizona	New England	21	23	-9.0	44.5
534	2016-09-11	Week 1	Seattle	Miami	12	10	-10.5	43.5
333	2016-09-12	Week 1	Washington	Pittsburgh	16	38	2.5	49.0
516	2016-09-12	Week 1	San Francisco	L.A. Rams	28	0	2.5	43.0
15	2016-09-15	Week 2	Buffalo	N.Y. Jets	31	37	-1.0	40.5
51	2016-09-18	Week 2	New England	Miami	31	24	-5.5	42.0
115	2016-09-18	Week 2	Cleveland	Baltimore	20	25	4.0	42.0
134	2016-09-18	Week 2	Pittsburgh	Cincinnati	24	16	-3.0	48.0
152	2016-09-18	Week 2	Houston	Kansas City	19	12	1.0	41.5
216	2016-09-18	Week 2	Denver	Indianapolis	34	20	-6.0	47.0
249	2016-09-18	Week 2	L.A. Chargers	Jacksonville	38	14	-3.0	47.5
266	2016-09-18	Week 2	Oakland	Atlanta	28	35	-4.0	47.5
300	2016-09-18	Week 2	N.Y. Giants	New Orleans	16	13	-3.5	54.0
332	2016-09-18	Week 2	Washington	Dallas	23	27	-3.5	47.0
365	2016-09-18	Week 2	Detroit	Tennessee	15	16	-6.0	48.0
400	2016-09-18	Week 2	Minnesota	Green Bay	17	14	1.5	43.0
435	2016-09-18	Week 2	Carolina	San Francisco	46	27	-12.0	44.5
483	2016-09-18	Week 2	Arizona	Tampa Bay	40	7	-7.5	49.5
499	2016-09-18	Week 2	L.A. Rams	Seattle	9	3	5.5	38.0
348	2016-09-19	Week 2	Chicago	Philadelphia	14	29	-3.0	42.5
50	2016-09-22	Week 3	New England	Houston	27	0	NA	38.5
14	2016-09-25	Week 3	Buffalo	Arizona	33	18	5.0	48.0
31	2016-09-25	Week 3	Miami	Cleveland	30	24	-10.0	42.0
98	2016-09-25	Week 3	Cincinnati	Denver	17	29	-3.5	42.0
167	2016-09-25	Week 3	Indianapolis	L.A. Chargers	26	22	-1.5	51.5
183	2016-09-25	Week 3	Jacksonville	Baltimore	17	19	2.5	45.0
199	2016-09-25	Week 3	Tennessee	Oakland	10	17	1.5	47.0
232	2016-09-25	Week 3	Kansas City	N.Y. Jets	24	3	-3.0	44.5
282	2016-09-25	Week 3	Dallas	Chicago	31	17	-6.5	44.5
299	2016-09-25	Week 3	N.Y. Giants	Washington	27	29	-3.5	47.0
315	2016-09-25	Week 3	Philadelphia	Pittsburgh	34	3	3.5	46.5
383	2016-09-25	Week 3	Green Bay	Detroit	34	27	-6.0	47.5
434	2016-09-25	Week 3	Carolina	Minnesota	10	22	-6.0	43.0
466	2016-09-25	Week 3	Tampa Bay	L.A. Rams	32	37	-3.5	40.5
532	2016-09-25	Week 3	Seattle	San Francisco	37	18	-10.5	42.0
450	2016-09-26	Week 3	New Orleans	Atlanta	32	45	-2.5	54.0
97	2016-09-29	Week 4	Cincinnati	Miami	22	7	-7.5	46.0
49	2016-10-02	Week 4	New England	Buffalo	0	16	-3.5	41.0
65	2016-10-02	Week 4	N.Y. Jets	Seattle	17	27	1.0	40.0
81	2016-10-02	Week 4	Baltimore	Oakland	27	28	-3.5	45.0
132	2016-10-02	Week 4	Pittsburgh	Kansas City	43	14	-3.0	48.0
150	2016-10-02	Week 4	Houston	Tennessee	27	20	-4.0	40.0
182	2016-10-02	Week 4	Jacksonville	Indianapolis	30	27	1.0	48.0
247	2016-10-02	Week 4	L.A. Chargers	New Orleans	34	35	-3.5	54.0
330	2016-10-02	Week 4	Washington	Cleveland	31	20	-7.5	48.0
346	2016-10-02	Week 4	Chicago	Detroit	17	14	3.0	48.0
417	2016-10-02	Week 4	Atlanta	Carolina	48	33	2.5	48.5
465	2016-10-02	Week 4	Tampa Bay	Denver	7	27	3.5	43.0
481	2016-10-02	Week 4	Arizona	L.A. Rams	13	17	-10.0	43.5
513	2016-10-02	Week 4	San Francisco	Dallas	17	24	1.0	44.5
398	2016-10-03	Week 4	Minnesota	N.Y. Giants	24	10	-3.5	42.5
512	2016-10-06	Week 5	San Francisco	Arizona	21	33	3.5	42.5
29	2016-10-09	Week 5	Miami	Tennessee	17	30	-2.5	44.5
80	2016-10-09	Week 5	Baltimore	Washington	10	16	-4.0	44.5
112	2016-10-09	Week 5	Cleveland	New England	13	33	10.0	47.5
131	2016-10-09	Week 5	Pittsburgh	N.Y. Jets	31	13	-10.0	50.0
165	2016-10-09	Week 5	Indianapolis	Chicago	29	23	-4.0	47.5
213	2016-10-09	Week 5	Denver	Atlanta	16	23	-3.5	44.5
263	2016-10-09	Week 5	Oakland	L.A. Chargers	34	31	-3.5	50.5
280	2016-10-09	Week 5	Dallas	Cincinnati	28	14	2.5	46.0
362	2016-10-09	Week 5	Detroit	Philadelphia	24	23	3.5	46.0
382	2016-10-09	Week 5	Green Bay	N.Y. Giants	23	16	-7.0	49.0
397	2016-10-09	Week 5	Minnesota	Houston	31	13	-6.0	39.0
496	2016-10-09	Week 5	L.A. Rams	Buffalo	19	30	2.5	41.5
432	2016-10-10	Week 5	Carolina	Tampa Bay	14	17	-6.0	46.5
245	2016-10-13	Week 6	L.A. Chargers	Denver	21	13	3.0	44.0
11	2016-10-16	Week 6	Buffalo	San Francisco	45	16	-7.5	44.0
28	2016-10-16	Week 6	Miami	Pittsburgh	30	15	7.5	49.5
47	2016-10-16	Week 6	New England	Cincinnati	35	17	-7.5	48.0
148	2016-10-16	Week 6	Houston	Indianapolis	26	23	-3.0	47.5
196	2016-10-16	Week 6	Tennessee	Cleveland	28	26	-7.5	44.5
262	2016-10-16	Week 6	Oakland	Kansas City	10	26	1.0	46.5
296	2016-10-16	Week 6	N.Y. Giants	Baltimore	27	23	-3.5	42.5
328	2016-10-16	Week 6	Washington	Philadelphia	27	20	3.0	45.0
344	2016-10-16	Week 6	Chicago	Jacksonville	16	17	-2.5	46.0
361	2016-10-16	Week 6	Detroit	L.A. Rams	31	28	-2.5	44.0
381	2016-10-16	Week 6	Green Bay	Dallas	16	30	-5.0	47.0
448	2016-10-16	Week 6	New Orleans	Carolina	41	38	2.5	53.5
530	2016-10-16	Week 6	Seattle	Atlanta	26	24	-7.0	45.5
479	2016-10-17	Week 6	Arizona	N.Y. Jets	28	3	-7.0	45.5
380	2016-10-20	Week 7	Green Bay	Chicago	26	10	-7.5	46.5
27	2016-10-23	Week 7	Miami	Buffalo	28	25	2.5	46.0
62	2016-10-23	Week 7	N.Y. Jets	Baltimore	24	16	-2.5	40.0
94	2016-10-23	Week 7	Cincinnati	Cleveland	31	17	-11.0	46.5
129	2016-10-23	Week 7	Pittsburgh	New England	16	27	7.5	49.0
180	2016-10-23	Week 7	Jacksonville	Oakland	16	33	-2.0	47.5
195	2016-10-23	Week 7	Tennessee	Indianapolis	26	34	-4.0	48.0
229	2016-10-23	Week 7	Kansas City	New Orleans	27	21	-7.0	51.5
312	2016-10-23	Week 7	Philadelphia	Minnesota	21	10	3.0	39.0
360	2016-10-23	Week 7	Detroit	Washington	20	17	1.0	50.0
414	2016-10-23	Week 7	Atlanta	L.A. Chargers	30	33	-4.5	52.5
478	2016-10-23	Week 7	Arizona	Seattle	6	6	-2.5	43.0
494	2016-10-23	Week 7	L.A. Rams	N.Y. Giants	10	17	2.5	44.5
510	2016-10-23	Week 7	San Francisco	Tampa Bay	17	34	-1.0	45.0
211	2016-10-24	Week 7	Denver	Houston	27	9	-8.5	40.0
194	2016-10-27	Week 8	Tennessee	Jacksonville	36	22	-3.0	43.5
9	2016-10-30	Week 8	Buffalo	New England	25	41	5.5	48.0
93	2016-10-30	Week 8	Cincinnati	Washington	27	27	-3.0	49.0
109	2016-10-30	Week 8	Cleveland	N.Y. Jets	28	31	2.5	45.5
146	2016-10-30	Week 8	Houston	Detroit	20	13	-1.0	46.5
162	2016-10-30	Week 8	Indianapolis	Kansas City	14	30	3.0	50.5
210	2016-10-30	Week 8	Denver	L.A. Chargers	27	19	-3.5	43.0
278	2016-10-30	Week 8	Dallas	Philadelphia	29	23	-5.0	44.0
413	2016-10-30	Week 8	Atlanta	Green Bay	33	32	-3.0	51.0
430	2016-10-30	Week 8	Carolina	Arizona	30	20	-2.5	45.5
446	2016-10-30	Week 8	New Orleans	Seattle	25	20	1.0	50.0
462	2016-10-30	Week 8	Tampa Bay	Oakland	24	30	-1.0	48.0
342	2016-10-31	Week 8	Chicago	Minnesota	20	10	4.5	39.5
461	2016-11-03	Week 9	Tampa Bay	Atlanta	28	43	4.5	49.0
26	2016-11-06	Week 9	Miami	N.Y. Jets	27	23	-3.5	45.0
77	2016-11-06	Week 9	Baltimore	Pittsburgh	21	14	3.5	46.0
108	2016-11-06	Week 9	Cleveland	Dallas	10	35	7.0	49.0
227	2016-11-06	Week 9	Kansas City	Jacksonville	19	14	-7.0	42.5
242	2016-11-06	Week 9	L.A. Chargers	Tennessee	43	35	-3.5	47.5
259	2016-11-06	Week 9	Oakland	Denver	30	20	-1.0	44.5
294	2016-11-06	Week 9	N.Y. Giants	Philadelphia	28	23	-3.0	42.5
378	2016-11-06	Week 9	Green Bay	Indianapolis	26	31	-7.5	52.0
394	2016-11-06	Week 9	Minnesota	Detroit	16	22	-4.5	42.5
493	2016-11-06	Week 9	L.A. Rams	Carolina	10	13	3.0	44.5
509	2016-11-06	Week 9	San Francisco	New Orleans	23	41	5.0	53.0
527	2016-11-07	Week 9	Seattle	Buffalo	31	25	-5.5	43.5
76	2016-11-10	Week 10	Baltimore	Cleveland	28	7	-7.5	44.0
44	2016-11-13	Week 10	New England	Seattle	24	31	-7.5	49.5
59	2016-11-13	Week 10	N.Y. Jets	L.A. Rams	6	9	1.0	39.0
127	2016-11-13	Week 10	Pittsburgh	Dallas	30	35	-3.0	50.5
177	2016-11-13	Week 10	Jacksonville	Houston	21	24	-3.0	42.0
192	2016-11-13	Week 10	Tennessee	Green Bay	47	25	3.0	48.5
241	2016-11-13	Week 10	L.A. Chargers	Miami	24	31	-4.0	48.5
309	2016-11-13	Week 10	Philadelphia	Atlanta	24	15	-2.0	48.5
325	2016-11-13	Week 10	Washington	Minnesota	26	20	-2.5	42.0
428	2016-11-13	Week 10	Carolina	Kansas City	17	20	-3.0	44.0
444	2016-11-13	Week 10	New Orleans	Denver	23	25	-3.0	50.0
460	2016-11-13	Week 10	Tampa Bay	Chicago	36	10	2.5	45.0
476	2016-11-13	Week 10	Arizona	San Francisco	23	20	-13.5	46.5
293	2016-11-14	Week 10	N.Y. Giants	Cincinnati	21	20	1.0	49.5
427	2016-11-17	Week 11	Carolina	New Orleans	23	20	-3.5	52.5
91	2016-11-20	Week 11	Cincinnati	Buffalo	12	16	-2.5	48.0
106	2016-11-20	Week 11	Cleveland	Pittsburgh	9	24	8.0	45.5
160	2016-11-20	Week 11	Indianapolis	Tennessee	24	17	-3.0	53.5
225	2016-11-20	Week 11	Kansas City	Tampa Bay	17	19	-7.0	45.0
275	2016-11-20	Week 11	Dallas	Baltimore	27	17	-7.0	44.5
292	2016-11-20	Week 11	N.Y. Giants	Chicago	22	16	-7.0	41.5
324	2016-11-20	Week 11	Washington	Green Bay	42	24	-3.0	48.0
357	2016-11-20	Week 11	Detroit	Jacksonville	26	19	-5.5	47.0
392	2016-11-20	Week 11	Minnesota	Arizona	30	24	-2.0	39.5
491	2016-11-20	Week 11	L.A. Rams	Miami	10	14	-1.0	39.0
507	2016-11-20	Week 11	San Francisco	New England	17	30	10.5	51.5
525	2016-11-20	Week 11	Seattle	Philadelphia	26	15	-6.5	42.5
258	2016-11-21	Week 11	Oakland	Houston	27	20	-6.5	45.5
159	2016-11-24	Week 12	Indianapolis	Pittsburgh	7	28	8.0	50.0
274	2016-11-24	Week 12	Dallas	Washington	31	26	-5.5	53.0
356	2016-11-24	Week 12	Detroit	Minnesota	16	13	-1.5	42.0
6	2016-11-27	Week 12	Buffalo	Jacksonville	28	21	-8.5	43.5
23	2016-11-27	Week 12	Miami	San Francisco	31	24	-7.5	44.5
58	2016-11-27	Week 12	N.Y. Jets	New England	17	22	8.5	48.0
74	2016-11-27	Week 12	Baltimore	Cincinnati	19	14	-3.5	41.5
105	2016-11-27	Week 12	Cleveland	N.Y. Giants	13	27	6.5	46.5
143	2016-11-27	Week 12	Houston	L.A. Chargers	13	21	2.5	45.5
207	2016-11-27	Week 12	Denver	Kansas City	27	30	-3.5	40.0
257	2016-11-27	Week 12	Oakland	Carolina	35	32	-3.5	48.5
339	2016-11-27	Week 12	Chicago	Tennessee	21	27	6.5	41.5
410	2016-11-27	Week 12	Atlanta	Arizona	38	19	-4.0	49.0
442	2016-11-27	Week 12	New Orleans	L.A. Rams	49	21	-8.0	45.0
458	2016-11-27	Week 12	Tampa Bay	Seattle	14	5	5.0	46.0
307	2016-11-28	Week 12	Philadelphia	Green Bay	13	27	-4.0	47.0
390	2016-12-01	Week 13	Minnesota	Dallas	15	17	3.0	43.5
41	2016-12-04	Week 13	New England	L.A. Rams	26	10	-13.0	44.5
73	2016-12-04	Week 13	Baltimore	Miami	38	6	-3.5	41.5
89	2016-12-04	Week 13	Cincinnati	Philadelphia	32	14	-2.0	42.0
124	2016-12-04	Week 13	Pittsburgh	N.Y. Giants	24	14	-6.5	49.5
174	2016-12-04	Week 13	Jacksonville	Denver	10	20	3.5	38.5
239	2016-12-04	Week 13	L.A. Chargers	Tampa Bay	21	28	-3.5	49.0
256	2016-12-04	Week 13	Oakland	Buffalo	38	24	-3.0	48.5
338	2016-12-04	Week 13	Chicago	San Francisco	26	6	NA	44.0
374	2016-12-04	Week 13	Green Bay	Houston	21	13	-6.5	44.5
409	2016-12-04	Week 13	Atlanta	Kansas City	28	29	-5.0	50.0
441	2016-12-04	Week 13	New Orleans	Detroit	13	28	-6.5	53.0
473	2016-12-04	Week 13	Arizona	Washington	31	23	-2.5	48.5
523	2016-12-04	Week 13	Seattle	Carolina	40	7	-8.0	43.5
57	2016-12-05	Week 13	N.Y. Jets	Indianapolis	10	41	-1.0	48.5
222	2016-12-08	Week 14	Kansas City	Oakland	21	13	-3.5	46.0
4	2016-12-11	Week 14	Buffalo	Pittsburgh	20	27	1.0	45.5
21	2016-12-11	Week 14	Miami	Arizona	26	23	2.0	44.0
104	2016-12-11	Week 14	Cleveland	Cincinnati	10	23	4.5	42.0
157	2016-12-11	Week 14	Indianapolis	Houston	17	22	-6.5	47.5
173	2016-12-11	Week 14	Jacksonville	Minnesota	16	25	3.0	38.0
189	2016-12-11	Week 14	Tennessee	Denver	13	10	-2.0	44.0
289	2016-12-11	Week 14	N.Y. Giants	Dallas	10	7	3.5	47.0
305	2016-12-11	Week 14	Philadelphia	Washington	22	27	2.0	48.5
354	2016-12-11	Week 14	Detroit	Chicago	20	17	-7.5	42.0
373	2016-12-11	Week 14	Green Bay	Seattle	38	10	3.0	47.0
424	2016-12-11	Week 14	Carolina	L.A. Chargers	28	16	-1.0	48.5
456	2016-12-11	Week 14	Tampa Bay	New Orleans	16	11	-2.0	52.0
488	2016-12-11	Week 14	L.A. Rams	Atlanta	14	42	4.5	44.0
504	2016-12-11	Week 14	San Francisco	N.Y. Jets	17	23	-3.0	42.5
40	2016-12-12	Week 14	New England	Baltimore	30	23	-6.0	45.0
521	2016-12-15	Week 15	Seattle	L.A. Rams	24	3	-15.0	39.5
55	2016-12-17	Week 15	N.Y. Jets	Miami	13	34	2.5	40.0
3	2016-12-18	Week 15	Buffalo	Cleveland	33	13	-10.5	43.0
71	2016-12-18	Week 15	Baltimore	Philadelphia	27	26	-5.0	41.0
87	2016-12-18	Week 15	Cincinnati	Pittsburgh	20	24	3.0	45.5
140	2016-12-18	Week 15	Houston	Jacksonville	21	20	-3.5	39.5
204	2016-12-18	Week 15	Denver	New England	3	16	3.0	43.0
221	2016-12-18	Week 15	Kansas City	Tennessee	17	19	-6.0	43.0
237	2016-12-18	Week 15	L.A. Chargers	Oakland	16	19	2.5	49.5
271	2016-12-18	Week 15	Dallas	Tampa Bay	26	20	-7.0	47.5
288	2016-12-18	Week 15	N.Y. Giants	Detroit	17	6	-4.0	42.5
336	2016-12-18	Week 15	Chicago	Green Bay	27	30	4.5	40.0
388	2016-12-18	Week 15	Minnesota	Indianapolis	6	34	-5.0	44.5
407	2016-12-18	Week 15	Atlanta	San Francisco	41	13	-13.5	51.5
471	2016-12-18	Week 15	Arizona	New Orleans	41	48	-3.0	48.5
320	2016-12-19	Week 15	Washington	Carolina	15	26	-7.0	50.5
303	2016-12-22	Week 16	Philadelphia	N.Y. Giants	24	19	-1.5	42.5
2	2016-12-24	Week 16	Buffalo	Miami	31	34	-4.5	44.5
38	2016-12-24	Week 16	New England	N.Y. Jets	41	3	-17.0	45.0
102	2016-12-24	Week 16	Cleveland	L.A. Chargers	20	17	4.5	45.0
139	2016-12-24	Week 16	Houston	Cincinnati	12	10	-3.0	41.5
171	2016-12-24	Week 16	Jacksonville	Tennessee	38	17	4.0	44.0
253	2016-12-24	Week 16	Oakland	Indianapolis	33	25	-3.5	52.0
335	2016-12-24	Week 16	Chicago	Washington	21	41	3.0	49.0
371	2016-12-24	Week 16	Green Bay	Minnesota	38	25	-6.0	44.5
422	2016-12-24	Week 16	Carolina	Atlanta	16	33	3.0	49.0
438	2016-12-24	Week 16	New Orleans	Tampa Bay	31	24	-3.0	53.0
486	2016-12-24	Week 16	L.A. Rams	San Francisco	21	22	-6.0	39.5
520	2016-12-24	Week 16	Seattle	Arizona	31	34	-9.0	43.5
121	2016-12-25	Week 16	Pittsburgh	Baltimore	31	27	-5.5	46.5
220	2016-12-25	Week 16	Kansas City	Denver	33	10	-3.5	38.0
270	2016-12-26	Week 16	Dallas	Detroit	42	21	-6.5	46.5
18	2017-01-01	Week 17	Miami	New England	14	35	7.5	47.0
53	2017-01-01	Week 17	N.Y. Jets	Buffalo	30	10	3.5	43.0
85	2017-01-01	Week 17	Cincinnati	Baltimore	27	10	2.5	40.5
120	2017-01-01	Week 17	Pittsburgh	Cleveland	27	24	-3.0	41.5
154	2017-01-01	Week 17	Indianapolis	Jacksonville	24	20	-5.5	48.5
186	2017-01-01	Week 17	Tennessee	Houston	24	17	-3.0	41.5
202	2017-01-01	Week 17	Denver	Oakland	24	6	-1.0	40.0
235	2017-01-01	Week 17	L.A. Chargers	Kansas City	27	37	5.5	45.0
302	2017-01-01	Week 17	Philadelphia	Dallas	27	13	-6.5	44.0
318	2017-01-01	Week 17	Washington	N.Y. Giants	10	19	-9.0	47.5
351	2017-01-01	Week 17	Detroit	Green Bay	24	31	3.5	50.0
386	2017-01-01	Week 17	Minnesota	Chicago	38	10	-6.0	44.0
405	2017-01-01	Week 17	Atlanta	New Orleans	38	32	-7.5	58.5
453	2017-01-01	Week 17	Tampa Bay	Carolina	17	16	-3.0	44.5
485	2017-01-01	Week 17	L.A. Rams	Arizona	6	44	7.0	39.0
501	2017-01-01	Week 17	San Francisco	Seattle	23	25	11.5	45.0
137	2017-01-07	Wildcard	Houston	Oakland	27	14	-4.0	38.0
518	2017-01-07	Wildcard	Seattle	Detroit	26	6	-8.0	45.5
119	2017-01-08	Wildcard	Pittsburgh	Miami	30	12	-11.0	47.5
369	2017-01-08	Wildcard	Green Bay	N.Y. Giants	38	13	-5.0	46.5
36	2017-01-14	Divisional	New England	Houston	34	16	-16.0	44.0
404	2017-01-14	Divisional	Atlanta	Seattle	36	20	-6.5	51.0
218	2017-01-15	Divisional	Kansas City	Pittsburgh	16	18	-2.5	45.5
268	2017-01-15	Divisional	Dallas	Green Bay	31	34	-5.5	52.5
35	2017-01-22	Conference	New England	Pittsburgh	36	17	-5.5	50.0
403	2017-01-22	Conference	Atlanta	Green Bay	44	21	-6.5	59.5
402	2017-02-05	Super Bowl	Atlanta	New England	28	34	3.0	57.0

bonus function

This function will combine multiple seasons of data together.

Please be kind when scraping websites

GetLinesRange <- function(sport = "NBA", year.start, year.end, type = "both") {
  lines <- data.frame()
  
  for (year in year.start:year.end) {
    temp <- GetLines(sport, year, type)
    temp$season <- year
    lines <- rbind(lines, temp)
  }
  
  return(lines)
}