cs:go Jak poprawić trustfactor i wyjść z red tf?

example features included in the training data may include, without limitation:

• an amount of time a player spent playing video games 110 in general, 
• an amount of time a player spent playing a particular video game 110, 
• times of the day the player was logged in and playing video games 110, 
• match history data for a player- e.g., total score (per match, per round, etc.), 
• headshot percentage, kill count, death count, assist count, player rank, etc., 
• a number and/or frequency of reports of a player cheating, a number and/or frequency of cheating acquittals for a player, 
• a number and/or frequency of cheating convictions for a player, 
• confidence values (score) output by a machine learning model that detected a player of cheat during a video game, 
• a number of user accounts 120 associated with a single player (which may be deduced from a common address, phone number, payment instrument, etc. tied to multiple user accounts 120), 
• how long a user account 120 has been registered with the video game service, 
• a number of previously-banned user accounts 120 tied to a player, 
• number and/or frequency of a player’s monetary transactions on the video game platform, 
• a dollar amount per transaction, a number of digital items of monetary value associated with a player’s user account 120, 
• number of times a user account 120 has changed hands (e.g., been transfers between different owners/players), a frequency at which a user account 120 is transferred between players, 
• geographic locations from which a player has logged-in to the video game service, 
• a number of different payment instruments, phone numbers, mailing addresses, etc. that have been associated with a user account 120 and/or how often these items have been changed, 
• and/or any other suitable features that may be relevant in computing a trust score 118 that is indicative of a player’s propensity to engage in a particular behavior.