你不需要指定想要的dict结果......也没有人可以阻止你使用复杂的解决方案。然而，这项工作可以用一种简单的方式来完成，使用python、requests、BeautifulSoup和panda：

import requests
from bs4 import BeautifulSoup
import pandas as pd

final_list = []

headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.17 (KHTML, like Gecko) Chrome/24.0.1312.60 Safari/537.17'}

for x in range(1, 7):
    r = requests.get(f'https://www.transfermarkt.es/transfers/transfertagedetail/statistik/top/land_id_zu/0/land_id_ab/0/leihe//datum/2022-07-10/sort//plus/2/page/{x}', headers=headers)
    soup = BeautifulSoup(r.text, 'html.parser')
    big_table = soup.select('table.items>tbody>tr')
    for row in big_table:
        name = row.find_all('td',  recursive=False)[0].select('td')[1]
        position = row.find_all('td',  recursive=False)[0].select('td')[2]
        age = row.find_all('td',  recursive=False)[1]
        nationality = row.find_all('td',  recursive=False)[2].select_one('img')['alt']
        origin_club = row.find_all('td',  recursive=False)[3].select('td')[1]
        origin_club_league = row.find_all('td',  recursive=False)[3].select('td')[2]
        new_club = row.find_all('td',  recursive=False)[4].select('td')[1]
        new_club_league = row.find_all('td',  recursive=False)[4].select('td')[2]
        value_when_transferred = row.find_all('td',  recursive=False)[5]
        cost = row.find_all('td',  recursive=False)[6]
        final_list.append((name.text.strip(), age.text.strip(), 
                           position.text.strip(), nationality, 
                           origin_club.text.strip(), origin_club_league.text.strip(), 
                           new_club.text.strip(), new_club_league.text.strip(), 
                           value_when_transferred.text.strip(),cost.text.strip()))
final_df = pd.DataFrame(final_list, columns = ['Name', 'Age', 'Position', 'Nationality', 
                        'Origin Club', 'Origin Club league', 'New Club', 'New Club League', 
                        'Value when transferred', 'Cost'])
final_df

这个 Dataframe 可以做成一个法令：

final_dict = final_df.to_dict()
final_dict

编辑：由于您现在正在确认所需的最终词典，您可以执行以下操作：

final_dict = {}
final_dict['Names'] = final_df['Name'][:2].tolist()
final_dict['Ages'] = final_df['Age'][:2].tolist()
final_dict['Positions'] = final_df['Position'][:2].tolist()
final_dict

将返回：

{'Names': ['Neco Williams', 'Omar Richards'],
 'Ages': ['21', '24'],
 'Positions': ['Lateral derecho', 'Lateral izquierdo']}

根据你张贴的标签scrapy并输出为字典，你可以尝试下一个例子：

import scrapy
from scrapy.crawler import CrawlerProcess

class TransferSpider(scrapy.Spider):     
    name = 'transfers'
    start_urls = ['https://www.transfermarkt.es/transfers/transfertagedetail/statistik/top/land_id_zu/0/land_id_ab/0/leihe//datum/2022-07-10/sort//plus/1/page/'+str(x)+'' for x in range(1,3)]

    custom_settings = {
        'CONCURRENT_REQUESTS_PER_DOMAIN': 1,
        'DOWNLOAD_DELAY': 1,
        'USER_AGENT': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/103.0.0.0 Safari/537.36',
        "FEEDS": {'data.json': {'format': 'json'}},
        "FEED_EXPORT_ENCODING": "utf-8",
        "INDENT":4
          }

    def parse(self, response):
        #for tr in response.xpath('//*[@class="items"]/tbody/tr'):

        yield {
            'names': response.xpath('//*[@class="items"]/tbody/tr/td[1]/table/tr[1]/td[2]/a/text()').getall(),
            'position': response.xpath('//*[@class="items"]/tbody/tr/td[1]/table/tr[2]/td/text()').getall(),
            'origin_club':response.xpath('//*[@class="items"]/tbody/tr/td[4]/table/tr/td[2]/a/text()').getall(),
            'leage_origin_club':response.xpath('//*[@class="items"]/tbody/tr/td[4]/table/tr[2]/td/a/text()').getall(),
            'new_club': response.xpath('//*[@class="items"]/tbody/tr/td[5]/table/tr[1]/td[2]/a/text()').getall(),
            'leage_new_club': response.xpath('//*[@class="items"]/tbody/tr/td[5]/table/tr[2]/td/a/text()').getall()
        }

if __name__ == '__main__':
    process = CrawlerProcess()
    process.crawl(TransferSpider)
    process.start()

输出：

{'names': ['Diego Vita', 'Julani Archibald', 'Alessio Benedetti', 'Santino Misale', 'Panagiotis Arnaoutoglou', 'Tauã', 'Igor Zeetti', 'Matías Nahuel', 'Hakob 
Hakobyan', 'Vojtech Brak', 'Jordi Calavera', 'Igor Kurylo', 'Aleksey Chubukin', 'Adrián Jiménez', 'Jesús del Amo', 'Giovanni Romano', 'Giuseppe Lopez', 'Sagas Tambi', 'Pedro Justiniano', 'Insar Salakhetdinov', 'Francesco Mele', 'Sina Moridi', 'Julen Monreal', 'Mahmoud Motlaghzadeh', 'Katriel Islamaj'], 'position': 
['Extremo derecho', 'Portero', 'Mediocentro', 'Lateral izquierdo', 'Lateral izquierdo', 'Extremo izquierdo', 'Defensa central', 'Extremo izquierdo', 'Lateral 
izquierdo', 'Defensa central', 'Lateral derecho', 'Defensa central', 'Defensa central', 'Defensa central', 'Defensa central', 'Extremo derecho', 'Delantero centro', 'Pivote', 'Defensa central', 'Pivote', 'Pivote', 'Pivote', 'Defensa central', 'Mediocentro', 'Mediocentro'], 'origin_club': ['Sanremese ', 'Santa Lucia FC', 'Arezzo', 'Gioiese', 'PASA Irodotos', 'PT Prachuap FC', 'Montespaccato', 
'CD Tenerife', 'FC Urartu ', 'Usti nad Labem', 'Girona FC', 'Agrobiznes V.', 'FK Saransk', 'CD Toledo', 'Ast. Vlachioti', 'Portici', 'Brindisi', 'Bnei Yehuda', 'Coimbra', 'Biolog', 'Chieti FC', 'Foolad', 'UE Costa Brava', 'Sanat Naft', 'Real Forte'], 'leage_origin_club': ['Serie D - A', 'Premier League

...等等