Abstract:
A method and apparatus for facilitating electronic commerce between suppliers of predictions and consumers of predictions. Suppliers provide their predictions on the outcomes of future events in one or more categories, and each supplier&#39;s accuracy is tracked. Consumers interested in obtaining predictions for one of more of those categories are allowed to selectively choose which suppliers&#39; predictions they wish to view. The suppliers are compensated based on the number of consumers who view their predictions. In one embodiment, the consumers pay for the predictions that they view while the suppliers are paid a portion of the revenue obtained from the consumers. In another embodiment the consumers are not charged and all revenue is derived from advertisers. The system in accordance with the present invention includes a controller which automatically credits each supplier&#39;s account, aggregates earnings for that supplier, and automatically sends an electronic pay order to the Federal Reserve&#39;s automated clearinghouse to thereby facilitate payment.

Description:
RELATED APPLICATIONS 
     There are no related applications. 
     1. Field of the Invention 
     The present invention is directed to an electronic network-based marketplace for supplying and consuming predictions of future events. More particularly, it is directed to a marketplace in which suppliers are compensated based on the number of consumers who view their predictions. 
     2. Background of the Invention 
     The internet, also called the world wide web, or simply, the “web”, has been increasingly used as a means of communication in recent years. One area in which the web has found particular use is electronic commerce whereby goods and services provided by a supplier are made available for sale to a consumer. As seen in FIG. 1, the web  100  serves as the communication means between consumers  102  and suppliers  104 , each of which is represented as a computer connected to the web. A consumer and a supplier can communicate directly with one another across the web if one knows the other&#39;s e-mail address, or web-site URL, and this type of information can often be found by using well-known internet search engines available to either via their internet service provider. 
     As an alternative to direct communication between a consumer  102  and a supplier  104 , one may instead use a facilitator  106 , represented by a computer in FIG.  1 . The facilitator&#39;s web-site serves as a depository of information concerning the goods and/or services offered by a number of suppliers. Consumers can visit the facilitator&#39;s website and browse through one or more categories of good and/or services to view the offerings of various suppliers. After viewing these, a consumers may then request more information about a particular item or service, or may even purchase the goods and/or services. This can be done by either directly contacting the supplier, if the facilitator so permits, or by contacting the supplier via the facilitator, with the facilitator acting as an intermediary. The facilitator may charge either the customer, the supplier, or both, for introducing one to the other, either on a subscription basis, a per-introduction basis, a per-completed transaction, a sales-volume basis, or in accordance with some other agreed-upon arrangement with the supplier and/or buyer. Thus, items as collectibles, airline tickets and a host of other goods and services can be obtained, either at a fixed price, or by auctions and even reverse-auctions, all via a facilitator. 
     SUMMARY OF THE INVENTION 
     The present invention is directed to a marketplace for information provided by a plurality of suppliers for display on a facilitator&#39;s web-site. The information resides in a relational database on the facilitator&#39;s web-site and can be selectively viewed by a consumer without having to jump to a supplier&#39;s web-site. A supplier is compensated based on the number of times that that supplier&#39;s information is viewed by consumers. In the preferred embodiment, the type of information supplied by the suppliers are predictions about future events, and consumers view these predictions. 
     In one embodiment, a consumer is charged by the facilitator for viewing a supplier&#39;s information, and a portion of the payment collected from that consumer is then passed on to the supplier as compensation. For this, the consumer must first provide the facilitator with billing information to establish some form of electronic collection scheme so as to permit the facilitator to charge the consumer for each access to information. 
     In another embodiment, consumers are charged nothing for viewing a supplier&#39;s information. Revenue to pay the suppliers comes from advertisers, whose advertisements are displayed while a user is logged into the system. Because the consumers are charged nothing in this embodiment, the invention also contemplates preventing a supplier from benefitting from friends (or themselves) repeatedly viewing the same information provided by a supplier simply for the purpose of boosting the amount of compensation made to that supplier. This is done by crediting a supplier only if a particular consumer has not previously viewed that particular piece of information. For this, the facilitator keeps track of what all items a particular consumer has previously viewed for which the seller has already been credited. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     FIG. 1 is a schematic showing suppliers, consumers and facilitators connected by the web; 
     FIGS. 2-19 present a first embodiment of the present invention (called “SPORTSCAPPERS™”) wherein: 
     FIG. 2 show the home page; 
     FIG. 3 show the registration page; 
     FIGS. 4 a-   4   c  show the terms-and-conditions page; 
     FIGS. 5 a-   5   b  show the instruction page; 
     FIG. 6 shows the top-analysts-criteria page; 
     FIG. 7 shows the top-analysts-display page; 
     FIG. 8 shows the supplier-daily-history page; 
     FIGS. 9A &amp; 9B show the supplier-daily-event page; 
     FIG. 10 shows the future-picks page; 
     FIG. 11 shows the how to-buy-picks instruction page; 
     FIG. 12 shows the privacy-policy page; 
     FIG. 13 shows the enter-your-picks-category page; 
     FIG. 14 shows the line-policy page; 
     FIG. 15 shows the enter-your-picks-not-logged-in page; 
     FIG. 16 shows the enter-your-picks-play page; 
     FIGS. 17 a-   17   b  show the confirmation-of-picks page; 
     FIG. 18 shows the member-account page; 
     FIG. 19 shows the shopping-cart-payment page; 
     FIGS. 20-24 present a second embodiment of the present invention (called “PREDICTIT!™”) wherein: 
     FIG. 20 is the home page; 
     FIGS. 21A &amp; 21B are the registration pages; 
     FIG. 22 is the welcome page; 
     FIG. 23 is the top-analysts-criteria page; and 
     FIG. 24 is the group-management page. 
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     The prediction marketplace in the present invention is run by a facilitator who provides a web-site on one or more server computers. The server computer typical includes a processor, one or more memory storage devices such as semiconductor memory, disk drives or other computer storage medium, an interface device such as a modem or Ethernet adapter, or the like to connect the server computer to the internet or other network, along with other elements, as is known to those skilled in the art. The server computer is preferably connected to a database, such as a relational database management system. Resident in a memory device associated with the computer is executable software, typically including interface code, algorithmic code, database code, and other code which performs all the functions needed to operate the server computer. 
     The web-site comprises a number of pages written in hypertext mark-up language (HTML) suitable for transmission to a remote computer across the internet or other network. When visiting the web-site, consumers can access and view the predictions of suppliers, and suppliers can, among other things, enter predictions for future events. The supplier&#39;s predictions, results of those predictions, and other information at the web-site is preferably stored in the relational database, in a manner known to those skilled in the art. 
     FIGS. 2-19 show one embodiment of the user interface to a prediction marketplace in accordance with the present invention. The embodiment shown, called SPORTSCAPPERS™, provides a marketplace for predictions on the outcome of certain sporting events selected by the facilitator. A user accesses the web-site through the internet and is permitted to navigate through the web-site to enter predictions, view predictions, or simply browse through various portions of the web-site. 
     FIG. 2 shows the front page  110  of this web-site. The user is provided with a window for logging in. A user may log in only if that user has previously registered and has established an identity within the marketplace (i.e., is a member). If the user is a member, the user is asked to enter his email address in login e-mail address field  114  and his password in login password field  116 , and then click on the ‘Login’ icon  118 . 
     If the user is not already a member, or does not want to login even though he is a member, the front page includes a number of hot links to permit further navigation through the web-site. Each hot link is represented by underlined text or an icon which can be activated, as is commonly known to those skilled in the art. A registration link  120  “Become a SportsCapper—It&#39;s Free” sends a user to a registration page  130  which asks for information allowing a user to become a member. A best-predictors link  122  “Get the picks of the Hottest Cappers in the Country” or “See Who&#39;s Hot” sends a user to a top-analysts-criteria page  200  which leads to information on the performance of the best prediction suppliers. Finally, an instruction-and-information link  124  “How it works” sends the user to an information page  170  which further explains how to play the game. Auxiliary links  120 ″,  122 ″, which are associated with additional text, send the user to the same pages as links  120 ,  122 , respectively, thereby providing the user with more than one link to the same page. 
     FIG. 3 shows the registration page  130 , which allows a user to become a member. Registration page  130  preferably includes one or more windows  132  in which advertisements placed by third parties, or even the facilitator, are displayed. The advertisements may promote specific products, specific services, a specific entity such as a business or organization, and will often provide one or more links to other sites where more information may be obtained. The Registration page  130  also includes a terms-of-registration link  134  “Terms and Conditions” which sends a user to a terms and conditions page  160   a-c  detailing rules of the marketplace, the respective obligations of the facilitator and the users, and the terms to which the user agrees, among other items. The remainder of the registration page  130 , however, is devoted to registration information 
     In this embodiment, certain identifying information  136  is required of all users who wish to be members, i.e., participants in the marketplace. The registration nickname field  138  requests a unique nickname by which the user will be known in the system, especially when that user supplies predictions. No two users in the marketplace can have the same nickname so as to prevent confusion. The registration e-mail address field  140  asks for the user&#39;s email address and the registration password field  142  asks for a user-selected password. The registration password verification field  144  asks the user to repeat the password to ensure that the user did not mistype it the first time. Finally, the registration password hint field  146  requests the user to enter a word which will remind the user of his password, should the password have been forgotten. While the nickname is used primarily for name recognition among participants in the marketplace, the e-mail address and the password are used for administrative purposes, as discussed further below. 
     In addition to just providing identifying information, a user can also enter contact information  148 , which will be used by the facilitator to make payments to suppliers whose predictions are viewed by consumers. A user need only enter contact information, if the user wants to be compensated for providing predictions. For this, a first name field  150   a,  a last name field  150   b,  a street address field  152   a,  a city field  152   b,  a state/province field  152   c,  a postal/zip code field  152   d  and a country field  152   e  are provided to receive the name and address of a user. A telephone field  154  may also be provided for the user to enter his telephone number, in the event that the facilitator wishes to contact the user. 
     Once the requested information has been provided, a user may activate a register button  156  to submit the registration information. Upon registering, the user becomes a participant in the marketplace, and is authorized to supply predictions which consumers may view. 
     FIGS. 4 a-c  show the terms of registration page  160 , presenting the terms and conditions of participation. Included in these are a brief summary of the rules concerning such things as the submission of predictions, charging a consumer for viewing predictions, compensating a supplier for viewed predictions, and other terms and conditions governing the participant as well as the facilitator. 
     FIGS. 5 a  &amp;  5   b  show the information page  170  which provides directions on how to participate in the marketplace, tips on how to succeed in the marketplace, and also provides a number of links to other pages which a user may exercise. 
     The enter-your-picks link  172  sends a user to an enter-your-picks-category page  310  on which a supplier can view the various events for which predictions are being accepted, and then enter his predictions. There is no charge to enter predictions for events and so suppliers are not charged anything for their participation. 
     The line-policy link  174  sends a user to a line policy page  320  which explains how the facilitator sets the margin for an event in which the outcome is a numerical score—e.g., the point spread in a football game. Instead of, or in addition to, the margin, the line policy page may include information on odds, risk factors and other parameters which may be taken into account when making predictions of the offered events. 
     The view-your-performance link  176  sends a supplier to a performance page  200   a  which presents information on how well, i.e., how accurate, that supplier&#39;s predictions have been over a selected time period in a given event category. The performance page  200   a  also indicates the performance of the best predictors in the marketplace for comparable periods in the same event categories. This allows the participant/supplier to compare his own performance with those of the best prediction suppliers in the marketplace. 
     A supplier may only enter predictions for future events which have been selected by the facilitator. After a supplier has entered his predictions for an event, that supplier earns credits each time a consumer views his predictions. To maximize the number of consumer who will view his predictions for a given event, a supplier must try to do two things: enter his predictions as soon as the facilitator has identified the event(s) for which predictions will be accepted; and establish a good track record at accurately predicting the outcomes of events. The first of these is simply to make sure that his own predictions are posted for the longest time possible before the event occurs, thus providing maximum opportunity for consumers to select that supplier&#39;s predictions. The second is to establish that that supplier has been good at making predictions of past events, and so presumably will be good at predicting future events, thereby prompting consumers to elect to view that supplier&#39;s predictions. 
     To establish a track record, a supplier who has not entered any predictions before, must predict a number of events in a given event category over a period of time. By accurately predicting the outcome of several of these events, that supplier establishes a good track record which may merit being displayed on the list of best predictors over a preselected time period in a particular event category. Although some consumers are likely to be most interested in the predictions of a supplier who has established a good track record over an extensive period of time, say, 30 days, other consumers may only be interested in suppliers who have done very well over a much shorter period of time, and are on a ‘hot streak’. Therefore, it is entirely possible that a supplier who has accurately predicted the outcomes of events for a very short time may find his predictions in demand. 
     The privacy-policy link  176  sends a user to a privacy policy page  300  explaining the facilitator&#39;s policy on revealing information about a member. 
     FIG. 6 shows the top-analysts-criteria page  200 . This page  200  permits a user to enter a number of parameters to define the search for the best predictors to be displayed; the page also provides opportunities for a user to learn more about how the user can obtain additional information about obtaining predictions. Once the various search parameters have been set, a query engine searches through the database to extract information responsive to the set of parameters designated by the user (filtering) and then displays the responsive information in an order in accordance with some criterion (sorting). Thus, the information about the best predictors is found and formatted “on the fly” and is always up to date, rather than being a “canned” report which is periodically updated by the facilitator or other entity. 
     The how-to-buy-picks link  202  sends a user to a pick purchase instruction page  280 . 
     The event-category window  204  provides a pull-down screen which allows a user to select the event category for which the best predictors will be displayed. In this embodiment, which is directed to the field of sports, a user can select the best predictors in one of several sports: college basketball, professional basketball, college football, professional football and professional hockey, college basketball being the default. It should be evident, however, that the selection of event categories in the field of sports may vary depending on the time of year. It should also be evident that non-team sports such as boxing, tennis, figure skating, golf, etc. may also serve as event categories in the field of sports. 
     The event-sub-category window  206  provides a pull-down screen which allows a user to select the kinds of sub-categories for each event which the search engine should take into account in identifying the best predictors. In the preferred embodiment, if a user were to pull down this window, the following choices would appear: “Side”, “O/U” (‘over/under’) and “Side &amp; O/U” (the default). “Side” refers to events in which a supplier picked which side would win, after the spread is taken into account. “O/U” refers to events in which the supplier picked whether the combined score of the teams was over, or under, a predetermined value selected by the facilitator; and “Side &amp; O/U” refers to events in which the supplier made predictions on both of these event sub-categories. It should be evident that additional event sub-categories may be provided, and that different sports may have different subcategories. For instance, football games may include a “score by quarter O/U” sub-category, tennis matches may have a “games per match O/U” or “games per set O/U” sub-category; and hockey games may have a “shots on goal O/U” sub-category. 
     The number-of-days-criteria button  208   a,  the entire-season-criteria button  208   b  and number-of-days field  210  allow a user to define a relevant time period over which prediction performance for past events is taken into account in ranking the best predictors. If the user enables the number-of-days-criteria button  208   a,  and sets a value in the number-of-days field  210  to X, X being at least 1, the system will take into account the prediction performance over the most recent X days of all prediction suppliers in the selected event category, to determine the best predictors. If, on the other hand, a user enables the entire-season-criteria button  208   b,  the prediction performance for the entire season is taken into account. While the preferred embodiment allows one to define the relevant time period in either number of days, or the entire season, the important principle is that a user be able to define some predetermined criteria for selecting corresponding prediction performance data, from which the best predictors are determined. Thus, the facilitator may provide alternative options such as ‘the last X predictions’, or ‘the best predictions in month X’, and so forth. 
     The particular-supplier field allows a user to obtain the prediction performance record of one or more particular suppliers, over the defined period. This is done by entering the nicknames of the particular suppliers in field  212 . If one or more particular suppliers&#39;nicknames are entered in this field, their prediction performance results are displayed, in addition to those of the best predictors. 
     Once a user has completed selecting options on the top-analysts-criteria page  200 , the user clicks on the ‘Go’ button  214  to obtain the best predictors, in accordance with the selected options. Clicking on this button causes the search engine to retrieve and display the best predictors on the top-analysts-display page  200   a,  which is displayed on the user&#39;s computer screen. 
     FIG. 7 shows the top-analysts-display page  200   a,  which displays the performance results of the  25  best prediction suppliers. This page also provides a link  216  for a member to log on so as to view his own prediction performance and compare it with the best. 
     The top  25  prediction suppliers, each listed by nickname  218 , are ranked according to the number of rating points  220  (“units”) each has earned, and also presents the number of correct and incorrect predictions each has made, along with additional statistics. If a supplier predicts an outcome correctly, he wins a first predetermined number of rating points and if the supplier guesses incorrectly, he loses a second predetermined number of rating points, preferably greater than the first predetermined number so as to provide a penalty for guessing. Because both correct and incorrect predictions are accounted for in the total rating points earned by a supplier, it may be possible for a supplier to have a net negative number of rating points over the course of a single day, or even a prolonged period. This allows new suppliers with relatively little experience to establish themselves as expert predictors by demonstrating that they have a positive number of rating points. 
     In the preferred embodiment, the best predictors are ranked in descending order, based on the total number of rating points each has earned, in accordance with the selection criteria specified on the top-analysts-criteria page  200 . It should be evident, however, that other criteria, such as the ratio of rating-points-won to rating-points-lost, the ratio of correct to incorrect predictions, or daily average of the difference between rating points won and rating points lost, and a multitude of other metrics may used instead. What is important is that the system should calculate some metric which reflects the performance of the predictors in accordance with filtering criteria such as event categories, event determinations and relevant time periods. 
     The top-analysts-display page  200   a  also includes a supplier-research link  222  which allows a user to delve into the specific predictions made by a particular supplier, which led to that supplier being listed on the best predictors page display page. Clicking on the supplier-research link  222  sends the user to the supplier-daily-history page  230 , which lists the day-by-day performance of the selected supplier. 
     The top-analysts-display page  200   a  also includes a future-games column  224  which indicates whether the corresponding supplier has made predictions for future events. If so, the corresponding column entry has a future-games link  226  which takes the user to a future-pick page  260 . If a particular supplier has not made any predictions for future events, the corresponding entry in the future-games column  224  indicates that there are none  228 . 
     FIG. 8 shows the supplier-daily-history page  230  for the supplier nicknamed ‘slickrick’ on the top-analysts-display page  200   a.  The supplier-daily-history page  230  displays slickrick&#39;s day-by-day prediction performance results for each day on which he predicted the outcome of one or more event. A user can delve into the particular events on any given day, by clicking the daily-research link  232 . Clicking on the daily-research link  232  sends the user to a supplier-daily-event page  240  which details the predictions made by ‘slickrick’ for each event on the selected day, and the outcome of those events. 
     FIGS. 9 a-   9   b  show a supplier-daily-event page  240  for corresponding to a particular day on which ‘slickrick’ predicted the outcome of a number of college basketball games. As seen in these figures, ‘slickrick’ predicted the outcome of seven games taking place on Feb. 14, 1999. A daily-summary text box  242  repeats the summary information on the supplier-daily-history page  230  corresponding to the detailed information on the displayed supplier-daily-event page  240 . Each of the games, game time and final score are identified in a past-game-information text box  244 , along with information  246  about the outcome of that game. For each game, this information includes the point spread  248 , the amount of rating points risked for incorrectly predicting the outcome of an event  250 , the number of rating points gained for a correct prediction  252 , the game score  254  and the outcome of ‘slickrick&#39;s’ prediction for that game  256 , i.e., whether or not he was correct. 
     FIG. 10 shows a future-pick page  260  for ‘slickrick’. The future-pick page  260  lists the various events  262  for which ‘slickrick’ has made predictions, including the start time of each event. An icon  264  next to each event  262  allows the user to add the corresponding prediction to the user&#39;s electronic shopping cart. If the user has not logged in, a text box  266  states this, and advises the user that one must either login or register to obtain predictions for the listed future events. A login link  268  and a register link  270  are provided to further assist the user. If the user were now to login (or register) as a member, and ultimately view ‘slickrick&#39;s’ predictions, ‘slickrick’ would earn money for each prediction that is viewed by that member. 
     FIG. 11 shows the how-to-buy-picks instruction page  280 . This page has a first text box  282  advising that a user can get a list of the best predictors in an event category; a second text box  284  advising that a user can get research information about the underlying events predicted by each of the best predictors; a third text box  286  advising that a user can determine whether a particular supplier on the best predictors list has predictions for future events which may be viewed; a fourth text box  288  advising how a user can select one or more of those predictions for viewing and a fifth text box  290  advising how the user can pay for the predictions  290 , either by having the cost debited to a credit card account, or debited to a prepaid account which has been arranged with the facilitator. Other forms of payment, such as debiting a bank account or electronic cash may also be provided for. Additional text boxes may be provided to provide further detail about any one or more of these directions. 
     FIG. 12 shows the privacy-policy page  300 , which includes a text box  302  explaining the facilitator&#39;s policy regarding dissemination of information about members. The facilitator may set up certain guidelines to ensure the privacy of members in the marketplace, and agree only to display the members&#39;own nicknames, such as when displaying the top-analysts-display page  200   a.    
     FIG. 13 shows the enter-your-picks-category page  310 . Information about how to make predictions, how the point spread works, and when one can make predictions can be obtained by clicking the line-policy link  312  and going to the line-policy page  320 . This page also includes a pull-down menu  314 , which allows a user to select from among a number of categories in which predictions for future events are being accepted by the facilitator. Once the user has selected the desired category in which the predictions are to be made, the user clicks on the “Go” button  316  to start entering his predictions. If the user is a member who is logged in as a supplier, clicking the “Go” button sends the supplier to the enter-your-picks-play page  370 . If, on the other hand, the user is neither logged in nor recognized by the facilitator as a supplier, clicking the “Go” button  316 , sends the user to an enter-your-picks-not-logged-in page  340 . 
     FIG. 14 shows a sample line-policy page  320  for event categories in the field of sports. The line policy page includes a line-source text box  322  which explains the basis for the betting line used. A pick-entry-opening-times text box  324  explains when predictions may be entered each day for the various sports. A spreads-and-odds text box  326  explains how the spreads and risks work for each of the event categories—for each event, a user risks losing a first designated number of rating points to win a second designated number of rating points. Typically, the amount risked is greater than the amount that one can win to penalize random guessing, and the differential between the two varies from sport to sport, and sometimes even event to event. A presentation text box  328  explains the layout of the pick options, and a questions text box  330  provides a link for users to contact the facilitator. 
     FIG. 15 shows the enter-your-picks-not-logged-in page  340 . This page includes a text box  342  advising the user that he is not logged in, and providing links to enable the user to either login or register. The page  330  nevertheless lists the events for which predictions are being accepted. Each event is provided with an upcoming event information text box  344  listing the teams, and the time that the event will start. In the preferred embodiment, one is not permitted to make predictions after an event starts. Event prediction information  346  is also provided for each of the events. The prediction information includes the point spread  348 , the amount of rating points risked  350  if one were to incorrectly predict the outcome of the event, and the amount of rating points that can be earned  352  if one were to correctly predict the outcome of the event. A pick column  354  allows the user to enter his prediction for those events which are enabled, as indicated by the pick status column  356 . In page  340 , because the user is not logged in, all picks are disabled, as indicated by ‘no pick’ designations  358 ,  360 . 
     FIG. 16 shows the enter-your-picks-play page  370 , which is substantially similar to the enter-your-picks-not-logged-in page  350 . A text box  372  on page  370  provides a link to the line policy page  320 . A supplier may enter his prediction for each of the listed events by clicking on the icon  374  in the pick column  376  for those events which are not designated in the no-pick column  378  as being disabled  380 . Once the supplier has selected and edited his picks, the supplier may then enter them by clicking on the submit-picks button  382 . Clicking on the submit-picks button  382  causes a confirmation of picks screen  390  to be displayed. 
     FIGS. 17 a-b  shows the confirmation-of-picks page  390 . This page  390  includes text box  392  instructing the supplier how to confirm his picks once he has reviewed his selections A first icon  394  allows a supplier to confirm picks, and a second icon  396  allows the supplier to make changes to the picks previously selected. For each event, the confirmation-of-picks page  390  includes, among other items, the amount of rating points risked, the amount of rating points that one can win by predicting the outcome, and the prediction itself  398 . After a particular event is over, the outcome of the event, e.g., the score of that particular ball game is entered into the database. This information will then be used to score the corresponding picks made by a supplier, when that supplier&#39;s prediction performance is next accessed. 
     FIG. 18 shows a member-account page  400 . The member-account page includes a field for displaying the pre-paid-credit balance  402  from funds that the member had previously deposited, the complimentary-credit balance  404  given from time to time by the facilitator, and the earnings  406  from consumers viewing that member&#39;s predictions. The pre-paid-credit balance may be from unused monies originally deposited by sending in a check or money order, authorizing charges to a credit card or a bank account, or receiving advance payment in some other manner. A registration update text box  408  on this page  400  provides the user with a link to change registration information. 
     FIG. 19 shows a shopping-cart-payment page  410 . This page  410  includes a text box  412  providing members with the option to buy pre-purchased credit. An available-credit-information window  412  presents information on the credits or funds available for purchasing predictions. A present-sale window  414  presents information on the total amount of pending purchases of both predictions and additional pre-purchased credit, and provides the member with an icon  416  to remove items from the shopping cart which the member has previously selected for purchase. An applied-credit-information window  418  presents data on how the member has selected to pay for the current set of purchases, and a remaining credit after sale window  420  presents the remaining balance in various forms of credit after the purchase has been finalized and payment has been made. Finally, a use-credit icon  422  allows consumer to choose to pay for the purchases with a credit card, or other form of payment involving a financial institution. 
     In the SPORTSCAPPERS™ embodiment of FIGS. 2-19, a consumer of predictions must pay for the predictions of suppliers that that consumer wishes to view. Thus, the consumer is charged by the facilitator for viewing the predictions and the supplier whose predictions are viewed receives a portion of amount charged. One may instead establish a prediction marketplace in which a consumer may view the predictions for free, with most, if not all, revenue to compensate the suppliers being provided by advertisers. In such case, one does not need payment information from the consumers and no funds need be collected from them. The alternate embodiment in which consumers need not pay not only increases the number of consumers, who would then view the predictions for free, but also eliminates the administrative burdens and costs of collecting from the consumers. 
     FIGS. 20-23 illustrate a number of web pages from an alternate embodiment of a web-based prediction marketplace, called PREDICTIT!™, which has many functional features in common with the SPORTSCAPPERS™ embodiment. In contrast to the SPORTSCAPPERS™embodiment, the PREDICTIT!™ embodiment does not charge consumers for viewing a supplier&#39;s predictions and so a supplier whose predictions are viewed is not paid a portion of any payment made by the consumer to the facilitator. Instead, a supplier earns a small amount of money, for example, $0.01, each time any of his prediction are viewed by a consumer, and these monies are provided indirectly by advertisers on the web-site. 
     FIG. 20 shows the home page  500  of the PREDICTIT!™ web-site. A login window  502  asks a user to log onto the web-site by entering an e-mail address and password. If the user has not previously registered, the user may do so by activating the register hot link  504  to be transferred to a registration page  510 . 
     FIGS. 21A &amp; 21B show the registration page  510 . The registration page  510  displays a number of mandatory fields  512  for entering information which is required of all users, whether they wish only to view others&#39;predictions, or provide predictions for others to view. 
     In addition to the required information, the registration page also includes a number of optional fields  514  which the user must fill out, if that user wishes to be compensated for having their predictions viewed. The optional fields  514  call for information which helps the facilitator contact a supplier who is to be paid for his predictions, and for other matters. After filling out the registration information, the user clicks on the register button  516  to submit the registration information. 
     FIG. 22 shows the welcome page  520  to which the member is transferred, after either registering on registration page  510 , or having logged in on home page  500 . The welcome page  520  provides the member with a number of interactive windows. Included among these are a logout window  522  which permits the member to log out of the web-site and return to the home page  500 , an enter-picks window  524  which permits the member to select an event category  526  before proceeding to an enter-picks page, and a view-top-analysts window  528  which permits the member to specify a number of parameters before being transferred to a top-analysts-criteria page  550 . In addition to the windows  522 ,  524  and  528 , the welcome page also includes an enter-picks hot link  530  which transfers the member to the enter-picks page, a view-top-analysts hot link  532  which transfers the member to the top-analysts-criteria page  550 , and a view-earnings hot link  534  which transfers the user to a view-earnings page. 
     FIG. 23 shows the top-analysts-criteria page  550 . This page allows a member to specify a number of criteria to determine which predictors&#39;performance results are displayed. Included among these criteria are an event-category pull-down window  552 , an event-sub-category pull-down window  554 , a time-period-criteria option set  556  which allows one to specify the X most recent days, the entire season, or a range of dates, a minimum-number-of-picks option  558  which will only present results for suppliers who have made no less than the specified number of relevant events, and a particular-supplier field  560  which allows the user to enter the nickname of a particular supplier, and have that particular supplier&#39;s results displayed along with those of the top analysts. 
     In addition to the above criteria, the top-analysts-criteria page also includes a group option  562 . In this context, a ‘group’ means a list of member nicknames, the group itself having name specified by the user. The purpose of a group is to act as a filter in selecting which suppliers&#39;prediction performance should be displayed. When the group option  562  is selected, the user is transferred to a group-management page  570 . 
     FIG. 24 shows the group-management page  570 . In the preferred embodiment, the group-management page includes a particular-supplier window  572  in which a user can enter the nickname a particular supplier whose prediction performance results are to be viewed. The group management page also includes a number of windows and links which allow to manipulate the groups. Included among these are an add-group link  574  which allows the user to create an entirely new group, a select-group pull-down window  576  to permit the user to either delete an existing group or select which of a number of existing groups should have their members&#39;prediction performance displayed (the default being the top  25  prediction suppliers), an add-group window  578  which allows the user to create a new group and an edit-group pull-down window  580 , which allows a user to edit the membership list of an existing group. 
     The use of the various group functions should now be evident. By activating the add-group link  574 , a member may create a group named “favorites” which comprises his favorite prediction suppliers. Once the “favorites” group has been created, that member may easily obtain the performance results for all members of that group by simply selecting the ‘favorites’ group from among those in the select-group window  576 . This avoids the necessity of manually entering the nickname of each member in the particular-supplier field  560 . Similarly, each of a handful of members may decide to create a group named “buddies” which comprises their own nicknames. This allows the members of the “buddies” group to compare prediction performance amongst themselves. Thus, using groups provides an alternative to only displaying the prediction performance of the best predictors, and this feature can be used in either the paying, or the non-paying, embodiment. 
     Since the prediction marketplace of the PREDICTIT!™ embodiment is free to consumers, one may wish to ensure that a supplier does not benefit from having his friends repeatedly view that supplier&#39;s same information, either manually or by means of an automated routine such as computer program. This is because suppliers are compensated based on the number of times consumers access their predictions, and so it would be prudent to protect against repeated viewings of a supplier&#39;s predictions by the same consumer(s) solely to increase a particular supplier&#39;s earnings. One can prevent a supplier from benefitting from such collusive activity by keeping track of which consumers have viewed which of that supplier&#39;s predictions, resulting in that supplier having been credited for such viewing, i.e., a “credited prediction”. Tracking this information may be done in any number of ways, including planting cookies on a consumer&#39;s computer, keeping and updating entries in a file created for each prediction, each supplier or each consumer, or any of a number of other techniques. By keeping track of a supplier&#39;s credited predictions, one may then ensure that a supplier is not multiply credited due to the actions of the same consumer repeatedly viewing the predictions of the same supplier. For instance, a particular supplier may not be credited a second time when the same consumer views any one or more of the following: a) the same exact prediction, b) a different prediction either on the same day and/or in the same event category, or c) a different prediction in a different field. It is understood, however, that other such heuristics may be used to prevent a supplier from being credited for having his predictions viewed by the same consumer. In addition, it should also be understood that different event categories, and even different events, may employ dissimilar criteria for preventing a supplier from benefitting from the same consumer&#39;s actions, if that supplier has a credited prediction due to that consumer. 
     In either embodiment, payment is made to suppliers from time to time by the facilitator. Payment to a particular supplier may be made either periodically regardless of the amount due to that supplier, or may be made whenever that supplier earns a predetermined amount of money, say, $20.00. The form of cash payment may take one of several forms. It can be a check sent to the address supplied by the supplier, a monetary credit made to a supplier&#39;s credit card, or even a direct deposit made to a bank account of the supplier, among others. One skilled in the art will readily recognize that non-cash payments, such as merchandise credits, frequent flier miles, and other such non-monetary type of compensation can be arranged for, if the facilitator and a third party such as a corresponding store or airline so arrange. 
     It should be noted that while the above embodiments are directed to predicting events in the general field of sports, the present invention could just as easily be applied to predictions in fields other than sports. For instance, there can be a prediction marketplace for the financial field in which event categories such as stocks, bonds, commodities, currency and other securities may be provided and in which suppliers may predict the levels of such things as individual stocks, mutual funds, treasury yields, oil futures, and currency exchange rates over various time periods. Similarly, fields as diverse as weather (e.g., predicting temperature, snow fall, rain, etc. at various locations over different time periods), entertainment (e.g, predicting winners of Oscar, Grammy, Emmy &amp; Tony awards, etc.) and even politics (e.g., predicting election results, outcomes of legislation, etc.) may all be suitable for a web-based prediction marketplace. 
     Similarly, while in the described embodiments, it is the facilitator who determines the events for which predictions are accepted, the present invention is not limited to this. One or more options, links and windows may be made available to enable a user to enter information about one or more upcoming events. That user, and others, may then enter predictions about the outcome of that event. Such a provision would allow one or more members to make predictions about events which they have specified and which presumably are of significance to themselves. For instance, the members of the aforementioned “college buddies” group might create events for their alma mater&#39;s games, not otherwise provided for by the facilitator. Similarly, participants in community sports events, such as softball leagues, little leagues, high school sports, and the like, may thus find a forum in which to supply and consume each others&#39;predictions.