3 Best Boxing games for IOS iPhone

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The best 3 Boxing games for IOS iPhone daily generated by our specialised A.I. comparing over 40 000 video games across all platforms for IOS iPhone. The order in this selection is not absolute, but the best games tends to be up in the list.

The latest addition in this selection are Prizefighters 2 released the 16 December 2020 and ranked #2, Deck 'Em! released the 3 September 2020 and ranked #3, Million Dungeon released the 11 June 2020 and ranked #1.

1# Million Dungeon - 2020

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Join us for an epic adventure spanning the six realms of man! Build your squad for thrilling tactical match-3 action! Strife plagues the land, and only one bold adventurer has what it takes to unravel the mysteries overtaking the world.

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2# Prizefighters 2 - 2020

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Screenshot of the video game Prizefighters 2
Screenshot of the video game Prizefighters 2
Screenshot of the video game Prizefighters 2

Prizefighters returns to the ring to take on all challengers as the best boxing game on the App Store! Start as an amateur and then train, spar, and climb the rankings to become a champion. - Manage all aspects of the league including booking every fight in Be the Promoter mode.

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3# Deck 'Em! - 2020

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Screenshot of the video game Deck 'Em!
Screenshot of the video game Deck 'Em!
Screenshot of the video game Deck 'Em!

Traceback (most recent call last): File "/usr/local/lib/python3.7/dist-packages/sumy/nlp/tokenizers.py", line 81, in _get_sentence_tokenizer return nltk.data.load(path) File "/usr/local/lib/python3.7/dist-packages/nltk/data.py", line 752, in load opened_resource = _open(resource_url) File "/usr/local/lib/python3.7/dist-packages/nltk/data.py", line 877, in _open return find(path_, path + [""]).open() File "/usr/local/lib/python3.7/dist-packages/nltk/data.py", line 585, in find raise LookupError(resource_not_found) LookupError: ********************************************************************** Resource punkt not found. Please use the NLTK Downloader to obtain the resource: >>> import nltk >>> nltk.download('punkt')  For more information see: https://www.nltk.org/data.html Attempted to load tokenizers/punkt/PY3/english.pickle Searched in: - '/root/nltk_data' - '/usr/nltk_data' - '/usr/share/nltk_data' - '/usr/lib/nltk_data' - '/usr/share/nltk_data' - '/usr/local/share/nltk_data' - '/usr/lib/nltk_data' - '/usr/local/lib/nltk_data' - '' ********************************************************************** During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/local/bin/sumy-3.7", line 10, in sys.exit(main()) File "/usr/local/lib/python3.7/dist-packages/sumy/__main__.py", line 68, in main summarizer, parser, items_count = handle_arguments(args) File "/usr/local/lib/python3.7/dist-packages/sumy/__main__.py", line 109, in handle_arguments parser = parser(document_content, Tokenizer(language)) File "/usr/local/lib/python3.7/dist-packages/sumy/nlp/tokenizers.py", line 69, in __init__ self._sentence_tokenizer = self._get_sentence_tokenizer(tokenizer_language) File "/usr/local/lib/python3.7/dist-packages/sumy/nlp/tokenizers.py", line 84, in _get_sentence_tokenizer "NLTK tokenizers are missing. Download them by following command: " LookupError: NLTK tokenizers are missing. Download them by following command: python -c "import nltk; nltk.download('punkt')"

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