Inviting Users to Participate in a Venture Exchange

Abstract

A computer-implemented method for inviting members of a venture exchange to participate in a wager. The method includes receiving a wager placed by a first user; parsing the wager to determine wager characteristics associated with the wager; determining, using a processor, friends of the first user that have an affinity for the wager based on the wager characteristics; causing an interface to be displayed to the first user, where the friends of the first user are organized by a relative affinity for the wager; receiving a selection by the first user of friends to invite to participate in the wager; and transmitting a wager invitation to each friend selected by the first user.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of U.S. patent application Ser. No. 12/543,149, filed on Aug. 18, 2009, which claims benefit of U.S. provisional patent application Ser. No. 61/089,811 filed on Aug. 18, 2008. Each of these applications is hereby incorporated herein by reference.

BACKGROUND

1. Field of the Invention

Embodiments of the invention relate generally to computer-implemented venture exchanges, and more particularly, to systems, computer-readable media, and methods for inviting users to participate in a venture exchange.

2. Description of Related Art

Conventional betting exchanges are computer networked processes that provide virtual trading places at which individuals invest (e.g., bet) on outcomes that they predict are likely to occur. Typically, an operator of a betting exchange—or bookmaker—determines the outcomes (or at least influences the details of bets), and mediates the resolution of the bets among many individuals. Bets available in the betting exchanges are usually open to large numbers of individuals, most of whom do not know the identities of the other individuals.

Conventional betting exchanges generally offer a large number of different bets, as well as many different types of bets. Typically, traditional betting exchanges present bets to the betting community at-large. Usually, the presentation of numerous bets can obfuscate other bets, thereby further increasing the quantities of bets that an individual needs to search. This can lead to inefficiencies as some bets that cannot be easily found may remain “unmatched.” An unmatched bet is a bet that has yet to found and matched by another individual. Unmatched bets tie up individuals' wagers for an extended amount of time, thereby decreasing enthusiasm for betting, as well as the rate which bets are processed (which, in turn, reduces liquidity). Further, many typical betting exchanges do not provide a vehicle to sufficiently facilitate camaraderie and cohesiveness among individuals who prefer certain bets and/or know each other. This in turn can also dampen participation that might otherwise be present when individuals bet competitively with other known individuals.

It would be desirable to provide improved techniques that minimize one or more of the drawbacks associated with conventional techniques for facilitating the exchange of bets.

SUMMARY

One embodiment of the invention provides a computer-implemented method for inviting members of a venture exchange to participate in a wager. The method includes receiving a wager placed by a first user; parsing the wager to determine wager characteristics associated with the wager; determining, using a processor, friends of the first user that have an affinity for the wager based on the wager characteristics; causing an interface to be displayed to the first user, where the friends of the first user are organized by a relative affinity for the wager; receiving a selection by the first user of friends to invite to participate in the wager; and transmitting a wager invitation to each friend selected by the first user.

Advantageously, embodiments of the invention allow a user to quickly and easily select which users to invite to participate in the wager.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention and its various embodiments are more fully appreciated in connection with the following detailed description taken in conjunction with the accompanying drawings, in which:

FIG. 1 illustrates a venture exchange system including a recommendation generator, according to various embodiments of the invention;

FIG. 2 illustrates a venture affinity predictor, according to various embodiments of the invention;

FIG. 3 illustrates a presentation engine, according to various embodiments of the invention;

FIG. 4 is a diagram illustrating a recommendation engine, according to various embodiments of the invention;

FIG. 5 is a diagram depicting an interface providing a venture recommendation panel, according to at least one embodiment of the invention;

FIG. 6 is a diagram depicting an interface providing search/selection results using a recommendation generator, according to at least one embodiment of the invention;

FIG. 7 is a diagram depicting an interface providing other outcomes using a recommendation generator, according to at least one embodiment of the invention;

FIG. 8A is a diagram depicting an interface providing selections to generate a customized event, according to at least one embodiment of the invention;

FIG. 8B is a diagram depicting an example of a flow to create a bet, according to at least one embodiment of the invention.

FIG. 9 is a diagram depicting an interface providing sub-pool participant information, according to at least one embodiment of the invention

FIGS. 10A and 10B illustrate examples of a panel presentation application for implementing a panel that includes venture recommendations, according to various embodiments of the invention;

FIG. 11 illustrates an exemplary computer system suitable for implementing an interactive panel for an interface to provide venture recommendations, according to at least one embodiment of the invention; and

FIG. 12 illustrates an example of a panel presentation system for recommending ventures, according to various embodiments of the invention,

FIG. 13 illustrates a system 1300 for inviting friends to a bet, according to at least one embodiment of the invention.

FIG. 14 is a flow diagram of method steps for inviting friends to a wager, according to at least one embodiment of the invention.

Like reference numerals refer to corresponding parts throughout the several views of the drawings. Note that most of the reference numerals include one or two left-most digits that generally identify the figure that first introduces that reference number.

DETAILED DESCRIPTION

Various embodiments or examples of the invention may be implemented in numerous ways, including as a system, a process, an apparatus, or a series of program instructions on a computer-readable medium such as a computer-readable storage medium or a computer network where the program instructions are sent over optical, electronic, or wireless communication links. In general, operations of disclosed processes may be performed in an arbitrary order, unless otherwise provided in the claims.

A detailed description of one or more examples is provided below along with accompanying figures. The detailed description is provided in connection with such examples, but is not limited to any particular example. The scope is limited only by the claims, and numerous alternatives, modifications, and equivalents are encompassed. Numerous specific details are set forth in the following description in order to provide a thorough understanding. These details are provided as examples and the described techniques may be practiced according to the claims without some or all of the accompanying details. For clarity, technical material that is known in the technical fields related to the examples has not been described in detail to avoid unnecessarily obscuring the description.

FIG. 1 illustrates a venture exchange system 100 including a recommendation generator 150, according to various embodiments of the invention. In the example shown in FIG. 1, recommendation generator 150 is configured to interact with a pool of participants 102 to gather information associated with pool of participants 102 and to generate recommendations for a user 103 as a function of the gathered information. In particular, recommendation generator 150 can be configured to determine ventures (e.g., bets) for which user 103 has an affinity, and to present those ventures as recommendations to user 103. In at least some embodiments, recommendation generator 150 can generate recommendations based on group attributes 114 (e.g., venture or bet-related information associated with sub-pool of participants 104), as well as global attributes 115 (e.g., venture or bet-related information associated with pool of participants 102) and user-specific attributes 128 (e.g., venture or bet-related information associated with user 103). User 103 can be associated with a sub-pool 104, which is a subset of the pool of participants 102, whereby information about certain ventures is shared via recommendation generator 150 among user 103 and sub-pool participants 105 (e.g., friends of user 103).

As shown, user 103 can use an interface 108 to interact with recommendation generator 150, whereas sub-pool participants 105 can use interfaces 113 to interact with the recommendation generator 150. As used herein, the term “venture” can refer, at least in some embodiments, to an event having multiple unknown outcomes from which a participant (e.g., user 103) selects a particular outcome to occur along with an investment of some unit of value. In some examples, the term “venture” can be used interchangeably with the terms “bet” or “wager.” As used herein, the term “units of value” can refer, at least in some embodiments, to represent an amount of investment or risk expressed in monetary forms or in non-monetary forms, such as tokens or points.

In at least some embodiments, recommendation generator 150 can include either a venture affinity predictor 152 or a presentation engine 154, or both. Venture affinity predictor 152 can be configured to determine ventures for which user 103 has an affinity based on information from any number of sources. Examples of sources of such information include pool of participants 102, sub-pool participants 105, and user 103. Venture affinity predictor 152 can receive data representing global attributes 115 (as information from pool of participants 102) to generate recommendations expressed in terms, for example, of aggregated attributes of the participants. Thus, venture affinity predictor 152 can use global attributes 115 for predicting ventures that, for example, might appeal to a predominant number of participants in pool of participants 102. In some cases, venture affinity predictor 152 uses global attributes 115 to generate venture recommendations when other sources of information are limited (e.g., when user 103 is not logged in or a registered member of venture exchange system 100). Venture affinity predictor 152 can also receive data representing group attributes 114, which can describe the characteristics for the ventures in which one or more of sub-pool participants 105 participate.

Further, in some embodiments, venture affinity predictor 152 can receive data representing user-specific attributes 128, which may describe characteristics of user 103. User-specific attributes 128 can be derived from one or more views 120 (or sessions) of interface 108. For example, user-specific attributes 128 can be provided via view 120a, which can include an electronic form into which user 103 inputs user-specific information, such as name, gender, age, residence, etc. As another example, user-specific attributes 128 can be provided responsive to the interaction of user 103 with one or more views 120a to 120c. For example, user-specific attributes 128 can include information indicating recommended bets that were presented to user 103, but were not selected. Thus, venture affinity predictor 152 can predict that other bets having similar attributes as the unselected recommended ventures likely will not be selected, too. Therefore, those types of ventures can be recommended less or not at all, at least with respect to user 103. In operation, venture affinity predictor 152 can use group attributes 114, global attributes 115, and user-specific attributes 128, or any combination thereof, to generate venture recommendations for which user 103 likely will have an affinity. Recommendation generator 150 can provide the venture recommendations (e.g., as data representing user-specific venture recommendations 126) to a portion (“P2”) 110 of interface 108.

In at least some embodiments, presentation engine 154 can be configured to optimize the presentation of the venture recommendations in a manner that user 103 can readily detect ventures in which user 103 is interested. For example, presentation engine 154 can be configured to order venture recommendations for presentation at portion 110 of interface 108 as a function of group attributes 114, global attributes 115, and/or user-specific attributes 128. In at least one embodiment, recommendation generator 150 can include a venture creation unit 156, which can be configured to create a customized venture responsive to venture creation factors 122 input into a portion (“P3”) 112 of interface 108. Examples of venture creation factors 122 include identifiers (e.g., names) of sub-pool participants 105 and indications whether to limit access to a venture to only sub-pool participants 105, thereby making it private and inaccessible to others in pool of participants 102. Further, recommendation generator 150 can be configured to access group attributes 114, filter those attributes, and stream data representing friend ventures 124 to a portion (“P1”) 109 of interface 108. The streaming attributes can be displayed on portion 109 of interface 108 to report bet-related activities as a betting activity ticker or feed. In some instances, a betting activity ticker or feed can be implemented similar to a news feed-like format. Thus, user 103 can observe ventures in which friends of the user are participating, and can also participate in friend-created ventures, among other betting news-related information or things.

In view of the foregoing, the structures and/functionalities of recommendation generator 150 can provide recommendations that user 103 prefers, and can present the recommendations in a manner that facilitates expeditious searching to locate suitable ventures in which to participate. The recommendations can be a function of group attributes 114, thereby providing user 103 with recommended ventures as a function of the ventures in which friends 105 participate. The friends can presumably be trustworthy sources of information for predicting ventures that might also interest user 103. Additionally, recommendation generator 150 can tune the ventures that are recommended by monitoring which presented recommendations are ignored by user 103. Further, recommendation generator 150 can use global attributes 115 to present venture recommendations as a function of the aggregate behaviors and/or selections of pool of participants 102, rather than relying on, for example, keyword-related recommendations. Thus, recommendation generator 150 can reduce the search cost for user 103 to find ventures (e.g., bets) that they would be interested in. Any number of views 120 (e.g., as served web pages) can be used to continuously collect and process data.

In still further embodiments, the recommendation generator 150 can be used in conjunction with an invitation engine such that after the user 103 places a wager, the user 103 may invite other users (e.g., friends) to participate in the bet. For example, a friend picker may be provided through which the user 103 can select which other users to invite to participate in the bet. In some embodiments, the recommendation generator 150 may organize the friends of the user 103 so that the users that are most likely to want to participate in the bet are placed first, e.g., near the top of the friend picker. Additional details of the invitation engine are described below in FIGS. 13-14.

In various embodiments, any of the described elements in FIG. 1 can be implemented in hardware or software, or any combination thereof, regardless of whether the elements are distributed throughout a network or reside on a server machine (or in a contiguous computer-readable medium). In at least some embodiments, recommendation generator 150 can generate recommendations based on more or fewer attributes that group attributes 114, global attributes 115, and user-specific attributes 128. For example, the venture exchange system 100 may be implemented as a website to which users navigate using a web browser on a personal computer (PC) or laptop. In other embodiments, the web-site based venture exchange system 100 may be navigated using a mobile browser on a mobile phone. In still further embodiments, the venture exchange system 100 may be implemented as a software application that is installed on a user's computer or phone. For example, the software application may be provided on a disc or downloaded as a computer program over the internet and installed on the user's computer. In still further embodiments, the venture exchange system 100 may be implemented as a combination of a website and software application. In yet further embodiments, the venture exchange system 100 may be implemented via a standalone device or kiosk. For example, a kiosk may be provided that is connected to the internet and allows users to participate in the venture exchange via an interface. For example, the interface may be a keyboard and mouse interface, a touch screen interface, or any other technically feasible interface. In some embodiments, the kiosk may be located at a horse race track, auto race track, athletic stadium, off-track betting (OTB) facility, convenient store, an outdoor location, such as a sidewalk, a transit terminal, an airport, or any location. In some embodiments, the kiosk is connected to the internet with a wired LAN/WAN connection, a wireless Internet connection, a mobile phone network, a satellite connection, or any technically feasible type of connection.

FIG. 2 illustrates a venture affinity predictor 220, according to various embodiments of the invention. In diagram 200, venture affinity predictor 220 is shown to include a data collection engine 230, a user model generator 222, and a prediction engine 224, and is further shown to interact with one or more data repositories, such as data repositories 240 to 249. Data collection engine 230 can be configured to gather data from various sources for use by user model generator 222 to generate a user model that can describe the likes and dislikes of a user, among other things. As shown, data collection engine 230 can include a search analyzer 232, a sub-pool venture analyzer 234, a user activity tracker 236, and an attribute manager 238.

Search analyzer 232 can be configured to receive search criteria 204 in connection with a search by a user to find ventures in which the user seeks to participate, in at least some embodiments. Search analyzer 232 can analyze and decompose, for example, a string of text to determine a subset of words that can be used to identify likes and dislikes of the user. The subset of words (and an optional association to the user) can be stored in a repository 242 as user-specific attributes. For example, the subsets of words can include the word “baseball,” thereby associating that word with the user. Venture affinity predictor 220 then can subsequently present venture recommendations associated with the term “baseball.”

Sub-pool venture analyzer 234 can be configured to receive friend-related data 206 (e.g., as group attributes) in connection with ventures in which the user's friends are participating, in at least some embodiments. Sub-pool venture analyzer 234 can analyze the ventures that the user's friends are participating in, and can extract information that can be useful to predict whether a user prefers one or more bets over other bets. Sub-pool venture analyzer 234 can store friend-related data 206 in sub-pool database (“DB”) 240. Examples of friend-related data 206 can include: an amount of friends of the user that have participated in a venture/bet, the amounts wagered as a function of one or more friends, activity levels of any friend (e.g., adding or removing units of value for a bet), a list of bets that any friend is participating in, search results of any friend's search, and the like.

User activity tracker 236 can be configured to receive user activity context data 202 (e.g., as at least a portion of user-specific attributes) in connection with the activities of the user for various ventures, in at least some embodiments. User activity tracker 236 can store user activity context data 202 in user-specific attributes repository 242. In operation, user activity tracker 236 can analyze the context in which the user is reviewing, searching, selecting (and not selecting), and participating in various ventures. For example, user activity tracker 236 can determine which recommended ventures (e.g., generated by the recommendation generator) were ignored by the user, based on user activity context data 202. User model generator 222 can use this information to exclude or deemphasize presentation of similar ventures for recommendation purposes. Examples of other user activity context data 202 include:

• • (1) the page context data that describes the category factor associated with any web page view by the user (so that venture affinity predictor 220 can emphasize or enhance the prediction of other similar bets based on user-favored categories),
  • (2) the amount of times a user viewed a bet,
  • (3) the bet subject matter for determining whether the user is a fan of a particular subject (for example, a team or a player) for predicting that bets about that subject matter are likely to be preferable to the user,
  • (4) the geographic location of the user as determined, for example, by mapping an IP address to a geographical location,
  • (5) recent actions of the user (e.g., adding a bet, increasing/decreasing a bet amount, etc.) to discover the temporal “mood” of the user during a period of time, and present bets that the user currently is more interested in,
  • (6) the number of times the user has participated in bets of the same category,
  • (7) the number of times the user has participated in similar bets,
  • (8) the amount of money the user has wagered on a bet,
  • (9) the frequency that a user wins similar bets,
  • (10) favored outcomes that the user typically selects (e.g., user predominantly bets either “for” or “against” an outcome, etc.), and the like.

Attribute manager 238 can be configured to manage the usage and/or storage of user-specific attributes in repository 242 and global attributes in repository 244, in at least some embodiments. Attribute manager 238 can store explicit attribute data 208 as user-specific data in user-specific attributes repository 242. In one embodiment, explicit attribute data 208 can be extracted from an electronic form into which the user enters user-specific information directly, or from surveys. Attribute manager 238 can also operate to manage the usage and/or storage of global attributes 209 in repository 244. Examples of global attributes 209 include:

• • (1) an amount of money in the pot for a bet,
  • (2) the number of participants who have participated in a bet,
  • (3) recent activity relating to the bet (e.g., how many bets have been placed in the last 24 hours),
  • (4) the expiration time at which the bet will close,
  • (5) how soon the bet will resolve,
  • (6) betting volumes for a bet (e.g., rate at which units of value flow into a pot, amounts of individuals participating), and the like.

User model generator 222 can be configured to generate a data model representing the likes (e.g., affinity for participating in a venture/bet) and dislikes, and to store the data model in repository 246. In at least some embodiments, the user model includes a data arrangement of data (or a subset thereof) stored in repositories 240 to 244, the data arrangement being well-suited for use by prediction engine 224.

Prediction engine 224 can be configured to generate recommended ventures 210 for delivery to a presentation engine (not shown). Prediction engine 224 can be further configured to access data in repository (“venture-specific data”) 248 and repository (“prediction generation rules”) 249. Repository 248 maintains data representing bets (e.g., all bets, public or otherwise) available to one or more participants, including the user and friends of the user. Repository 249 can include prediction generation rules that guide the prediction engine 224 in performing the recommendation process. In at least some embodiments, the prediction generation rules cause prediction engine 224 to identify open bets (i.e., not closed) and generate a list of those bets that are open. The prediction generation rules can also cause prediction engine 224 to filter bets on the list as a function of venture selection context data 202. For example, if venture selection context data 202 indicate that the user has viewed or is viewing a category sub-page (e.g., one level down into a category, such as baseball in the sports category), then venture recommendations can be limited to bets within the category (or sub-category).

Next, prediction engine 224 can be configured to rank the bets as a function of the data in the user model repository 246. The prediction rules can then also cause prediction engine 224 to evaluate the venture selection context data 202 to determine recent activity to, for example, to identify unselected recommendations for subsequent de-emphasis. According to various embodiments, the prediction generation rules can cause prediction engine 224 to perform any type of ranking or weighting to determine the most relevant recommendations to present to a user. For example, if the prediction rules attribute more weight to locality than other attributes, then prediction engine 224 can evaluate the IP (Internet Protocol) address to present geographically relevant ventures/bets to a user (e.g., bets relating to a local minor league ball team in Visalia, Calif.).

FIG. 3 illustrates a presentation engine 310, according to various embodiments of the invention. In diagram 300, presentation engine 310 is shown to include a venture consolidator 312 and a presentation manager 314, and is further shown to interact with one or more data repositories, such as data repositories 330 to 336. Venture consolidator 312 can be configured to consolidate (e.g., or combine) redundant/duplicative bets stored in repository 330, such as multiple “Who will win the World Series” bets. Filtering out such bets decreases the number of bets that a user, for example, searches through. As shown, redundancy eliminator 312 generates a set of filtered recommendations 315 and transmits them to presentation manager 314. Note that in some cases, venture consolidator 312 is optional.

Presentation manager 314 can be configured to generate user-specific venture recommendations 316 for review by a user. Presentation manager 314 can be further configured to access user-specific attributes and global attributes in repositories 332 and 334, respectively. Then, presentation manager 314 can tune the presentation of user-specific venture recommendations 316, according to how the presentation rules in repository 336 causes presentation manager 314 to process the attributes. In various embodiments, the presentation rules that are implemented can vary depending on how an interface or window is to be presented to a user. For example, for a first page (e.g., an introductory or “dashboard” page), the presentation rules can be configured to cause presentation manager 314 to present recommended ventures/bets at the top of an interface. In some cases, presentation manager 314 can also present a betting activity ticker or feed on the first page to display the latest activity in the network of friends for the user. The betting activity ticker or feed can include recommendations embedded within it. For a second page (e.g., a user profile page), the presentation rules can be configured to cause presentation manager 314 to present a subset of the bets that the user is participated/has participated in. Presentation manager 314 can use the attributes to determine which bets constitute the subset of venture recommendations that are to be presented to the user.

In some embodiments, presentation manager 314 can be configured to present user-specific venture recommendations 316 in a “mini view” on interface 398. A “mini view” can be a portion of interface 398 in which a bet is displayed with an identifier (e.g., a name, such as “Who will win the World Series”) and/or photo (e.g., photo of Kobe Bryant for a basketball bet), a favored outcome (e.g., as provided by user-specific attribute data or by a user model), friend-related information, and/or an amount of value units wagered. Presentation manager 314 can be configured to display the bets within a particular category, and can determine which bets to display and in which order. Presentation manager 314 can be configured to order search results responsive to a search query. Presentation manager 314 can be configured to display other bets that the user is likely to participate in. Presentation manager 314 can also be configured to show recommended bets after a user has placed a bet and invited friends to participate in the bet that the user made.

In some embodiments, presentation manager 314 can include a message generator 390 that can be configured to transmit user-specific venture recommendations 316 via any number of communication media, channels, or techniques. For example, message generator 390 can transmit one or more user-specific venture recommendations 316 as a Short Message Service (“SMS”) message 392, an email message 394, or any other type of electronic message 396.

FIG. 4 is a diagram 400 illustrating a recommendation engine 402, according to various embodiments of the invention. In this example, recommendation engine 402 is shown to include servers 430a, 430b, and 430n that can provide structures and/or functionalities for a venture affinity predictor, a presentation engine, and a venture creation unit, respectively, which, in turn, can be configured to access data in repositories 440a, 440b, and 440n. In various embodiments, recommendation engine 402 can be communicatively coupled via a network 410, such as the Internet or any other communications network, to any number of clients 420a, 420b, and 420n. In at least some embodiments, clients 420a to 420n can respectively execute applications 422a to 422n, which can perform part of the functionality of a venture exchange system. Examples of applications 422a to 422n include web browser applications, mobile browser application, installed software application, mobile phone applications, or the like. In some embodiments, the clients 420a to 420n comprise a personal computer, laptop, mobile phone, standalone device or kiosk, or any other technically feasible type of computer device.

FIG. 5 is a diagram 500 depicting an interface providing a venture recommendation panel, according to at least one embodiment of the invention. In this example, a display 503 is configured to provide an interface 501 that is configured to present a venture recommendation panel 590. As used herein, the term “panel,” at least in one embodiment, can refer to displays, palettes, tabs, windows, screens, portions of an interface, and the like. Venture recommendation panel 590 can be configured to include recommended bet portion 512 for at least presenting a recommended venture (e.g., a bet for the winner of the 2008 U.S. Presidential Election). Venture recommendation panel 590 can also be configured to present one or more of the following: (1) an interactive panel portion 540 configured to accept a search query to form a search, (2) a group of categorized links 560, and (3) another bet portion 550 for at least presenting another recommended venture (e.g., 2008 Regular Season Kobe Bryant Assists/Game) or for indicating a pending bet for a user. Venture recommendation panel 590 includes a panel title bar 504, which can indicate the name of the venture exchange site, a menu and/or toolbar 506, which is shown to include at least menu items 513, panel control buttons 519, and scroll bar 542. In at least one embodiment, venture recommendation panel 590 facilitates finding bets and participating in on-line betting.

In this example, recommended bet portion 512 includes information originating from various sources to describe a bet offered to a user in a manner that can influence participation. As shown, recommended bet portion 512 is depicted as a shortened view (or mini view) of a bet. A mini view presents an outcome, such as outcome (“George Washington”) 516 for the bet having a title 510 of “2008 US Presidential Election Winner.” In various embodiments, a recommendation generator can determine an affinity (e.g., a user's affinity) for George Washington, whether in the context of previous bets or any other tangential activity (e.g., searches for George Washington, etc.), and can recommend George Washington as an outcome. Recommended bet portion 512 also includes a field 514 suggesting a unit of value (e.g., 20 units) that can be over-written with any other number of units of value. Also included is an indication of an amount (e.g., expressed as a percentage) of people (either in the pool of participants or in the sub-pool of friends, as well as a specific individual (not shown)) that have picked the outcome presented. As such, friend-related information can be presented coincident to the presentation of an outcome of a bet to provide a user with real-time information based on select individuals' choices. Part 518 of recommended bet portion 512 is shown to include “XXXXX,” which can be representative of the total pot. A user input 520 can be configured to activate participation in a bet. Part 522 of recommended bet portion 512 is shown to include “another outcome” selection, which can be a link to an alternative outcome should the recommend outcome 516 not be attractive to the user. Further, part 524 of recommended bet portion 512 is shown to include “closes in 6 months,” which is the time left until the bet closes and further participation and/or bet alterations are locked out.

Next, consider a case in which the user desires to search for a bet based on ordered categories 560, which can be presented in a manner as determined by a recommendation generator. Here, the user uses cursor 510 to select the “Sports” category (note that the subsequent presentation of results can be obtained by entering “Sports” into field 540).

FIG. 6 is a diagram 600 depicting an interface providing search/selection results using a recommendation generator, according to at least one embodiment of the invention. In this example, an interface 601 is configured to present a search/selection panel 602. As shown, search/selection panel 602 presents bets 620, 622, 624, and 626, any of which the user can select for participation. Note that the ordering of the bets, the information presented in each of the bets 620 to 626, the types of bets (e.g., “How many wins . . . ,” “Who will win the World Series,” etc.), and the like, can be determined based on an affinity (or a predicted affinity) that a user might have to the subject matter presented in search/selection panel 602. A recommendation generator can evaluate user-specific attributes, group attributes, and/or global attributes to determine that bets 620, 622, 624, and 626 are to be presented rather than other bets (not shown). Next, consider that a user selects another outcome using a cursor 670 for bet 622.

FIG. 7 is a diagram 700 depicting an interface providing other outcomes using a recommendation generator, according to at least one embodiment of the invention. In this example, an interface 701 is configured to present outcomes panel 702 for event 706 titled “Who will win the World Series this Season?” Also shown is the amount of time left 704 before the bet closes. As shown, outcomes panel 702 presents outcomes 710, 712, and 714, any of which the user can select for participation. Note that the ordering of the outcomes, the information presented in each of the outcomes 710 to 714, the titles 720 of outcomes (e.g., “Toronto Blue Jays” for outcome 712 etc.), the types of friend-related information presented at portions 722 and 724, and the like, can be determined based on an affinity (or a predicted affinity) that a user might have to the subject matter presented in outcomes panel 702. That is, a recommendation generator can evaluate user-specific attributes, group attributes, and/or global attributes to determine that outcomes 710, 712, and 714 and the information presented therein are to be presented rather than other outcomes and information (not shown). Portion 726 accepts inputs from the user to bet any amount of units of value. Next, consider that a user desires to create a customized event other than shown in the search/selection results panel.

FIG. 8A is a diagram 800 depicting an interface providing selections to generate a customized event, according to at least one embodiment of the invention. In this example, an interface 801 is configured to present a customized event creation panel 802. To create a customized event (or bet), a user can select a template in drop down menu 820 with which to create bet. For example, the user can use drop down menu 820 to clone an existing bet for purposes of modifying it. Or, the user can use drop down menu 820 to select a template requiring the user to create some or all aspects of a bet (e.g., titles, closing dates and times, etc.). A user can select whether to make the customized event public or private using inputs 810. Here, the user selected the radio button “private.” As such, customized event creation panel 802 can present the user with drop down menu 822 to select the individuals (e.g., friends) who are authorized to access and/or participate in the customized event, thereby denying access to those external to the sub-pool.

FIG. 8B is a diagram depicting an example of a flow to create a bet, according to at least one embodiment of the invention. Persons skilled in the art will understand that, even though the method 850 is described in conjunction with the systems of FIGs. 1-8A, any system configured to perform the method steps, in any order, is within the scope of embodiments of the invention.

As shown, the method 850 begins at step 852, where a user describes a bet. At step 854, the user adds outcomes. At step 856, the user may optionally take a position. At step 858, the user may invite one or more friends to participate in the bet. In one example, an interface can be configured to provide for custom bet creation, such as described in pages 20 to 26 of Appendix 1. For instance, an interface, such as depicted on page 20 of Appendix 1, can receive information that describes certain attributes of a venture (or a bet). For example, the interface can include fields for entering: (1) the title of the bet, (2) the close date (e.g., the date on which the bet closes to any new participants), (3) the date that the bet will be resolved, (4) whether the bet can be accessible (or viewable) by everyone (i.e., is it a public bet) or whether the bet has limited access (e.g., limited access to the friends of the user or a group of friends of the user). In other examples, the interface can include fields (not shown) for entering: (1) maximum amount of participants that can participate in a venture/bet, (2) a maximum number of positions a user can participate in per venture (e.g., a creator of a bet can restrict a participant to selecting a maximum of 3 outcomes of a group of outcomes), (3) a minimum amount of units of value to wager (e.g., per outcome or bet), (4) restricting an outcome to only a specific number of users (e.g., an outcome can be limited to only one participant, such that after that one outcome is selected, no others can select that outcome), and the like.

FIG. 9 is a diagram 900 depicting an interface providing sub-pool participant information, according to at least one embodiment of the invention. In this example, an interface 901 is configured to present a sub-pool participant panel 902. As shown, portion 910 of panel 902 is configured to present friend information via a selection in drop down menu 912. Consider that the user selects “Joe” as a friend having information that the user wishes to review. As shown, the friend's name 916 is shown as Joe, along with the bets 918 that Joe is participating in as well as the amounts wagered 920 in the bets. Other information can be shown responsive to selecting Joe's name in drop down menu 912. Portion 930 of panel 902 is configured present friend information in real-time (or near real-time) as part of a stream of information, such as a betting activity ticker or feed (shown as “bet feed”), in which friend-related information units 932 is present to the user. Note that in some embodiments, a recommendation generator can evaluate user-specific attributes, group attributes, and/or global attributes to determine that which information units 932 are to be presented to the user.

FIG. 10A illustrates an example of a panel presentation application for implementing a panel that includes venture recommendations, according to various embodiments of the invention. In at least one embodiment, venture recommendations and/or selections can be implemented in a panel, such as a single panel. Here, application 1002 includes interface (“I/F”) module 1004, display module 1006, rendering engine 1008, repository 1010, logic module 1012, panel generator 1014, and data bus 1016. In some examples, the number and type of elements shown and described may be varied and are not limited to the descriptions provided. In some examples, the above-described elements can be implemented as part, component, or module of application 1002. As an example, application 1002 can be implemented to include either a web-based form or an electronic form as part of a software product, and can have content input field functionality as described herein. Logic module 1012 can be implemented as software, hardware, circuitry, or a combination thereof to implement control logic for the described techniques for panel presentation.

In some examples, logic module 1012 can be configured to control panel generator 1014 to form panels that include venture recommendations. Rendering engine 1008 can be configured to operate as a layout engine for web pages, for example, to manipulate both content (e.g., as expressed in or including HTML, XML, image files, etc.) and formatting information (e.g., as expressed in or including CSS, XSL, etc.) for rendering the data or information as one or more panels on an interface. Interface module 1004 can exchange panel presentation data, including content data, image data, audio data, as well as other data, between application 1002 and another application (e.g., a host, client, web services-based, distributed (i.e., enterprise), application programming interface (“API”), operating system, program, procedure or others) that can use data and information generated from panel generator 1014 to render presented panels on a display screen. In other examples, the above-described techniques and elements can be varied in design, implementation, and function and are not limited to the descriptions provided. In one embodiment, logic module 1012 can include a recommendation generator 1090 that is configured to include structure and/or functionality similar to previously-described recommendation generators.

FIG. 10B illustrates an alternative example of a panel presentation application for implementing a panel that includes venture recommendations, according to one embodiment of the invention. Here, application 1020 includes panel generator 1022 and logic module 1024, which can have equivalent functionality as 1012 of FIG. 10A. Further, application 1020 is shown in data communication with interface (“I/F”) module 1026, display module 1028, rendering engine 1030, and repository 1032. Data bus 1034 can be configured to send or receive data among application 1020, I/F module 1026, display module 1028, rendering engine 1030, and repository 1032. In other examples, more, fewer or different elements can be used and implemented without limitation to the examples provided above.

In some examples, logic module 1024 and panel generator 1022 can be implemented as part of application 1020, which can be implemented separately from other functional components or modules, such as interface module 1026, display module 1028, rendering module 1030, and repository 1032. Data bus 1034 can be implemented to communicate data over a given port between application 1020 and interface module 1026, display module 1028, rendering module 1030, and repository 1032. In other words, application 1020 can be implemented as a standalone application or as a component (i.e., module) of another application. Data or information associated with a panel can be stored in repository 1032, which can be implemented using a database, data store, data warehouse, or any other type of data repository or structure. In other examples, more, fewer, or different modules can be used to implement the described techniques for panel presentation and are not limited to those provided.

FIG. 11 illustrates an exemplary computer system suitable for implementing an interactive panel for an interface to provide venture recommendations, according to at least one embodiment of the invention. In some examples, computer system 1100 can be used to implement computer programs, applications, methods, processes, or other software to perform the above-described techniques and to realize the structures described herein. Computer system 1100 includes a bus 1102 or other communication mechanism for communicating information, which interconnects subsystems and devices, such as processor 1104, system memory (“memory”) 1106, storage device 1108 (e.g., ROM), disk drive 1110 (e.g., magnetic or optical), communication interface 1112 (e.g., modem or Ethernet card), display 1114 (e.g., CRT or LCD), input device 1116 (e.g., keyboard), and pointer cursor control 1118 (e.g., mouse or trackball). In one embodiment, pointer cursor control 1118 invokes one or more specialized commands that, at least in part, facilitate participation in a bet. Pointer cursor control 1118 can interact via a pointer cursor with a panel to select a bet.

According to some examples, computer system 1100 performs specific operations in which processor 1104 executes one or more sequences of one or more instructions stored in system memory 1106. Such instructions can be read into system memory 1106 from another computer-readable medium, such as static storage device 1108 or disk drive 1110. In some examples, hard-wired circuitry can be used in place of or in combination with software instructions for implementation. In the example shown, system memory 1106 includes modules of executable instructions for implementing an operation system (“O/S”) 1132, an application 1136, and a recommendation generator 1138.

In some examples, execution of the sequences of instructions can be performed by a single computer system 1100. According to some examples, two or more computer systems 1100 coupled by communication link 1120 (e.g., LAN, PSTN, or wireless network) can perform the sequence of instructions in coordination with one another. Computer system 1100 can transmit and receive messages, data, and instructions, including program code (i.e., application code) through communication link 1120 and communication interface 1112. Received program code can be executed by processor 1104 as it is received, and/or stored in disk drive 1110, or other non-volatile storage for later execution. In one embodiment, system 1100 is implemented as a hand-held device, such as a mobile phone 1150. But in other embodiments, system 1100 can be implemented as a personal computer, laptop, mobile phone, standalone device or kiosk, or any other technically feasible type of computing device.

FIG. 12 illustrates an example of a panel presentation system for recommending ventures, according to various embodiments of the invention. Here, system 1200 includes network 1202, display environment 1204, interface 1206, which can be presented on devices such as computer 1208, notebook computer (“notebook” or “laptop”) 1210, smart phone 1212, personal digital assistant (“PDA”) 1214, server 1216, administrator computer 1218, and/or standalone device or kiosk (not shown). In other examples, the number and type of devices can be varied and are not limited to those shown and described.

In some examples, one or more panels for creating electronic documents can be presented on interface 1206, which can be an interface for an application such as a web browsing program, Internet content portal, client or desktop application for any purpose. Interface 1206, in some embodiments, can include Uls for stand-alone video players, including a DVD-player UI. Panels can be used to provide additional or supplemental information that can be contextually relevant to another panel presented in interface 1206. Computer 1208, notebook computer (“notebook” or “laptop”) 1210, smart phone 1212, personal digital assistant (“PDA”) 1214, server 1216, and administrator computer 1218 can provide content data for rendering content as well as other data, which can be implemented to generate, for example, an electronic form and content input field in interface 1206. In some cases, an operating system installed on computer 1208 can communicate (i.e., via an application programming interface (“API”)) content data and/or other related data to another application installed on computer 1208 to render (i.e., interpreting data and information to draw or display the content in an interface) one or more panels presented in interface 1206. In some examples, different types of panels can be rendered in interface 1206. In one embodiment, interface 1206 can include any number and/or any type of display environments, such as CRT and LCD displays. Note that the above-described system and elements can be varied and are not limited to the descriptions or examples provided.

FIG. 13 illustrates a system 1300 for inviting friends to a bet, according to at least one embodiment of the invention. As shown, the system 1300 includes a venture exchange 1302, a user 1308, and friends 1310, 1312. The venture exchange 1302 includes a recommendation engine 1304 and an invitation engine 1302. In one embodiment, the recommendation engine 1304 is substantially similar to the recommendation generator 150 described in FIG. 1. In some embodiments, the friends 1310, 1312 are related to the user 1308 in a social network context, i.e., the user 1308 is a “friend” of friend 1310 and friend 1312.

In some embodiments, the user 1308 places a wager with the venture exchange. According to various embodiments, the wager may be placed via a web browser on a personal computer or laptop, a software application installed on a personal computer or laptop, a mobile browser on a mobile phone, a mobile application installed on a mobile phone, a standalone device or kiosk, or via any technically feasible implementation of the venture exchange. The recommendation engine 1304 receives the wager and parses the wager into wager characteristics. Some examples of wager characteristics include, but are not limited to, a bet history of the user 1308, the social network for the user 1308, the geographical location of the user 1308, the age of the user 1308, the gender of the user 1308, other members of the social network of the user 1308 that are affiliated with the same group of users (e.g., people that work in the same office as the user 1308, or went to the same university as the user 1308), user preferences (e.g., teams of which the user 1308 has indicated as being a fan), the bet history of friends of the user 1308, and the like. Based on the wager characteristics, the recommendation engine 104 may determine which friends of the user 1308 are likely to have an affinity for the same wager, i.e., which friends would be interested in placing a bet on this wager.

After placing the wager, an interface may be displayed to the user that allows the user 1308 to invite friends to the wager. Such an interface may be termed a “friend picker.” In some embodiments, the friends of the user 1308 may be presented to the user in the interface sorted by affinity to the wager. For example, based on the results of the recommendation engine 1304, the friends may be sorted so that friends with the greatest affinity for the wager are placed near the top of the interface. In another embodiment, the friends may be organized into groups based on affinity to the wager. For example, the groups may include (i) “Friends likely to be interested in the wager,” (ii) “Friends likely to be disinterested in the wager,” or (iii) “Friends that are indifferent to the wager.”

The user 1308 may then select which friends to invite to the wager. Based on the selection, the invitation engine 1306 transmits an invitation to the selected friends. In some embodiments, the invitation is transmitted by the invitation engine 1306 via email to the selected friends. In other embodiments, the invitation is transmitted via SMS (Short Message Service), fax, postal mail, or via any other technically feasible manner. In other embodiments, the invitation may be transmitted via mobile messaging. For example, in embodiments where the venture exchange is implemented, in part, as a mobile application on a mobile phone (e.g., an iPhone® app), the invitation may be sent to the mobile application via mobile messaging, separate from SMS or mobile browsing. In some examples, the invitation may be a push notification received by the mobile application. In other embodiments, the invitation may be transmitted via a third-party website or service. For example, the invitation may be transmitted as a notification via a social networking site, such as Twitter or Facebook. The invitation includes a description of the bet and the options offered on which to wager. The invitation may also include an indication of which user has invited the friend to the bet, how that user wager (e.g., which side did the inviting friend take), who else was invited to the wager, or any other technically feasible information. The user 1308 that invited friends to the bet may also have access to an interface that tracks which invited friends have viewed the invitation, which invited friends have wagered, and what side did they take.

In some embodiments, the recommendation engine 1304 may include logic that recommends, to the friends that receive the invitation, which side to take in the wager. For example, the recommendation engine 1304 may recommend for friend 1310 to take one side of the wager, but may recommend for friend 1312 to take the opposite side. Factors that the recommendation engine 1304 may consider when recommending a side for the invited friend to take may include prior bet history of the friend, demographics, geographical location, age, gender, favorite teams, or any other factors.

In further embodiments, the recommendation engine 1304 may present the invitation to the invited friends in one of several different views or media based on the various characteristics or settings. For example, the invitation to friend 1310 may be sent via email, whereas the invitation to friend 1312 may be sent via SMS. In another example, the invitation to friend 1310 may include a recommendation for a side to take, whereas the invitation to friend 1312 may not include a recommendation for a side to take. In yet another example, the interface or display that embodies the invitation may be different for different recipients of the invitation. Again, any number of different characteristics or settings may be taken into account by the recommendation engine 1304 and/or invitation engine 1306 when delivering the invitation to the selected friends.

FIG. 14 is a flow diagram of method steps for inviting friends to a wager, according to at least one embodiment of the invention. Persons skilled in the art will understand that, even though the method 1400 is described in conjunction with the systems of FIGS. 1-8A and 9-13, any system configured to perform the method steps, in any order, is within the scope of embodiments of the invention.

As shown, the method 1400 begins as step 1402, where a venture exchange receives a wager placed by a first user. The wager can be any type of wager, including a straight wager, a paramutual (or pool-based) wager, a parlay wager, or any other type of wager. In some embodiments, the wager is placed after the user has logged-in to a website operated by the venture exchange to place the wager. In other embodiments, the wager may be placed via a mobile phone or a standalone device or kiosk.

At step 1404, the venture exchange parses the wager to determine wager characteristics of the wager. Some examples of wager characteristics include, but are not limited to, a bet history of the user, the social network for the user, the geographical location of the user, the age of the user, the gender of the user, other members of the social network of the user that are affiliated with the same group of users (e.g., people that work in the same office as the user, or went to the same university as the user), user preferences (e.g., teams of which the user has indicated as being a fan), the bet history of friends of the user, and the like. In reference to FIG. 1, the wager characteristics may also include the global attributes 115, the group attributes 114, the user-specific attributes 128, and/or the venture creation factors 112.

At step 1406, the venture exchange determines which friends of the first user have an affinity for the wager based on the wager characteristics. In one embodiment, the recommendation generator 150 shown in FIG. 1 performs step 1406. At step 1408, the venture exchange displays to the first user a wager invitation interface, where friends of the first user are sorted based on relative affinity for the wager. In some embodiments, the presentation engine 154 is configured to generate the interface displayed to the first user. For example, the friends of the user in a social network that have the greatest affinity for the wager may be placed at the top of the interface, and friends that have the lowest affinity for the wager may be placed at the bottom of the interface. In other embodiments, the friends may be organized in groups. The groups may include (i) “Friends likely to be interested in the wager,” (ii) “Friends likely to be disinterested in the wager,” or (iii) “Friends that are indifferent to the wager.”

At step 1410, the venture exchange receives a selection from the first user of friends to invite to the wager. For example, the first user may click on or otherwise select which users to invite to participate in the wager.

At step 1412, the venture exchange transmits a wager invitation to each of the selected friends. In one embodiment, the invitation engine 1306 in FIG. 13 is configured to generate the wager invitation and transmit the wager invitation to the appropriate friends. As described above, embodiments of the invention provide wager invitations that are transmitted via email, SMS, fax, postal mail, mobile messaging, third-party application or service, or any other technically feasible medium. In addition, in some embodiments, different wager invitations may be transmitted based on various characteristics of the wager and/or settings.

Advantageously, embodiments of the invention allow a user to quickly and easily select which users to invite to participate in the wager. Since the friends are organized by affinity to participate in the wager, the user can more readily determine whom to invite. Embodiments of the invention are especially useful when the user has many friends (e.g., over 500 friends). Another advantage is that inviting other users to participate in a wager drives traffic to the venture exchange, allowing the venture exchange to generate more revenue.

Various embodiments of the invention may be implemented as a program product for use with a computer system. The program(s) of the program product define functions of the embodiments (including the methods described herein) and can be contained on a variety of computer-readable storage media. Illustrative computer-readable storage media include, but are not limited to: (i) non-writable storage media (e.g., read-only memory devices within a computer such as CD-ROM disks readable by a CD-ROM drive, flash memory, ROM chips or any type of solid-state non-volatile semiconductor memory) on which information is permanently stored; and (ii) writable storage media (e.g., floppy disks within a diskette drive or hard-disk drive or any type of solid-state random-access semiconductor memory) on which alterable information is stored.

In at least some of the embodiments of the invention, the structures and/or functions of any of the above-described interfaces and panels can be implemented in software, hardware, firmware, circuitry, or a combination thereof. Note that the structures and constituent elements shown herein, as well as their functionality, can be aggregated with one or more other structures or elements. Alternatively, the elements and their functionality can be subdivided into constituent sub-elements, if any. As software, the above-described described techniques can be implemented using various types of programming or formatting languages, frameworks, syntax, applications, protocols, objects, or techniques, including C, Objective C, C++, C#, Flex™, Fireworks®, Java™, Javascript™, AJAX, COBOL, Fortran, ADA, XML, HTML, DHTML, XHTML, HTTP, XMPP, Ruby, Ruby on Rails, and others, such as MySQL. These can be varied and are not limited to the examples or descriptions provided.

The various embodiments of the invention can be implemented in numerous ways, including as a system, a process, an apparatus, or a series of program instructions on a computer-readable medium such as a computer-readable storage medium or a computer network where the program instructions are sent over optical or electronic communication links. In general, the steps of disclosed processes can be performed in an arbitrary order, unless otherwise provided in the claims.

The foregoing description, for purposes of explanation, uses specific nomenclature to provide a thorough understanding of the invention. However, it will be apparent to one skilled in the art that specific details are not required in order to practice the invention. In fact, this description should not be read to limit any feature or aspect of the present invention to any embodiment; rather features and aspects of one embodiment can readily be interchanged with other embodiments. Notably, not every benefit described herein need be realized by each embodiment of the present invention; rather any specific embodiment can provide one or more of the advantages discussed above. In the claims, elements and/or operations do not imply any particular order of operation, unless explicitly stated in the claims. It is intended that the following claims and their equivalents define the scope of the invention.

Claims

1. A computer-implemented method for inviting members of a venture exchange to participate in a wager, comprising:

receiving a wager placed by a first user;

parsing the wager to determine wager characteristics associated with the wager;

determining, using a processor, friends of the first user that have an affinity for the wager based on the wager characteristics;

causing an interface to be displayed to the first user, wherein the friends of the first user are organized by a relative affinity for the wager;

receiving a selection by the first user of friends to invite to participate in the wager; and

transmitting a wager invitation to each friend selected by the first user.

2. The method of claim 1, wherein the wager characteristics include at least one of a bet history of the first user, a geographical location of the first user, an age of the first user, a gender of the first user, preferences of the first user, and a bet history of friends of the first user.

3. The method of claim 1, further comprising the step of sorting all of the friends of the first user based on the relative affinity for the wager, wherein the friends of the first user are presented to the first user in the interface based on results of the sorting.

4. The method of claim 1, further comprising the step of grouping the friends of the first user into groups based on the relative affinity for the wager.

5. The method of claim 1, wherein the wager invitation is transmitted via email, SMS (Short Message Service), fax, or postal mail.

6. The method of claim 1, wherein the wager is placed by the first user via mobile browser on a mobile phone.

7. The method of claim 1, wherein the wager is placed via a standalone device or kiosk.

8. The method of claim 1, wherein the wager invitation is transmitted via mobile messaging to an application installed on a mobile phone.

9. The method of claim 1, wherein the wager invitation is transmitted via a third-party website or service.

10. The method of claim 1, wherein the wager invitation includes a description of the wager including different betting options available.

11. The method of claim 10, wherein the wager invitation further includes a recommendation of which betting option the friend should select based on one or more characteristics of the friend.

12. The method of claim 10, wherein the wager invitation further includes information that indicates which betting option the first user selected when placing the wager.

13. A computer-implemented method for providing an interface through which a first user invites other members of a venture exchange to participate in a wager, comprising:

displaying an interface to the first user, wherein friends of the first user are organized by a relative affinity for the wager based on one or more wager characteristics; and

receiving a selection of one or more friends to invite to participate in the wager, to cause a wager invitation to be transmitted to each of the one or more friends.

14. The method of claim 13, wherein the wager characteristics include at least one of a bet history of the first user, a geographical location of the first user, an age of the first user, a gender of the first user, preferences of the first user, and a bet history of friends of the first user.

15. The method of claim 13, wherein the friends are displayed in a ranked order in the interface based on the relative affinity for the wager.

16. The method of claim 13, wherein the friends are displayed in groups in the interface based on the relative affinity for the wager.

17. The method of claim 13, wherein the wager invitation is transmitted via email or SMS (Short Message Service).

18. The method of claim 13, wherein the wager invitation includes a description of the wager including different betting options available.

19. The method of claim 18, wherein the wager invitation further includes a recommendation of a betting option for the friend to select based on one or more characteristics of the friend.

20. The method of claim 18, wherein the wager invitation further includes information that indicates which betting option was selected by the first user that placed the wager.