Item generation based on player data

Abstract

To provide item generation based on player data.SOLUTION: Systems and methods are described for providing an in-game item to a player. An instruction is received to generate an in-game item for a first player. A second player is identified based on a first metric. A second metric is generated based on at least data associated with the second player. The in-game item is generated based on the second metric and the in-game item is provided to the first player. In one embodiment, the first metric comprises a likelihood-of-engagement parameter associated with the second player. In one embodiment, the second metric comprises a user-specific item desirability score.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present disclosure relates to methods of providing in-game items to players. In particular, but not exclusively, the present disclosure relates to enhancing user experience and engagement by providing players with in-game items that may be of interest to other players to encourage interaction between players. Summary of the Invention [Means for solving the problem]

[0002] (Summary) Many genres of video games generate in-game items, ranging from car stickers in racing games to magical weapons in action games. Any given game has a vast library of potential in-game items to generate, and each game sets its own probability of unlocking different items (also referred to as "drop rates"). Depending on the game, the drop rates can be static or dynamic, changing based on player actions or game context. To generate in-game items, the game will usually generate a random number that is used to identify the item according to the game's drop rate. The item offered in this way is likely to be the most common outcome. However, players usually want a specific category of item (or even a specific item), and therefore the item offered is likely to be of no use to the player. This results in a disappointing experience for the player, which can negatively impact engagement.

[0003] Therefore, it is a non-exclusive object of the present disclosure to provide a method for solving the above problems.

[0004] According to a first aspect, a method is provided that includes receiving an instruction to generate an in-game item for a first player, identifying a second player based on a first metric, generating a second metric based on data associated with at least the second player, generating an in-game item based on the second metric, and providing the in-game item to the first player. This may encourage interaction between the first player and the second player, improving user engagement, since the first player is provided with an in-game item that is of interest to the second player. The first player and the second player may be related to each other via mechanisms defined in the game (such as a friends list, teammates, co-players, etc.).

[0005] In one embodiment, the first metric may comprise a likelihood of engagement parameter associated with the second player. The likelihood of engagement parameter may be determined based on data associated with the first and / or second player. All players in the game associated with the first player may have a likelihood of engagement parameter associated with them. This may facilitate player selection among one or more players associated with the first player such that the likelihood of engagement between the first player and the second player is maximized.

[0006] In one example, the second metric may comprise a user specific item desirability score (USIDS). The USIDS may be generated based on data associated with the second player regarding one or more items. The one or more items may be items available to provide to the first player among a set of in-game items. An advantage of using the USIDS may be to ensure that the generated items will be items desired by the second player (i.e., the target player), thereby maximizing the likelihood of user engagement.

[0007] In one example, the method may further comprise determining that the user-specific item desired score exceeds a threshold and providing an output to the first player when the user-specific item desired score associated with the second player exceeds the threshold, allowing the first player to be informed that the provided in-game item is desired by a player associated with the first player.

[0008] In one example, a second player may be indicated to a first player. The output may have user interface elements, such as sounds and / or visual elements. The output may comprise tactile elements. The sounds, visual elements and / or tactile elements may be perceived by the first player as associated with the second player.

[0009] In one example, the output may comprise a user interface element that facilitates an exchange of an item between a first player and a second player. The user interface element may comprise a form of an interaction element that, upon receiving input from the first player, initiates the item exchange process between the first player and the second player.

[0010] In one embodiment, the first metric and / or the second metric comprise one or more parameters associated with a game configuration. The one or more game parameters may be configured by a third party (such as a game developer).

[0011] In one example, the first metric may comprise at least one of total game play time, total play time spent by the first player, time since last played, character information and play history, percentage of play time spent by single player vs. multiplayer, number of peer-to-peer transactions conducted.

[0012] In one example, the first metric may comprise at least one of: a total play time across all games spent by a first player, a number of games previously played by the first player, a percentage of time spent in single player versus multiplayer games, a number and / or type of game titles owned, and a number of peer-to-peer transactions conducted across all games.

[0013] In one example, identifying the second player based on the first metric may include retrieving data associated with one or more players different from the first player and generating an engagement likelihood parameter for each one of the one or more players based on the data associated with the one or more players, where the first metric comprises a likelihood of engagement of at least one of the one or more players.

[0014] In one example, the method may include ranking one or more players based on a generated likelihood of engagement associated with the one or more players.

[0015] In one example, the method may include generating a third metric based on data associated with at least the first player, identifying a second in-game item based on the third metric, and providing media content to the first player that includes information associated with the second in-game item.

[0016] In one example, the third metric is generated based on data including total play time spent by a first player across one or all games, the number of games previously played by the first player, the percentage of time spent in single player versus multiplayer games, the number and / or type of game titles owned, and the number of peer-to-peer transactions conducted across one or all games. The present invention provides, for example, the following items. (Item 1) 1. A method, comprising: Receiving instructions to generate an in-game item for a first player; identifying a second player based on the first metric; generating a second metric based on data associated with at least the second player; generating the in-game item based on the second metric; and providing the first player with the in-game item; A method comprising: (Item 2) The method of any preceding claim, wherein the first metric comprises a likelihood of engagement parameter associated with the second player. (Item 3) The method of any preceding claim, wherein the second metric comprises a user-specific item desirability score. (Item 4) The method of any of the preceding items, further comprising determining that the user-specific item desired score exceeds a threshold and providing an output to the first player when the user-specific item desired score associated with the second player exceeds a threshold. (Item 5) 2. The method of claim 1, wherein the output indicates to the first player the second player. (Item 6) 2. The method of claim 1, wherein the output comprises a user interface element that facilitates the exchange of an in-game item between the first player and the second player. (Item 7) 2. The method of claim 1, wherein the first metric and / or the second metric comprises one or more parameters related to a game configuration. (Item 8) Identifying the second player based on the first metric includes: retrieving data associated with one or more players different from the first player; generating engagement likelihood parameters for said one or more players based on said data associated with said one or more players; and the first metric comprises a likelihood of engagement of at least one of the one or more players. A method according to any of the above items. (Item 9) 20. The method of claim 19, further comprising: ranking the one or more players based on the generated likelihood of engagement associated with each of the one or more players. (Item 10) generating a third metric based on data associated with at least the first player; identifying a second in-game item based on the third metric; and providing media content to the first player that includes information associated with the second in-game item; The method according to any of the above items, further comprising: (Item 11) The method of any of the preceding claims, wherein the third metric is generated based on data including total play time spent by the first player across one or all games, the number of games previously played by the first player, the percentage of time spent in single player versus multiplayer games, the number and / or type of game titles owned, and the number of peer-to-peer transactions conducted across one or all games. (Item 12) A system including a control circuit, the control circuit comprising: Receiving instructions to generate an in-game item for a first player; identifying a second player based on the first metric; generating a second metric based on data associated with at least the second player; generating the in-game item based on the second metric; and providing the in-game item to the first player; and A system configured to: (Item 13) The system of claim 1, wherein the first metric comprises a likelihood of engagement parameter associated with the second player. (Item 14) The system of any preceding item, wherein the second metric comprises a user-specific item desirability score. (Item 15) The system of any of the preceding items, wherein the control circuitry is configured to determine that the user-specific item desired score exceeds a threshold and to provide an output to the first player when the user-specific item desired score associated with the second player exceeds the threshold. (Item 16) The system of any of the preceding items, wherein the output indicates the second player to the first player. (Item 17) The system of any of the preceding claims, wherein the output comprises a user interface element that facilitates the exchange of in-game items between the first player and the second player. (Item 18) The system of any of the preceding items, wherein the first metric and / or the second metric comprise one or more parameters related to a game configuration. (Item 19) The control circuit includes: retrieving data associated with one or more players different from the first player; generating a likelihood of engagement parameter for each of the one or more players based on the data associated with the one or more players;

[0023] the first metric comprises the likelihood of engagement of at least one of the one or more players. 2. A system according to any one of the preceding items. (Item 20) The system of any of the preceding claims, wherein the control circuitry is configured to rank the one or more players based on the generated likelihood of engagement associated with each of the one or more players. (Item 21) generating a third metric based at least on data associated with the first player; identifying a second in-game item based on the third metric; and providing media content to the first player that includes information associated with the second in-game item; Item 11. The system of any of the preceding items, configured to: (Item 22) The system of any of the preceding items, wherein the third metric is generated based on data including total play time spent by the first player across one or all games, the number of games previously played by the first player, the percentage of time spent in single player versus multiplayer games, the number and / or type of game titles owned, and the number of peer-to-peer transactions conducted across one or all games. (Item 23) means for receiving instructions to generate an in-game item for a first player; means for identifying a second player based on the first metric; means for generating a second metric based at least on data associated with the second player; means for generating the in-game item based on the second metric; means for providing the in-game item to the first player; The system comprises: (Item 24) The system of any preceding item, wherein the second metric comprises a user-specific item desirability score. (Item 25) The system of any preceding item, wherein the second metric comprises a user-specific item desirability score. (Item 26) The system of any of the preceding items, further comprising: means for determining that the user-specific item desired score exceeds a threshold; and means for providing an output to the first player when the user-specific item desired score associated with the second player exceeds a threshold. (Item 27) The system of any of the preceding items, wherein the output indicates the second player to the first player. (Item 28) The system of any of the preceding claims, wherein the output comprises a user interface element that facilitates the exchange of in-game items between the first player and the second player. (Item 29) 2. The method of claim 1, wherein the first metric and / or the second metric comprises one or more parameters related to a game configuration. (Item 30) means for retrieving data associated with one or more players different from the first player; means for generating engagement likelihood parameters for said one or more players based on said data associated with said one or more players; Further equipped with the first metric comprises a likelihood of engagement of at least one of the one or more players. 2. A system according to any one of the preceding items. (Item 31) The system of any preceding claim, further comprising means for ranking the one or more players based on the generated engagement likelihood associated with each of the one or more players. (Item 32) means for generating a third metric based on data associated with at least the first player; means for identifying a second in-game item based on the third metric; a means for providing media content including information related to the second in-game item to the first player; 2. The system of claim 1, further comprising: (Item 33) The system of any of the preceding items, wherein the third metric is generated based on data including total play time spent by the first player across one or all games, the number of games previously played by the first player, the percentage of time spent in single player versus multiplayer games, the number and / or type of game titles owned, and the number of peer-to-peer transactions conducted across one or all games. (Item 34) A non-transitory computer readable medium having non-transitory computer readable instructions that, when executed by control circuitry, perform: Receiving instructions to generate an in-game item for a first player; identifying a second player based on the first metric; generating a second metric based at least on data associated with the second player; generating the in-game item based on the second metric; and providing the in-game item to the first player; and A non-transitory computer readable medium that causes the control circuit to perform the steps of: (Item 35) Item 35. The non-transitory computer-readable medium according to item 34, wherein the first metric comprises a likelihood of engagement parameter associated with the second player. The non-transitory computer-readable medium of any preceding item, wherein the second metric comprises a user-specific item desirability score. (Item 36) The non-transitory computer-readable medium of any preceding item, wherein the second metric comprises a user-specific item desirability score. (Item 37) The instructions cause the control circuitry to determine that the user-specific item desired score exceeds a threshold and to provide an output to the first player when the user-specific item desired score associated with the second player exceeds a threshold. (Item 38) The non-transitory computer-readable medium of any preceding item, wherein the output indicates the second player to the first player. (Item 39) The non-transitory computer-readable medium of any of the preceding items, wherein the output comprises a user interface element that facilitates the exchange of in-game items between the first player and the second player. (Item 40) The non-transitory computer-readable medium of any of the preceding items, wherein the first metric and / or the second metric comprise one or more parameters related to a game configuration. (Item 41) The instruction: retrieving data associated with one or more players different from the first player; generating engagement likelihood parameters for the one or more players based on the data associated with the one or more players; causing the control circuit to perform the first metric comprises a likelihood of engagement of at least one of the one or more players. 2. A non-transitory computer readable medium according to any of the preceding items. (Item 42) The non-transitory computer-readable medium of any of the preceding items, wherein the instructions cause the control circuitry to rank the one or more players based on the generated likelihood of engagement associated with each of the one or more players. (Item 43) The instruction: generating a third metric based at least on data associated with the first player; identifying a second in-game item based on the third metric; and providing media content to the first player that includes information associated with the second in-game item; The non-transitory computer-readable medium of any of the preceding items, which causes the control circuit to perform the following: (Item 44) The non-transitory computer-readable medium of any of the preceding items, wherein the third metric is generated based on data including total play time spent by the first player across one or all games, number of games previously played by the first player, percentage of time spent in single player versus multiplayer games, number and / or type of game titles owned, and number of peer-to-peer transactions conducted across one or all games. (Item 45) 1. A method, comprising: Receiving instructions to generate an in-game item for a first player; identifying a second player based on the first metric; generating a second metric based at least on data associated with the second player; generating the in-game item based on the second metric; and providing the first player with the in-game item; A method comprising: (Item 46) 2. The method of claim 1, wherein the first metric comprises a likelihood of engagement parameter associated with the second player. (Item 47) The method of any preceding claim, wherein the second metric comprises a user-specific item desirability score. (Item 48) The method of any of the preceding items, further comprising determining that the user-specific item desired score exceeds a threshold and providing an output to the first player when the user-specific item desired score associated with the second player exceeds a threshold. (Item 49) 2. The method of claim 1, wherein the output indicates to the first player the second player. (Item 50) 2. The method of claim 1, wherein the output comprises a user interface element that facilitates the exchange of an in-game item between the first player and the second player. (Item 51) 2. The method of claim 1, wherein the first metric and / or the second metric comprises one or more parameters related to a game configuration. (Item 52) Identifying the second player based on the first metric includes: retrieving data associated with one or more players different from the first player; generating engagement likelihood parameters for said one or more players based on said data associated with said one or more players; and the first metric comprises a likelihood of engagement of at least one of the one or more players. A method according to any of the above items. (Item 53) 20. The method of claim 19, further comprising: ranking the one or more players based on the generated likelihood of engagement associated with each of the one or more players. (Item 54) generating a third metric based on data associated with at least the first player; identifying a second in-game item based on the third metric; and providing media content to the first player that includes information associated with the second in-game item; The method according to any of the above items, further comprising: (Item 55) The method of any of the preceding items, wherein the third metric is generated based on data including total play time spent by the first player across one or all games, the number of games previously played by the first player, the percentage of time spent in single player versus multiplayer games, the number and / or type of game titles owned, and the number of peer-to-peer transactions conducted across one or all games. (Summary) A system and method for providing an in-game item to a player is described. Instructions are received to generate an in-game item for a first player. A second player is identified based on a first metric. A second metric is generated based on data associated with at least the second player. An in-game item is generated based on the second metric, and the in-game item is provided to the first player. [Brief description of the drawings]

[0017] [Figure 1]FIG. 1 illustrates a block diagram of a system according to one or more embodiments.

[0018] [Diagram 2] FIG. 2 illustrates a diagram for providing an item to a first player according to one or more embodiments.

[0019] [Diagram 3] FIG. 3 illustrates a method according to one or more embodiments.

[0020] [Figure 4] FIG. 4 illustrates a method for retrieving data associated with one or more players.

[0021] [Diagram 5] FIG. 5 illustrates a method for identifying a second player based on a first metric.

[0022] [Figure 6] FIG. 6 illustrates a method for determining an optimal allocation of personalized items using available metrics to generate in-game items.

[0023] [Figure 7] FIG. 7 illustrates a method for generating an in-game notification for a randomized or personalized item.

[0024] [Figure 8] FIG. 8 illustrates a method according to one or more embodiments.

[0025] [Figure 9] FIG. 9 illustrates a method according to one or more embodiments.

[0026] [Figure 10] FIG. 10 illustrates a table relevant to one or more embodiments.

[0027] [Figure 11] FIG. 11 illustrates media content in accordance with one or more embodiments. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0028] (Detailed Description) A system that randomly identifies items for loot drops may result in a disappointing player experience. To illustrate, in one approach, a loot box may be acquired by a player. The player may acquire the loot box by way of purchase, as a reward for completing a particular mission or task, or for discovering a loot box during a game. Upon opening the loot box by the player, the game randomly identifies and generates an item according to the game's drop rate. The player is then provided with the generated item. However, because the generated item is a random item, the item may be useless to the player. This negatively impacts the user experience and user engagement.

[0029] FIG. 1 illustrates a block diagram of a system 100 according to one or more embodiments. The system 100 includes a client device 101 and a server 103. The client device 101 may be connected to the server 103 via the Internet 105. However, it should be understood that this is an exemplary embodiment, and in other embodiments, the client device 101 and the server 103 may be connected to each other locally, such as by means of a cable or wireless connection. The client device 101 may include a control circuit 107, a communication circuit 109, and an input / output circuit 111. The control circuit 107 may include a processing circuit 113 and a memory 115. The communication circuit 109 may be used to communicate with the server 103. The input / output circuit 111 may be used to provide output content, such as a user interface, to a user and receive input data from a user. The server 103 may include a communication circuit 113, a control circuit 115. The communication circuit 113 may be used to communicate with the client device 101. The control circuitry 115 may include a processing circuitry 117 and a memory 119 .

[0030] FIG. 2 illustrates a diagram depicting a system 200 for providing items to a first player, according to one or more embodiments. In the depicted example, a first player 25 of a video game acquires a loot box 21. It should be understood that the loot box 21 is exemplary, and in other embodiments, the first player 25 may acquire (or interact with) any other form of in-game object designed to provide the player 25 with fully randomized or quasi-randomized items, such as a treasure chest, a virtual vending machine, a virtual content pack, etc. The term "first player" may refer to any user of a video game who acquires and / or opens a loot box or similar in-game object. The first player 25 may acquire the loot box 21 through a purchase made using real currency or using in-game virtual currency, or may acquire the loot box 21 as a reward for completing a particular mission or task, or by random or designed discovery of a loot box during the game.

[0031] Upon opening the loot box 21 by the first player 25, one or more players (such as players 23a, 23b, and 23c) associated with the player 25 are identified. Players 23a, 23b, and 23c may be associated with the first player 25 because they accepted a friend request from the first player 25 (or vice versa). However, in other embodiments, the association between players 23a, 23b, and 23c and player 25 may be due to being teammates, co-players, opponents, etc. In other embodiments, players 23a, 23b, and 23c may be players who most actively play the same game as the first player 25.

[0032] The first player 25 receives a combination of random items and items personalized for the identified players 23a, 23b, and 23c. For example, in-game item 27a may be a specific backpack personalized for player 23a because player 23a has collected all items for the player outfit except for this matching backpack. As another example, in-game item 27b may be a rocket launcher personalized for player 23b because player 23b does not own a rocket launcher and has already completed several peer-to-peer transactions. As another example, in-game item 27c may be a pistol personalized for player 23c because player 23c tends to use pistols and has not acquired this pistol.

[0033] It should be understood that the number of identified players in this embodiment is intended to be exemplary and not limiting. In other embodiments, only one player (e.g., only player 23a) or more than one player may be identified. It should also be understood that a first user may receive only one item personalized for another player (second player), or any other number of combinations of personalized items and random items.

[0034] Optionally, the first player may receive at least one output 29 (such as a notification) for the personalized and non-personalized items based on one or more conditions. The condition may be that one of the provided items has a User Specific Item Desirability Score (USIDS) that exceeds a threshold. The USIDS may be a metric based on available player data that predicts how useful an in-game item will be to a player. Additionally, the output 29 may include a user interface element for transferring, gifting, or exchanging at least one of the provided items with a second player.

[0035] 3 illustrates a method according to one or more embodiments. Method 300 may be implemented, in whole or in part, by system 100 shown in FIG. 1. One or more operations of method 300 may be incorporated into or combined with one or more operations of any other process or embodiment described herein. Method 300 may be stored in a memory or storage (such as any one or more of those shown in FIG. 1) as one or more instructions or routines that may be executed by a corresponding device or system to implement method 300.

[0036] In step 301, the game engine, which may be a software framework stored and processed by the control circuitry 107 and / or control circuitry 115 of FIG. 2, receives instructions to generate at least one in-game item for a first player. For example, X in-game items may need to be generated, where X can be any number, such as 1 or greater. In step 303, the game engine may determine whether there is relevant game-specific or platform-specific information available. The data may be data related to or associated with the second player (e.g., play time, time since last played, number of peer-to-peer transactions). If such data is not available, the game engine may proceed to step 305 and generate at least one pseudo-random, non-personalized item (i.e., X in-game items) to provide to the first player. However, if the game engine determines that such data is available, the game engine proceeds to step 309. In step 309, the game engine may determine how many items are to be personalized (e.g., P items, where P≦X).

[0037] It should be understood that if only one item is to be generated, the game engine may skip step 309.

[0038] In step 307, the game engine may reference and use information provided in the game settings (ie, game configuration) to determine how many items should be personalized in step 309.

[0039] In step 310, the game engine may determine whether any in-game items require personalization. In other words, the game engine determines whether P>0. If it is determined that none of the items require personalization (i.e., P=0), the game engine may return to step 305. If it is determined that none of the in-game items require personalization (i.e., P>0), the game engine proceeds to step 313.

[0040] In step 313, the game engine may obtain relevant data for the second player. In step 315, the game engine may reference a player database to obtain relevant data for the second player. Steps 313 and 315 will be described in more detail in FIG.

[0041] In step 317, the game engine may identify for which player the at least one in-game item should be personalized based on the first metric. The game engine may reference a game setting and / or a player database to identify the player. Step 317 will be described in more detail in FIG. 5.

[0042] In step 319, the game engine may generate at least one in-game item based on the second metric. The second metric may comprise the data retrieved in step 313. The game engine may optionally reference a game setting to generate the at least one in-game item. Step 319 will be described in more detail in FIG. 7.

[0043] FIG. 4 illustrates a method 400 of retrieving data associated with one or more players different from a first player. The method 400 may be implemented, in whole or in part, by the system 100 shown in FIG. 1. One or more operations of the method 400 may be incorporated into or combined with one or more operations of any other process or embodiment described herein. The method 400 may be stored in a memory or storage (such as any one or more of those shown in FIG. 1) as one or more instructions or routines that may be executed by a corresponding device or system to implement the method 400. A game engine may perform the method 400 described in FIG. 4 at steps 313 and 315 of the embodiment described in FIG. 3.

[0044] In step 401, the game engine receives instructions to retrieve data associated with one or more players different from the first player. The data may be game-specific friend data of the first player. In step 403, the game engine determines whether game-specific player data is available. If game-specific player data is available, the game engine proceeds to step 405. In step 405, the game engine retrieves all available game-specific data. The retrieved game-specific data may include at least one of total game play time, total play time spent with the first player, time since last played, character information and play history, percentage of play time spent in single player versus multiplayer, and number of peer-to-peer transactions conducted. Optionally, in step 409, the game engine may reference other game-specific player information databases. The game engine may then proceed to step 407.

[0045] If, in step 403, the game engine determines that game-specific player data is not available, the game engine may proceed directly to step 407.

[0046] In step 407, the game engine may determine whether there is public player data available. The data may be any friend data of the first player.

[0047] If the game engine determines that non-game specific player data is not available, the game engine may proceed to step 411.

[0048] If it is determined that general player data is available, the game engine may then proceed to step 413. In step 413, all relevant available non-game specific player data is obtained. The obtained non-game specific data may include at least one of the total play time across all games spent with the first player, the number of games previously played with the first player, the percentage of time spent with single player versus multiplayer games, the number and / or type of game titles owned, the number of peer-to-peer transactions conducted across all games. Optionally, in step 415, the game engine may reference other game and / or platform specific player information databases.

[0049] FIG. 5 illustrates a method 500 for identifying a second player based on a first metric. The method 500 may be implemented, in whole or in part, by the system 100 shown in FIG. 1. One or more operations of the method 500 may be incorporated into or combined with one or more operations of any other process or embodiment described herein. The method 500 may be stored in a memory or storage (such as any one or more of those shown in FIG. 1) as one or more instructions or routines that may be executed by a corresponding device or system to implement the method 500. A game engine may perform the method 500 described in FIG. 5 in step 317 of the embodiment described in FIG. 3.

[0050] In step 501, the game engine receives instructions to identify at least one player for whom an in-game item is to be personalized.

[0051] In step 503, the game engine determines whether a personalization guideline exists. An example of a personalization guideline may be that when a second player recently stopped playing the game, the personalization guideline may indicate that an item should be personalized for that player to bring them back during the game. In another example of a personalization guideline, if a second player recently started playing a new in-game character (e.g., a wizard in a fantasy game), the personalization guideline may indicate that an item should be personalized for that player's new character (rather than the second player's most played character). Yet in another example of a personalization guideline, when a second player is currently using an in-game item with lower quality relative to the remaining items, the personalization guideline may indicate that a similar item with higher quality should be personalized for that player. In this example, the quality of the item may be determined by any combination of the item's characteristics (e.g., required level, damage per second, attack damage, and attack speed). The personalization guideline may specify how many in-game items should be generated for each player based on priority. If a personalization guideline exists, the game engine proceeds to step 505.

[0052] In step 505, the game engine may obtain personalization guidelines. Optionally, in step 507, the personalization guidelines may be obtained from a game setting (i.e., a game configuration).

[0053] In step 509, the game engine may apply additional personalized ranking metrics, which may include at least one of relative weights applied to each personalized metric, encouraging returning of the first player's less recently active friends, encouraging high priority friends given multiple items, encouraging playing with recently updated / balanced content, or other personalized ranking metrics. The game engine may then proceed to step 511.

[0054] Step 511 determines an optimal distribution of personalized items using available metrics.

[0055] If, in step 503 , the game engine determines that no personalization guidelines exist, the game engine proceeds to step 513 .

[0056] In step 513, the game engine calculates a Likelihood to Engage (LTE) parameter for each player based on the obtained player data. LTE may be a metric based on available player data that predicts how likely the player is to engage in a peer-to-peer transaction with a first player. Peer-to-peer transactions may include in-game exchanges of items, either as gifts or trades.

[0057] In step 515, the game engine may rank the players based on the LTE parameters. Optionally, the number of players ranked based on the LTE parameters may be equal to the number of items to be generated. The game engine may then proceed to step 511.

[0058] In step 511, the game engine determines the optimal distribution of personalized items using available metrics.

[0059] 6 illustrates a method 600 for generating in-game items and determining optimal distribution of personalized items using available metrics. Method 600 may be implemented, in whole or in part, by system 100 shown in FIG. 1. One or more operations of method 600 may be incorporated into or combined with one or more operations of any other process or embodiment described herein. Method 600 may be stored in a memory or storage (such as any one or more of those shown in FIG. 1) as one or more instructions or routines that may be executed by a corresponding device or system to implement method 600.

[0060] In step 601, the game engine receives instructions to generate X in-game items distributed among a ranked list of a first player and Y different players based on priority. X and Y may be 1 or more. In step 603, the game engine may select the player with the highest priority ranking (i.e., the second player). Optionally, in step 607, the selection of the player with the highest priority ranking may be based on optimal player distribution for personalized items using available metrics. As one example, the game engine may generate any number of items for any number of players. The game developer may specify in the game engine, "this loot box generates X items," and the game engine may use LTE parameters and personalization metrics to determine which players the items are personalized for and how many items they each receive. For example, when a first player opens a loot box containing five items, the game may look through the other players associated with the first player and identify not only the two players who have the strongest relationship with the first player who recently stopped playing the game, but also a third player who recently started playing the game. In this example, an expansion pack may have recently been released for the game with new items and characters, and therefore it is desired to attract the two players to the game. In this case, the game engine generates two items for each of the two players who have the strongest relationship with the first player: one new item for their existing character from the new expansion pack, and one new item for the new character type. A final item may be generated for a lower priority third player who is already in the game.

[0061] In step 605, the game engine may identify the number of items (N) to be generated for the second player. The identification of N may be based on an optimal player distribution for personalized items using available metrics.

[0062] In step 609, the game engine may determine whether any items remain to be generated for the second player. In other words, the game engine may determine whether N is greater than 0. If it is determined that no items remain to be generated for the second player, the game engine proceeds to step 613.

[0063] In step 613, the game engine removes the second player from the ranked list and either returns to step 603 or continues to step 615.

[0064] However, if in step 609 it is determined that one or more items remain to be generated for the second player, the game engine may proceed to step 619.

[0065] In step 619, the game engine may generate a second metric. The second metric may comprise a user specific item desire score (USIDS). The game engine may calculate a USI for an in-game item to be generated based on a game setting. A USIDS may be defined as a metric derived based on at least available player data that predicts how useful an in-game item will be to a second player or a first player. The available data may be data obtained in steps 413 and / or 405 of FIG. 4.

[0066] In some embodiments, USIDS may be related to characteristics such as a player's character level, play style, and owned items. For example, if a second player has a large collection of cosmetic items for a particular character, the game engine may increment the USIDS for that player for new cosmetic items for that character.

[0067] Optionally, in step 617, the game engine may optimize the generated items to maximize USIDS across multiple players associated with the first player.

[0068] Optionally, the game engine may reference a game setting to calculate optimal USIDS for one or more items (step 621).

[0069] In step 623, the game engine may generate an in-game item for the second player based on the second metric. The generated item may be associated with an appropriate USIDS that meets the requirements determined during step 619. Optionally, the game engine may reference the game settings to obtain player data (step 625) to generate the in-game item. The game engine may then proceed to step 611.

[0070] In step 611, the game engine may update the number of identified items N, for example, by subtracting 1 from the N value. The game engine may then return to step 609.

[0071] In one embodiment, after the first player receives one or more generated in-game items, the game engine may generate an output (such as a notification) informing the first player that a second player may find at least one of the items provided useful. In some embodiments, the output may include a user interface element that allows the first player and / or the second player to more easily engage in peer-to-peer transactions (e.g., by pressing a unique button to exchange items with the second player). In one embodiment, the game engine may generate an output for the second player informing the second player that the first player has acquired a highly desirable item.

[0072] 7 illustrates a method 700 of generating an in-game notification for a randomized or personalized item. Method 700 may be implemented, in whole or in part, by system 100 shown in FIG. 1. One or more operations of method 700 may be incorporated into or combined with one or more operations of any other process or embodiment described herein. Method 700 may be stored in a memory or storage (such as any one or more of those shown in FIG. 1) as one or more instructions or routines that may be executed by a corresponding device or system to implement method 700.

[0073] A first player receives an in-game item in step 701. The in-game item may be generated according to the embodiments of Figures 3 to 6.

[0074] In step 703, the game engine determines whether associated second player data is available. If it is determined that associated second player data is not available, the game engine proceeds to end the process (step 707). However, if it is determined that associated second player data is available, the game engine may determine whether the first player is enabled for notifications (step 705). Optionally, the game engine may reference game settings to determine whether notifications are enabled (step 704).

[0075] If it is determined that the notification is not valid for the first player, the game engine may proceed to end the process (step 704).

[0076] If the notification is valid for the first player, the game engine proceeds to step 709 .

[0077] In step 709, the game engine may calculate a personalized desired score (PDS) for the in-game item for one or more players associated with the first player. Optionally, the game engine may reference associated player data to determine the PDS (step 711). The associated player data may be data obtained in steps 413 and / or 405 of FIG. 4.

[0078] In step 713, the game engine may determine whether notifications are valid for some players for each in-game item. Optionally, the game engine may reference game settings to determine whether notifications are valid for some players for each in-game item.

[0079] If notification is determined to be valid for some players per item, the game engine determines one or more players having a PDS score above a threshold (step 715). Optionally, the game engine may reference associated player data to determine the PDS score. The game engine may then proceed to step 721.

[0080] However, if it is determined that notification is not valid for some players per item, the game engine may identify one player (i.e., the second player) with the highest PDS and then proceed to step 721.

[0081] In step 721, the game engine may generate a notification to the first player indicating the in-game item and to a second player who may be interested in the in-game item. Optionally, the game engine may present reasons why the second player may be interested (step 719).

[0082] In step 723, the game engine may display the generated notification to the first player.

[0083] In step 725, the game engine may determine whether the notification is valid for the second player. Optionally, the game engine may refer to game settings to determine whether the notification is valid for the second player (step 706). If it determines that the notification is not valid for the second player, the game engine may proceed to end the process (step 727). If it determines that the notification is valid for the second player, the game engine may proceed to step 729.

[0084] In step 729, the game engine may generate a notification for each player potentially receiving the in-game item. The notification may identify at least one of the generated in-game item and the first player. Optionally, the game engine may present reasons why each potential player may be interested in receiving the in-game item.

[0085] At step 735, the game engine may present a notification to each potential player receiving the in-game item and proceed to end the process (step 737).

[0086] The acts or descriptions of FIGS. 3 through 7 may be performed in any suitable alternate order or in parallel to further the objectives of the present disclosure.

[0087] In one embodiment, the game engine may look at the second player's in-game inventory to identify in-game items with similar USIDS to the first player and generate a notification to inform the first player of a potential trade. The notification may be, "Friend X may be interested in the item you just found. Friend X has item Y and you may be interested in it. To trade with Friend X, press Y to open a menu."

[0088] In one embodiment, the game engine obtains data associated with a first player and / or a second player indicating a list of unique in-game items or item classes desired by each respective player. In one embodiment, the data may include a wish list for each player. The game engine may utilize this data to generate an in-game notification for a trade between the first player and the second player. For example, when the game engine determines that the data associated with the first player indicates in-game items owned by the second player and the data associated with the second player indicates in-game items owned by the first player, the game engine may generate an output informing the first player and the second player of a possible trade or exchange.

[0089] In one embodiment, the game engine may additionally use data associated with a different in-game character, rather than data associated with the user account, to further tailor the generated item to the second player. For example, the game engine may use character-specific characteristics (e.g., selected character skills, time played with the character compared to other characters, time since the most recent character play session) to further tailor the generated item to the second player.

[0090] In one embodiment, the game engine may utilize data indicative of a unique game configuration provided by a game designer or developer to influence the item generation process. For example, the data may indicate placing more weight on a unique in-game item or item class to balance the game's difficulty or promote a certain play style. For example, in a game with multiple character classes, a game designer may want to encourage more players to use an unpopular character class by increasing the drop rate for character-specific items.

[0091] In one embodiment, USIDS may be calculated for randomized (i.e., non-personalized) items and used to generate notifications. Notifications to other players may be stopped for the first player to acquire an item for items with high USIDs.

[0092] In one embodiment, the game engine may attempt to maximize USIDS for an item across multiple friends, for example, a generated in-game item may have associated USIDS that exceed a threshold for some players that are different from the first player but associated with the first player.

[0093] In one embodiment, the game engine may calculate USIDS for one or more players associated with a second player but not associated with the first player, where the second player is associated with the first player. In one embodiment, when the first player receives an in-game item that has USIDS below a threshold for one or more players associated with the first player, such as the first player and the second player, but has USIDS above a threshold for one or more players associated with the second player but not associated with the first player, the game engine may generate an output to notify the first player of a potential trade or exchange. The output may be a notification indicating "Friend Y is a friend with Friend Z who may be interested in the item you just found." The second player may receive a similar notification saying "Your friend X just found an item that your friend Z may be interested in."

[0094] In one embodiment, the game engine may analyze in-game communications to identify items of interest and update the USIDS model. For example, players who engage in text or voice chat discussions about a particular in-game item may have a higher USIDS for that item.

[0095] In one embodiment, the game engine may identify a set of in-game items (e.g., outfits, weapon packs) and may modify the USIDS for players who already own one or more of the in-game items in the set. As one example, player X who owns five of six items in an outfit class will have a higher USIDS for item six in that outfit class than player Y who owns two of the six items, which will in turn have a higher USIDS than player Z who owns none.

[0096] 8 illustrates a method 800 according to one or more embodiments. Method 800 may be implemented, in whole or in part, by system 100 shown in FIG. 1. One or more operations of method 800 may be incorporated into or combined with one or more operations of any other process or embodiment described herein. Method 800 may be stored in a memory or storage (such as any one or more of those shown in FIG. 1) as one or more instructions or routines that may be executed by a corresponding device or system to implement method 800.

[0097] At step 801, instructions are obtained to generate an in-game item for a first player. At step 803, a second player is identified based on a first metric. At step 805, a second metric is generated based at least on data associated with the second player. At step 807, an in-game item is generated based on the second metric. At step 809, the in-game item is provided to the first player.

[0098] In another embodiment according to the present disclosure, the third metric is used to provide personalized media content to the first player. In this embodiment, a media content template and a pool of potential in-game items may be available. When a system such as the system of FIG. 1 receives an instruction to generate personalized media content for the first player, the system may receive data related to the third metric including the first player's associated play history from the first game account and / or any other game accounts linked to their profile. After receiving all the associated play history, the system may assign a user specific item desired score (USIDS) to each potential in-game item reward. The in-game items with the highest USIDS may be selected to be added to the media content template and therefore appear in the media content. For example, when there is available data regarding the appearance of the first player's avatar in the first game, those avatars may appear in the media content.

[0099] 9 illustrates a method 900 associated with another embodiment according to the present disclosure. The method 900 may be implemented, in whole or in part, by the system 100 shown in FIG. 1. One or more operations of the method 900 may be incorporated into or combined with one or more operations of any other process or embodiment described herein. The method 900 may be stored in a memory or storage (such as any one or more of those shown in FIG. 1) as one or more instructions or routines that may be executed by a corresponding device or system to implement the method 900.

[0100] The embodiment of FIG. 9 relates to an embodiment in which a third metric is used to provide personalized media content to the first player. The third metric may include at least one of total game play time, time since last played, character information and play history, percentage of play time spent in single player vs. multiplayer, number of peer-to-peer transactions made. The third metric may be specific to one game or may relate to all games played by the first player. The personalized media content may be, but is not limited to, advertising content or a personalized ending of the game.

[0101] In step 901, it is desired by the media content providing service implemented in whole or in part by the system 100 shown in FIG. 1 to generate personalized media content such as advertising content including information of a first game for a first player. It should be understood that the advertising content is exemplary and non-limiting, and the media content can be any other form of media content. In step 903, it is determined whether a user account profile 909 associated with the first player is linked to a gaming service. If it is determined that the user account profile 909 associated with the first player is not linked to a gaming service, in step 905, general advertising content is provided. If it is determined that the account 909 associated with the first player is linked to a gaming service, the method 900 proceeds to step 907. In step 907, relevant information such as the play history of the first player is retrieved from the user account profile 909. The user account profile 909 can be linked to one or more gaming accounts of the first user, such as Steam and Xbox live.

[0102] In step 913, it is determined whether the first player has played the first game. If the first player decides not to play the first game, in step 915, a version of the advertising content targeted to new players is provided. This version of the advertising content may be suitable for the new player because it provides one or more in-game items that tend to be more useful to beginners, such as experience boosts, low-level items at the start. If it is determined that the first player has played the first game, in step 917, data including information such as associated game benefits from the first game (e.g., in-game item preferences, player avatar, etc.) is obtained. The data may be obtained from or based on the user account profile 909.

[0103] At step 919, it is determined whether the first player has played other games similar to the first game. If it is determined that the first player has not played any other games similar to the first game, the method proceeds to step 925. If it is determined that the first player has played other games similar to the first game, the method proceeds to step 921. At step 921, data is obtained from any other games similar to the first game, including information such as relevant play history (e.g., in-game item preferences, player avatar, etc.). The data may be obtained from or based on the user account profile 909. The method then proceeds to step 925. All obtained data associated with the first player may be referred to as a third metric.

[0104] At step 925, a USIDS for each potential in-game item is calculated based on the third metric. The potential in-game items may be from a pool of potential in-game items provided by or available in combination with the advertising media 923. At step 927, one or more items with the highest USIDS are identified. At step 929, personalized advertising content is generated that includes the identified one or more in-game items and / or the first player's avatar.

[0105] In one embodiment, the in-game items are generated based on the first player's data, rather than being chosen from a selection of pre-generated items.

[0106] In one embodiment, if the first player has never played the advertised game but has played previous games in the franchise, the advertising content may display the first player's avatar from the previously played game and use the play history from the previous game.

[0107] In one embodiment, when a first player has played previous games in a franchise of "choices matter" games, those choices in the previous games influence the advertising content generated for the first game. A "choices matter" game can be a narrative-driven game that forces the player to make decisions that can dramatically affect not only the plot of the rest of the game, but also future games in the series.

[0108] FIG. 10 illustrates a table 1000 related to the embodiment of FIG. 9 in which a third metric is used to provide personalized media content to a first player.

[0109] When it is desired to provide a first player with media content related to a first game, e.g., advertising content including information about the first game, in a first example, when the first player has already played the first game (shown in box 1001) and the first player has also played other games (shown in box 1003) similar to the first game, personalized advertising content (shown in box 1005) may be provided based on the first player's play history of the first game and the play history of the similar other games. In this manner, the advertised content may be most effective in attracting the first user's attention to the advertising content. In a second example, when the first player has already played the advertised game (shown in box 1001), but the first player has not played any other games similar to the first game (shown in box 1004), personalized advertising content may be provided based on the first player's play history of the first game (shown in box 1007). In this manner, the advertised content may be effective in attracting the first user's attention to the advertisement content, but may be less effective than the advertised content of the first example. In a third example, when the first player has never played the advertised game (shown in box 1009), but the first player has played other games similar to the first game (shown in box 1003), personalized advertisement content may be provided based on the first player's play history of other similar games (shown in box 1011). In this manner, the advertised content may be partially effective in attracting the first user's attention to the advertisement content, but may be less effective than the advertised content of the first and second examples. In a fourth example, when the first player has never played the advertised game (shown in box 1009), and the first player has never played any other games similar to the first game (shown in box 1004), a general advertisement (shown in box 1013) may be provided to the first user.In this manner, the advertised content may be at least effective in attracting the first user's attention to the advertising content, which may be less effective than the advertised content of the first, second and third examples.

[0110] Figure 11 illustrates media content 1100 provided to a first player in accordance with the present disclosure. Media content 1100 may be the media content of the embodiments of Figures 9 and 10. It should be understood that the media content illustrated in Figure 1100 is exemplary and non-limiting, and in other embodiments, the media content may have any other format, such as audio format, text format, or other format.

[0111] In this exemplary embodiment, the media content 1100 includes information of a first brand 1101, a second brand 1103, and a video game 1105, but in image format. The information of the first brand 1101, the second brand 1103, and the video game 1105 may be names and / or logos associated with each respective brand or video game. The media content 1100 may be personalized for the first player based on a personalized metric, such as the third metric of the embodiment of FIGS. 9 and 10. The personalized media content 1100 may include an image of a first player's character 1107 associated with the video game 1105, the image of the first player's character 1107 having been identified and included in the media content 1100 based on the first player's play history of the video game 1105 (i.e., the information included in the third metric). The player's character 1107 may have an in-game item 1109, such as a weapon, which may be a preferred type of in-game item for the first player. The in-game item 1109 may be a promotional in-game item. The in-game item 1109 may be identified based on the play history of the first player of the video game 1105 (i.e., the information included in the third metric). In this manner, the personalized media content 1100 may be most effective in attracting the attention of the first user because it includes the in-game item 1109 that is preferred by the first player.

[0112] It should be understood that the embodiments described above (such as those of Figures 1 through 11) are described in the context of a game engine or media content providing services performing the methods and steps described herein as an example for ease of understanding, which is intended to be illustrative and not limiting. In other embodiments, any other network-based systems, hardware modules or software modules, including but not limited to computer systems, servers, processors, electronic devices, processing nodes, etc., can be used to perform the methods and steps of the techniques of this disclosure.

[0113] The process described above is intended to be illustrative and not limiting. Those skilled in the art will understand that the steps of the process described herein may be omitted, modified, combined, and / or rearranged, and any additional steps may be performed without departing from the scope of the present disclosure. More generally, the above disclosure is meant to be illustrative and not limiting. Only the following claims are meant to set boundaries as to what the invention includes. Furthermore, it should be noted that the features and limitations described in any one example may be applied to any other example herein, and the flowchart or examples related to one example may be combined with any other example in a suitable manner, performed in different orders, and performed in parallel. In addition, the systems and methods described herein may be performed in real time. The systems and / or methods described above may be applied to or used in accordance with other systems and / or methods.

Claims

1. 1. A method, comprising: Receiving instructions to generate an in-game item for a first player; identifying a second player based on the first metric; generating a second metric based on data associated with at least the second player; generating the in-game item based on the second metric; and providing the first player with the in-game item; A method comprising:

2. The method of claim 1 , wherein the first metric comprises a likelihood of engagement parameter associated with the second player.

3. The method of claim 1 , wherein the second metric comprises a user-specific item desirability score.

4. 4. The method of claim 3, further comprising: determining that the user-specific item desired score exceeds a threshold; and providing an output to the first player when the user-specific item desired score associated with the second player exceeds a threshold.

5. The method of claim 4 , wherein the output indicates the second player to the first player.

6. The method of claim 4 , wherein the output comprises a user interface element that facilitates an exchange of an in-game item between the first player and the second player.

7. The method of claim 1 , wherein the first metric and / or the second metric comprise one or more parameters related to a game configuration.

8. Identifying the second player based on the first metric includes: retrieving data associated with one or more players different from the first player; generating engagement likelihood parameters for said one or more players based on said data associated with said one or more players; and The method of claim 1 , wherein the first metric comprises a likelihood of engagement of at least one of the one or more players.

9. The method of claim 8 , further comprising: ranking the one or more players based on the generated likelihood of engagement associated with each of the one or more players.

10. generating a third metric based on data associated with at least the first player; identifying a second in-game item based on the third metric; and providing media content to the first player that includes information associated with the second in-game item; The method of claim 1 further comprising:

11. 11. The method of claim 10, wherein the third metric is generated based on data including total play time spent by the first player across one or all games, number of games previously played by the first player, percentage of time spent in single player versus multiplayer games, number and / or type of game titles owned, number of peer-to-peer transactions conducted across one or all games.

12. A system including a control circuit, the control circuit comprising: Receiving instructions to generate an in-game item for a first player; identifying a second player based on the first metric; generating a second metric based on data associated with at least the second player; generating the in-game item based on the second metric; and providing the in-game item to the first player; A system configured to:

13. The system of claim 12 , wherein the first metric comprises a likelihood of engagement parameter associated with the second player.

14. The system of claim 12 , wherein the second metric comprises a user-specific item desirability score.

15. 15. The system of claim 14, wherein the control circuitry is configured to determine that the user-specific item desired score exceeds a threshold and to provide an output to the first player when the user-specific item desired score associated with the second player exceeds the threshold.

16. The system of claim 15 , wherein the output indicates the second player to the first player.

17. The system of claim 15 , wherein the output comprises a user interface element that facilitates an exchange of an in-game item between the first player and the second player.

18. The system of claim 12 , wherein the first metric and / or the second metric comprise one or more parameters related to a game configuration.

19. The control circuit includes: retrieving data associated with one or more players different from the first player; generating a likelihood of engagement parameter for each of the one or more players based on the data associated with the one or more players; [0023] the first metric comprises the likelihood of engagement of at least one of the one or more players. The system of claim 12.

20. 20. The system of claim 19, wherein the control circuitry is configured to rank the one or more players based on the generated likelihood of engagement associated with each of the one or more players.

21. generating a third metric based at least on data associated with the first player; identifying a second in-game item based on the third metric; and providing media content to the first player that includes information associated with the second in-game item; The system of claim 12 configured to:

22. 22. The system of claim 21, wherein the third metric is generated based on data including total play time spent by the first player across one or all games, number of games previously played by the first player, percentage of time spent in single player versus multiplayer games, number and / or type of game titles owned, number of peer-to-peer transactions conducted across one or all games. *"Generated": Because it is an invention of a system (thing).

23. means for receiving instructions to generate an in-game item for a first player; means for identifying a second player based on the first metric; means for generating a second metric based at least on data associated with the second player; means for generating the in-game item based on the second metric; means for providing the in-game item to the first player; The system comprises:

24. 24. The system of claim 23, wherein the first metric comprises a likelihood of engagement parameter associated with the second player.

25. 24. The system of claim 23, wherein the second metric comprises a user-specific item desirability score.

26. 28. The system of claim 27, further comprising: means for determining that the user-specific item desired score exceeds a threshold; and means for providing an output to the first player when the user-specific item desired score associated with the second player exceeds a threshold.

27. 27. The system of claim 26, wherein the output indicates the second player to the first player.

28. 27. The system of claim 26, wherein the output comprises a user interface element that facilitates the exchange of an in-game item between the first player and the second player.

29. 24. The method of claim 23, wherein the first metric and / or the second metric comprise one or more parameters related to a game configuration.

30. means for retrieving data associated with one or more players different from the first player; means for generating engagement likelihood parameters for said one or more players based on said data associated with said one or more players; Further equipped with the first metric comprises a likelihood of engagement of at least one of the one or more players.

24. The system of claim 23.

31. 31. The system of claim 30, further comprising means for ranking the one or more players based on the generated likelihood of engagement associated with each of the one or more players.

32. means for generating a third metric based on data associated with at least the first player; means for identifying a second in-game item based on the third metric; a means for providing media content including information related to the second in-game item to the first player; 24. The system of claim 23, further comprising:

33. 33. The system of claim 32, wherein the third metric is generated based on data including total play time spent by the first player across one or all games, number of games previously played by the first player, percentage of time spent in single player versus multiplayer games, number and / or type of game titles owned, number of peer-to-peer transactions conducted across one or all games.

34. A non-transitory computer readable medium having non-transitory computer readable instructions that, when executed by control circuitry, perform: Receiving instructions to generate an in-game item for a first player; identifying a second player based on the first metric; generating a second metric based at least on data associated with the second player; generating the in-game item based on the second metric; and providing the in-game item to the first player; A non-transitory computer readable medium that causes the control circuit to perform the steps of:

35. 35. The non-transitory computer readable medium according to claim 34, wherein the first metric comprises a likelihood of engagement parameter associated with the second player. The non-transitory computer readable medium according to claim 34 , wherein the second metric comprises a user-specific item desirability score.

36. The non-transitory computer readable medium according to claim 34 , wherein the second metric comprises a user-specific item desirability score.

37. 37. The non-transitory computer readable medium according to claim 36, wherein the instructions cause the control circuitry to determine that the user specific item desired score exceeds a threshold and to provide an output to the first player when the user specific item desired score associated with the second player exceeds a threshold.

38. 40. The non-transitory computer readable medium according to claim 37, wherein the output indicates the second player to the first player.

39. 40. The non-transitory computer readable medium according to claim 37, wherein the output comprises a user interface element that facilitates the exchange of an in-game item between the first player and the second player.

40. The non-transitory computer readable medium according to claim 34 , wherein the first metric and / or the second metric comprise one or more parameters related to a game configuration.

41. The instruction: retrieving data associated with one or more players different from the first player; generating engagement likelihood parameters for the one or more players based on the data associated with the one or more players; causing the control circuit to perform the first metric comprises a likelihood of engagement of at least one of the one or more players.

35. A non-transitory computer readable medium according to claim 34.

42. 42. The non-transitory computer readable medium according to claim 41 , wherein the instructions cause the control circuitry to rank the one or more players based on the generated likelihood of engagement associated with each of the one or more players.

43. The instruction: generating a third metric based at least on data associated with the first player; identifying a second in-game item based on the third metric; and providing media content to the first player that includes information associated with the second in-game item; 35. The non-transitory computer readable medium according to claim 34, causing the control circuitry to:

44. 44. The non-transitory computer readable medium according to claim 43, wherein the third metric is generated based on data including a total play time spent by the first player across one or all games, a number of games previously played by the first player, a percentage of time spent in single player versus multiplayer games, a number and / or type of game titles owned, and a number of peer-to-peer transactions conducted across one or all games.

45. 1. A method, comprising: Receiving instructions to generate an in-game item for a first player; identifying a second player based on the first metric; generating a second metric based at least on data associated with the second player; generating the in-game item based on the second metric; and providing the first player with the in-game item; A method comprising:

46. 46. ​​The method of claim 45, wherein the first metric comprises a likelihood of engagement parameter associated with the second player.

47. 47. The method of claim 45 or 46, wherein the second metric comprises a user-specific item desirability score.

48. 48. The method of claim 47, further comprising determining that the user-specific item desired score exceeds a threshold; and providing an output to the first player when the user-specific item desired score associated with the second player exceeds a threshold.

49. 49. The method of claim 48, wherein the output indicates the second player to the first player.

50. 49. The method of claim 48, wherein the output comprises a user interface element that facilitates the exchange of an in-game item between the first player and the second player.

51. 51. The method of any of claims 45 to 50, wherein the first metric and / or the second metric comprise one or more parameters related to a game configuration.

52. Identifying the second player based on the first metric includes: retrieving data associated with one or more players different from the first player; generating engagement likelihood parameters for said one or more players based on said data associated with said one or more players; and the first metric comprises a likelihood of engagement of at least one of the one or more players.

52. A method according to any one of claims 45 to 51.

53. 53. The method of claim 52, further comprising ranking the one or more players based on the generated likelihood of engagement associated with each of the one or more players.

54. generating a third metric based on data associated with at least the first player; identifying a second in-game item based on the third metric; and providing media content to the first player that includes information associated with the second in-game item; 54. The method of any of claims 45 to 53, further comprising:

55. 55. The method of claim 54, wherein the third metric is generated based on data including total play time spent by the first player across one or all games, number of games previously played by the first player, percentage of time spent in single player versus multiplayer games, number and / or type of game titles owned, number of peer-to-peer transactions conducted across one or all games.

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