Web scraping ESPN NFL with Python

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Python

HTML5

webscraping

I am trying to perform web scraping using Python on the ESPN website to extract historical NFL football game results scores only into a csv file. I’m unable to find a way to add the dates as displayed in the desired output. Could someone help me a way to get the desired output from the current output. The website I am using to scrape the data and the desired output is below:

NFL Website:
[DELETED]

Current Output:
Week #, Away Team, Away Score, Home Team, Home Score
Week 17, Cowboys, 27, Titans, 13
Week 17, Cardinals, 19, Falcons, 20
Week 17, Bears, 10, Lions, 41

Desired Game Results Output:
Week #, Date, Away Team, Away Score, Home Team, Home Score
Week 17, 12/29/2022, Cowboys, 27, Titans, 13
Week 17, 1/1/2023, Cardinals, 19, Falcons, 20
Week 17, 1/1/2023, Bears, 10, Lions, 41

What I have tried:

from urllib.request import urlopen
import bs4
from bs4 import BeautifulSoup
import requests
import pandas as pd
import numpy as np

daterange = 1
url_list = []

while daterange < 19:
    url = "https://www.espn.com/nfl/scoreboard/_/week/"+str(daterange)+"/year/2022/seasontype/2"
    url_list.append(url)
    daterange = daterange + 1 


j = 1
away_team = []
home_team = []
away_team_score = []
home_team_score = []
week = []

for url in url_list:
    response = urlopen(url)
    urlname = requests.get(url)
    bs = bs4.BeautifulSoup(urlname.text,'lxml')
    print(response.url)
    i = 0
    while True:
        try:
            name = bs.findAll('div',{'class':'ScoreCell__TeamName ScoreCell__TeamName--shortDisplayName truncate db'})[i]
        except Exception:
            break

        name = name.get_text()
        try:
            score = bs.findAll('div',{'class':'ScoreCell__Score h4 clr-gray-01 fw-heavy tar ScoreCell_Score--scoreboard pl2'})[i]
        except Exception:
            break


        score = score.get_text()

        if i%2 == 0:
            away_team.append(name)
            away_team_score.append(score)

        else:
            home_team.append(name)
            home_team_score.append(score)
            week.append("week "+str(j))

        i = i + 1
    j = j + 1
    
web_scraping = list (zip(week, home_team, home_team_score, away_team, away_team_score))
web_scraping_df = pd.DataFrame(web_scraping, columns = ['week','home_team','home_team_score','away_team','away_team_score'])
web_scraping_df