If the API allows these many calls, you can use a multiprocessing.pool.Pool function and iterate through each page parallelly to reduce time. This should work:

Copyimport requests
from functools import partial
from multiprocessing.pool import Pool

def loop(page,year,r,per_page):

   r = requests.get('https://jsonmock.hackerrank.com/api/football_matches?year='+str(year)+'&page='+str(page)).json()
   try:
      for i in range(0, per_page):
         if int(r['data'][i]['team1goals']) == int(r['data'][i]['team2goals']):
            increase = 1
         else:
            increase = 0
   except:
      increase = 0
   
   return increase

if __name__ == "__main__":
    
   year = 2011
   draw = []
   r = requests.get('https://jsonmock.hackerrank.com/api/football_matches?year='+str(year)+'&page=1').json()
   total_pages = r['total_pages']
   per_page = r['per_page']
   pages = range(1, total_pages+1)
   pool = Pool()
   f = pool.map(partial(loop,year=year,r=r,per_page=per_page),pages)
   draw += f
   final = 0
   for x in draw:
      x = int(x)
      final += x

   print(final) #516