How to make the selenium page wait for the content

The website is giving me same results for different urls scraped. I guess the reason for this is that selenium is not letting the website load completely before producing the result. I wrote my code using beautiful soup first but according to SO community, selenium had to be used to get the final webpage to scrape. I implemented selenium to scrape the data and beautiful soup for parsing the data but still the same problem persists. The code is given below:

from bs4 import BeautifulSoup
import pandas as pd
import requests
import re
import datetime
import os
from selenium.webdriver import Chrome
from selenium.webdriver.chrome.options import Options
from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.common.by import By
from selenium.webdriver.support import expected_conditions as EC
date_list = pd.date_range(start = "1971-02-01", end=datetime.date.today(), freq='1d')


chrome_options = Options()  
chrome_options.add_argument("--headless") # Opens the browser up in background
driver = webdriver.Chrome()

def get_batsmen(date):
    url = f'https://www.icc-cricket.com/rankings/mens/player-rankings/odi/batting?at={date}'
    with Chrome(options=chrome_options) as browser:
        browser.get(url)
        html = browser.page_source
        browser.implicitly_wait(10)
        
    
    doc = BeautifulSoup(html, "html.parser")
    find_class = doc.find_all("td", class_ = 'table-body__cell rankings-table__name name')
    player_list = []
    find_top = doc.find('div', class_='rankings-block__banner--name-large')
    player_list.append(find_top.text)
    for item in find_class:
        player_name = item.find("a")
        # print(player_name.text)
        player_list.append(player_name.text)
    df = pd.DataFrame(player_list, columns = ['Player Name'])
    return df

def get_bowler(date):
    url = f'https://www.icc-cricket.com/rankings/mens/player-rankings/odi/bowling?at={date}'
    # page = requests.get(url).text
    with Chrome(options=chrome_options) as browser:
        browser.get(url)
        html = browser.page_source
    doc = BeautifulSoup(html, "html.parser")
    find_class = doc.find_all("td", class_ = 'table-body__cell rankings-table__name name')
    player_list = []
    find_top = doc.find('div', class_='rankings-block__banner--name-large')
    player_list.append(find_top.text)
    for item in find_class:
        player_name = item.find("a")
        # print(player_name.text)
        player_list.append(player_name.text)
    df = pd.DataFrame(player_list, columns = ['Player Name'])
    return df

def get_allrounder(date):
    url = f'https://www.icc-cricket.com/rankings/mens/player-rankings/odi/all-rounder?at={date}'
    # page = requests.get(url).text
    with Chrome(options=chrome_options) as browser:
        browser.get(url)
        html = browser.page_source
    doc = BeautifulSoup(html, "html.parser")
    find_class = doc.find_all("td", class_ = 'table-body__cell rankings-table__name name')
    player_list = []
    find_top = doc.find('div', class_='rankings-block__banner--name-large')
    player_list.append(find_top.text)
    for item in find_class:
        player_name = item.find("a")
        # print(player_name.text)
        player_list.append(player_name.text)
    df = pd.DataFrame(player_list, columns = ['Player Name'])
    return df

#Storing the data into multiple csvs

for date in date_list:
    year = date.year
    month = date.month
    day = date.day
    newpath = rf'C:\Users\divya\OneDrive\Desktop\8th Sem\ISB assignment\{year}'
    if not os.path.exists(newpath):
        os.makedirs(newpath)
    newpath1 = rf'C:\Users\divya\OneDrive\Desktop\8th Sem\ISB assignment\{year}\{month}'
    if not os.path.exists(newpath1):
        os.makedirs(newpath1)
    newpath2 = rf'C:\Users\divya\OneDrive\Desktop\8th Sem\ISB assignment\{year}\{month}\{day}'
    if not os.path.exists(newpath2):
        os.makedirs(newpath2)
    get_batsmen(date).to_csv(newpath2+'/batsmen.csv')
    get_bowler(date).to_csv(newpath2+'/bowler.csv')
    get_allrounder(date).to_csv(newpath2+'/allrounder.csv')

I will be eternally grateful to anyone who could help