U.S. patent application number 13/192238 was filed with the patent office on 2012-12-27 for system and method for processing casino table games yield management data.
This patent application is currently assigned to TANGAM TECHNOLOGIES INC.. Invention is credited to Patrick Hermann DENIS, Maulin GANDHI, Prem GURURAJAN, Jason Robert JACKSON, Christopher TAYLOR.
Application Number | 20120329537 13/192238 |
Document ID | / |
Family ID | 47362353 |
Filed Date | 2012-12-27 |
View All Diagrams
United States Patent
Application |
20120329537 |
Kind Code |
A1 |
GURURAJAN; Prem ; et
al. |
December 27, 2012 |
System and Method for Processing Casino Table Games Yield
Management Data
Abstract
A system is provided for processing yield management and casino
table data. The system provides a graphical presentation of each
games table spread, and where the game is overspread or under
spread, and by how much. The table spread opportunities can also be
aggregated to determine whether what is observed is a trend so that
the operator can act on that trend to remedy it. An interactive
graphical representation of this data combined with an ability to
drill down to the underlying data to verify trends makes it
possible to find opportunities to close games, open games and add
or remove tables to the gaming floor so as to improve
profitability. Displaying graphically how pricing of tables could
be changed is particularly useful so that managers can know where
opportunities exist to change pricing in order to improve
profitability. An ability to drill down to a floor view makes it
possible for the manager to verify the casino floor and visually
see how the players are seated on tables. Displaying graphically
the time periods when an opportunity to price a game differently
than the current pricing to improve profitability also helps the
manager understand when this happens, how long it lasts and at
which price points. Displaying graphically the time periods when an
unmet demand exists also helps the manager understand when this
happens, how long it lasts and for which price points.
Inventors: |
GURURAJAN; Prem; (Kitchener,
CA) ; GANDHI; Maulin; (Kitchener, CA) ; DENIS;
Patrick Hermann; (Kitchener, CA) ; JACKSON; Jason
Robert; (Hamilton, CA) ; TAYLOR; Christopher;
(Elmira, CA) |
Assignee: |
TANGAM TECHNOLOGIES INC.
Waterloo
CA
|
Family ID: |
47362353 |
Appl. No.: |
13/192238 |
Filed: |
July 27, 2011 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
61499434 |
Jun 21, 2011 |
|
|
|
Current U.S.
Class: |
463/1 ;
463/43 |
Current CPC
Class: |
G07F 17/322 20130101;
G07F 17/3234 20130101 |
Class at
Publication: |
463/1 ;
463/43 |
International
Class: |
A63F 9/24 20060101
A63F009/24 |
Claims
1. A method, in a casino table game yield management data
processing system, of providing table spread data for a casino
environment, the method comprising: determining an actual number of
open tables associated with a first game type for each of a
plurality of time intervals; determining an ideal number of open
tables at each of the time intervals; displaying a timeline
comprising the time intervals, the timeline comprising, in
association with each time interval, a first visual element
indicative of the actual number of open tables during that time
interval, and a second visual element indicative of whether the
ideal number of open tables is above or below the actual number of
open tables; and enabling further detail corresponding to a desired
time interval to be displayed upon detecting selection of a
corresponding portion of the timeline.
2. The method of claim 1, wherein the actual number of open tables
and the ideal number of open tables are each aggregated over a
plurality of time periods, wherein each time period comprises the
plurality of time intervals.
3. The method of claim 2, further comprising enabling the timeline
to correspond to either a single time period or the aggregate of
the plurality of time periods.
4. The method of claim 2, further comprising enabling selection or
de-selection of at least one time period to be included in the
aggregation.
5. The method of claim 2, wherein the actual number of open tables
and the ideal number of open tables are each aggregated to
correspond to any one of an average, median, mean, weighted
average, and percentile.
6. The method of claim 1, further comprising displaying a third
visual element in association with at least one of the time
intervals indicative of how pricing at particular open tables could
be changed.
7. The method of claim 6, wherein the third visual element
quantifies an opportunity to improve profitability during the
respective time interval.
8. The method of claim 1, further comprising displaying a third
visual element in association with at least one of the time
intervals indicative of unmet customer demand at a particular price
point.
9. The method of claim 1, wherein the ideal number of open tables
is determined using a different optimal occupancy target for any
one or more of different price points and different game types.
10. The method of claim 1, wherein the further detail is displayed
using a third visual element in association with the desired time
interval, the further detail comprising any one or more of player
occupancy, number of players, number of seats occupied, number of
open tables, and table occupancy.
11. The method according to claim 1, wherein upon detecting
selection of the corresponding portion of the timeline, the further
detail is displayed using a third visual element providing a floor
view comprising data associated with at least one open table in an
area of the gaming environment.
12. The method of claim 11, wherein the floor view displays any one
or more of a visual depiction of each open table, players, and bets
placed by the players.
13. The method of claim 1, wherein the first visual element
provides a data point on a line graph at a respective time
interval.
14. The method of claim 1, wherein the second visual element is
varied to be indicative of the ideal number of open tables being
either above the actual number of open tables or below the actual
number of open tables.
15. The method of claim 14, wherein a threshold with respect to the
ideal number of open tables is used to trigger variation of the
second visual element.
16. A computer readable medium comprising computer executable
instructions that when executed by a casino table game yield
management data processing system, perform operations comprising:
determining an actual number of open tables associated with a first
game type for each of a plurality of time intervals; determining an
ideal number of open tables at each of the time intervals;
displaying a timeline comprising the time intervals, the timeline
comprising, in association with each time interval, a first visual
element indicative of the actual number of open tables during that
time interval, and a second visual element indicative of whether
the ideal number of open tables is above or below the actual number
of open tables; and enabling further detail corresponding to a
desired time interval to be displayed upon detecting selection of a
corresponding portion of the timeline.
17. A casino table game yield management data processing system
comprising the computer readable medium of claim 16.
18. A method, in a casino table game yield management data
processing system, of providing table spread data for a casino
environment, the method comprising: determining an actual number of
open tables associated with a game type for each of a plurality of
time intervals; determining an ideal number of open tables for the
game type at each of the time intervals; and displaying a plurality
of visual elements in a grid comparing the game type against the
plurality of time intervals, each visual element being indicative
of whether the ideal number of tables is above or below the actual
number of tables.
19. The method of claim 18, wherein the ideal number of open tables
is determined using a different optimal occupancy target for any
one or more of different price points and different game types.
20. The method of claim 18, wherein the game type is arranged in
the grid grouped by at least one time period, wherein the time
period comprises the plurality of time intervals.
21. The method of claim 20, wherein the game type is arranged in
the grid displayed in multiple instances, each instance being
associated with one of a plurality of time periods, wherein the
time period comprises the plurality of time intervals.
22. The method of claim 18, wherein the visual elements are varied
in at least one characteristic to indicate whether the ideal number
of open tables is above or below the actual number of open
tables.
23. The method of claim 22, wherein the characteristic comprises
any one or more of a numeric value, a colour, a shade, and a
shape.
24. The method of claim 18, further comprising, upon detecting
selection of one of the plurality of visual elements, displaying a
timeline comprising the time intervals, the timeline comprising, in
association with each time interval, a first visual element
indicative of the actual number of open tables during that time
interval, and a second visual element indicative of whether the
ideal number of open tables is above or below the actual number of
open tables.
25. The method of claim 24, wherein the actual number of open
tables and the ideal number of open tables are each aggregated over
a plurality of time periods, wherein each time period comprises the
plurality of time intervals.
26. The method of claim 25, further comprising enabling selection
or de-selection of at least one time period to be included in the
aggregation.
27. The method of claim 18, wherein the visual elements depict any
one or more of the actual number open tables, the ideal number of
open tables, and the actual number of open tables being above or
below the ideal number of open tables.
28. The method of claim 18, wherein the visual elements depict a
duration or frequency that the actual number of open tables is
above or below the ideal number of open tables.
29. The method of claim 18, wherein the visual elements depict a
numerical currency value that represents any one or more of an
improvement in profitability if the ideal number of tables had been
opened for each time interval, and a total currency amount of the
improvement in profitability if the ideal number of tables had been
opened for a plurality of time intervals.
30. The method of claim 18, further comprising enabling further
detail corresponding to a desired time interval to be displayed
upon detecting selection of a corresponding portion of the
grid.
31. The method of claim 30, wherein the further detail is displayed
using a second visual element in association with the desired time
interval, the further detail comprising any one or more of player
occupancy, number of players, number of open tables, and table
occupancy.
32. The method according to claim 30, wherein upon detecting
selection of the corresponding portion of the grid, the further
detail is displayed using a second visual element providing a floor
view comprising data associated with at least one open table in an
area of the gaming environment.
33. A computer readable medium comprising computer executable
instructions that when executed by a casino table game yield
management data processing system, perform operations comprising:
determining an actual number of open tables associated with a game
type for each of a plurality of time intervals; determining an
ideal number of open tables for the game type at each of the time
intervals; and displaying a plurality of visual elements in a grid
comparing the game type against the plurality of time intervals,
each visual element being indicative of whether the ideal number of
tables is above or below the actual number of tables.
34. A casino table game yield management data processing system
comprising the computer readable medium of claims 33.
35-50. (canceled)
Description
[0001] This application claims priority from U.S. Provisional
Patent Application No. 61/499,434 filed on Jun. 21, 2011, the
entire contents of which are incorporated herein by reference.
TECHNICAL FIELD
[0002] The following relates to systems and methods for processing
casino table games yield management data.
DESCRIPTION OF THE RELATED ART
[0003] Yield management (also known as "revenue management")
systems are used for determining the most profitable price for
products and services in response to market demands. Hotel room
pricing, airline tickets and car rentals are but some examples of
industries that use yield management data processing systems.
[0004] In general, the conditions that a service or product should
meet for yield management to be applicable are: (1) that there are
a fixed amount of resources available for sale; (2) that there is a
time limit to selling the resources, after which they may cease to
be of value; and (3) that different customers are willing to pay
different prices for using the same amount of resources.
[0005] In the context of a casino in which gaming tables are
operated, it has been suggested that yield management can be
applied, see "Table games revenue management: applying survival
analysis" by Clayton Peister published in Cornell Hotel and
Administration Quarterly, February 2007, and "Table Games: Optimal
Utilization", by Andrew MacDonald and Bill Eadington, published in
Global Gaming Business, volume 7, number 8, August, 2008.
[0006] These articles teach that occupancy of gaming tables affects
the number of plays per hour, namely that more players at a table
reduces the number of rounds per hour. While the number of bets
made per hour can still be greater at a full table than a table
that is half full, revenue can be adversely affected when players
betting smaller amounts play at a table with players betting larger
amounts. These articles teach that yield management analysis can be
used to gain insight into more profitable or optimal utilization of
table game resources in a casino.
[0007] Applicant's co-pending U.S. patent application Ser. No.
12/619,671 entitled "Casino Table Game Yield Management System" and
published as US 2011/0118007 describes a data processing system
that has a minimum bet change recommendation generator. The minimum
bet change recommendation generator receives casino table occupancy
and player betting data and generates recommendation data based on
casino game operations model data and business rule data. A timing
filter determines when recommendation data is to be presented to an
operator and a quantification filter calculates revenue value data
of implementing a minimum bet change and determining whether
recommendation data is to be presented to an operator.
[0008] Such a system enables casino managers to balance a variety
of player and house considerations when deciding on implementing a
gaming table betting minimum change. The above-noted co-pending
patent application thus recognizes that gaming table betting
minimum change recommendations based on yield management principles
are advantageously filtered to respect pre-established house rules
defining, for example, betting minimums, and minimum numbers of
tables operated at such betting minimums, and target occupancy
levels for each betting level. Gaming table betting minimum change
recommendations are also advantageously filtered to reduce either
the frequency or number of changes implemented, or to avoid changes
made in response to short-lived conditions. Moreover, the
above-noted patent application recognizes that it is advantageous
to calculate a financial value associated with gaming table betting
minimum change recommendations to only display recommendations that
are above a certain value threshold, or to help managers of casino
table games decide on implementing a gaming table betting minimum
change or to help managers of casino table games evaluate the
financial impact of recommendations that were not implemented.
[0009] It would be a further advantage to visualize yield
management data such as that calculated and provided in the system
described in US 2011/0118007.
[0010] In the context of a casino, table spread and game mix
statistics are also typically of interest to a casino manager.
Currently, table spread and game mix statistics are generated and
presented using static spreadsheets with some analysis. Current
casino managers also strive to ascertain whether or not player
segments for a game are being served, in order to improve
profitability. Existing tools available to casino managers also
lack the ability to provide interactive dashboards to measure or
visualize if there was an opportunity to price games differently
and further improve profitability.
[0011] Although static spreadsheets and other statistics exist or
can be generated for a particular casino, the casino industry
currently lacks a comprehensive yield management system, in
particular, one that can be used for current or real-time data or
on-demand analyses, let alone in a manner that can be understood
without specialized knowledge.
[0012] It is an object of the following to address the above-noted
disadvantages.
BRIEF DESCRIPTION OF THE DRAWINGS
[0013] Embodiments will now be described by way of example only
with reference to the appended drawings wherein:
[0014] FIG. 1 is a block diagram illustrating an example casino
management system in a networked system.
[0015] FIG. 2 is a block diagram illustrating an example of a
configuration for the casino management system of FIG. 1.
[0016] FIG. 3 is a screen shot of a daily overview UI.
[0017] FIG. 4 is a screen shot showing a pop-up displayed upon
detecting a mouse-over of the graph in FIG. 3.
[0018] FIG. 5 is a screen shot showing a pop-up displayed upon
detecting a mouse-over of a shaded segment in FIG. 3.
[0019] FIG. 6 is a screen shot showing a pop-up displayed upon
detecting a mouse-over of the upper bars in FIG. 3.
[0020] FIG. 7 is a screen shot showing a pop-up displayed upon
detecting a mouse-over of the lower bars in FIG. 3.
[0021] FIG. 8 is a screen shot showing a table view.
[0022] FIG. 9 is a screen shot of a trends view.
[0023] FIG. 10 is a screen shot showing a pop-up displayed upon
detecting a mouse-over of the graph in FIG. 9.
[0024] FIG. 11 is a screen shot showing a pop-up displayed upon
detecting a mouse-over of the player segment bars in FIG. 9.
[0025] FIG. 12 is a screen shot showing a pop-up displayed upon
detecting a mouse-over of the unmet demand bars in FIG. 9.
[0026] FIG. 13 is a screen shot showing an occupancy targets
window.
[0027] FIG. 14A is a flow chart showing a workflow for providing
the screen shots in FIGS. 3-8.
[0028] FIG. 14B is a flow chart showing a workflow for providing
the screen shots in FIGS. 9-12.
[0029] FIG. 15 is a screen shot showing table spread opportunities
in a game view.
[0030] FIG. 16 is a screen shot showing a pop-up displayed upon
detecting a mouse-over an under spread cell in FIG. 15.
[0031] FIG. 17 is a screen shot showing a pop-up displayed upon
detecting a mouse-over an over spread cell in FIG. 15.
[0032] FIG. 18 is a screen shot showing a pop-up displayed upon
detecting a mouse-over an at capacity cell in FIG. 15.
[0033] FIG. 19 is a screen shot showing table spread opportunities
in a day view.
[0034] FIG. 20 is a screen shot showing a settings window.
[0035] FIG. 21 is a screen shot showing betting minimums
opportunities in a game view.
[0036] FIG. 22 is a screen shot showing a pop-up displayed upon
detecting a mouse-over a too high occupancy cell in FIG. 21.
[0037] FIG. 23 is a screen shot showing a pop-up displayed upon
detecting a mouse-over a too low occupancy cell in FIG. 21.
[0038] FIG. 24 is a screen shot showing betting minimums
opportunities in a day view.
[0039] FIG. 25 is a screen shot showing unmet demand in a game
view.
[0040] FIG. 26 is a screen shot showing unmet demand in a day
view.
[0041] FIG. 27A is a flow chart showing a workflow for providing
the screen shots in FIGS. 15-18.
[0042] FIG. 27B is a flow chart showing a workflow for providing
the screen shots in FIGS. 22-23.
DETAILED DESCRIPTION
[0043] It will be appreciated that for simplicity and clarity of
illustration, where considered appropriate, reference numerals may
be repeated among the figures to indicate corresponding or
analogous elements. In addition, numerous specific details are set
forth in order to provide a thorough understanding of the example
embodiments described herein. However, it will be understood by
those of ordinary skill in the art that the example embodiments
described herein may be practised without these specific details.
In other instances, well-known methods, procedures and components
have not been described in detail so as not to obscure the example
embodiments described herein. Also, the description is not to be
considered as limiting the scope of the example embodiments
described herein.
[0044] It has been found that current table spread data can be
improved by providing intuitive data visualization, e.g., using
graphical indications of where the actual number of open tables is
significantly different from the ideal number of open tables. It
has also been found that useful table spread information can be
provided by enhancing interactivity and providing a drill down
ability in order to allow users to dig deeper into the data
provided beginning from high level and intuitive indications to raw
data and statistics. By providing flexibility in enabling "what if"
analyses and providing immediate results (e.g. by allowing days or
weeks to be selectively excluded in the analysis), a user can
explore various possibilities to better evaluate changes that could
be made to improve profitability. By aggregating this data to show
all of the opportunities in a single graphical visualization, an
overall picture is provided, enhancing the decision making
process.
[0045] It has also been found that there lacks an ability to
measure if there was a player segment that was not being served,
i.e., whether or not there is unmet or "censored" demand, which
could improve profitability if this segment was being served. A
system is therefore provided that graphically presents this
information. The following embodiments also enable unmet or
censored demand data to be aggregated over several weeks to
determine whether what is found is a trend, such that the operator
can act on that trend to remedy it. By presenting this aggregation
in an interactive manner, the user is also provided with the
ability to drill down to a detailed view.
[0046] The following embodiments also provide the ability to
measure if there was an opportunity to price games differently and
improve profitability. Provided is a graphical presentation of
which player segments have betting minimums opportunities, and
where the pricing can be adjusted. The betting minimums
opportunities can also be aggregated to determine whether what is
observed is a trend so that the operator can act on that trend to
remedy it. By presenting this aggregation in an interactive manner,
user is also provided with the ability to drill down to a detailed
view.
[0047] It has been recognized that managers of casino table games
often need to quickly determine which games and tables they need to
close in order to save labour, and which games and tables they need
to open in order to increase revenue. An interactive graphical
representation of this data combined with an ability to drill down
to the underlying data to verify trends makes it possible to find
opportunities to close games, open games and add or remove tables
to the gaming floor so as to improve profitability.
[0048] Displaying graphically how pricing of tables could be
changed is particularly useful so that managers can know where
opportunities exist to change pricing in order to improve
profitability. An ability to drill down to a floor view makes it
possible for the manager to verify the casino floor and visually
see how the players are seated on tables.
[0049] Displaying graphically the time periods when an unmet demand
exists helps the manager understand when this happens and for which
price points. This helps them decide if they need to open more
tables or add tables to meet the demand from this un-served player
segment, thus improve profitability. An ability to drill down to
the floor view makes it possible for the manager to verify the
casino floor and visually see how the players are seated at the
tables.
[0050] In some embodiments, the following system also provides a
grid to show each day of the week and each game to determine how
that game is spread. It is useful to have the ability to deselect
certain games from the analysis, or certain days from the analysis
to find out how the game is spread, compared to other games, or
other days of the same game. It is also useful to know which games
or time periods have the most opportunity to improve the spread by
having a visual element that emphasizes this.
[0051] It is also useful to have a grid to show each day of the
week and each game to determine how pricing can be changed. It is
useful to have the ability to deselect certain games from the
analysis, or certain days from the analysis to find out how the
pricing for a game can be changed, compared to other games, or
other days for the same game. It is useful to know which games or
time periods have the most opportunity to change pricing and
improve profitability by having a visual element that emphasizes
this.
[0052] It is also useful to have a grid to show each day of the
week and each game to determine where there are unmet customer
segments. It is useful to have the ability to deselect certain
games from the analysis, or certain days from the analysis to find
out how the unmet customer segments are compared to other games, or
other days for the same game. It is useful to know which games or
time periods have the most opportunity to open more tables to serve
the unmet customer segments and improve profitability by having a
visual element that emphasizes this.
[0053] In one aspect, the following provides a method, in a casino
table game yield management data processing system, of providing
table spread data for a casino environment. The method comprises
determining an actual number of open tables associated with a first
game type for each of a plurality of time intervals; determining an
ideal number of open tables at each of the time intervals;
displaying a timeline comprising the time intervals, the timeline
comprising, in association with each time interval, a first visual
element indicative of the actual number of open tables during that
time interval, and a second visual element indicative of whether
the ideal number of open tables is above or below the actual number
of open tables; and enabling further detail corresponding to a
desired time interval to be displayed upon detecting selection of a
corresponding portion of the timeline.
[0054] In another aspect, there is provided a computer readable
medium comprising computer executable instructions that when
executed by a casino table game yield management data processing
system, perform operations comprising: determining an actual number
of open tables associated with a first game type for each of a
plurality of time intervals; determining an ideal number of open
tables at each of the time intervals; displaying a timeline
comprising the time intervals, the timeline comprising, in
association with each time interval, a first visual element
indicative of the actual number of open tables during that time
interval, and a second visual element indicative of whether the
ideal number of open tables is above or below the actual number of
open tables; and enabling further detail corresponding to a desired
time interval to be displayed upon detecting selection of a
corresponding portion of the timeline.
[0055] In yet another aspect, there is provided a casino table game
yield management data processing system comprising the computer
readable medium above.
[0056] In yet another aspect, there is provided a method, in a
casino table game yield management data processing system, of
providing table spread data for a casino environment. The method
comprises determining an actual number of open tables associated
with a game type for each of a plurality of time intervals;
determining an ideal number of open tables for the game type at
each of the time intervals; and displaying a plurality of visual
elements in a grid comparing the game type against the plurality of
time intervals, each visual element being indicative of whether the
ideal number of tables is above or below the actual number of
tables.
[0057] In yet another aspect, there is provided a computer readable
medium comprising computer executable instructions that when
executed by a casino table game yield management data processing
system, perform operations comprising: determining an actual number
of open tables associated with a game type for each of a plurality
of time intervals; determining an ideal number of open tables for
the game type at each of the time intervals; and displaying a
plurality of visual elements in a grid comparing the game type
against the plurality of time intervals, each visual element being
indicative of whether the ideal number of tables is above or below
the actual number of tables.
[0058] In yet another aspect, there is provided a casino table game
yield management data processing system comprising the computer
readable medium above.
[0059] In yet another aspect, there is provided a method, in a
casino table game yield management data processing system, of
providing pricing data for open tables in a casino gaming
environment. The method comprises determining, for each of a
plurality of time intervals, that one or more open tables
associated with a game type should be priced differently than a
current pricing during that time interval; and displaying a
plurality of visual elements in a grid comparing the game type
against the plurality of time intervals, each visual element being
indicative of whether the one or more open tables should be priced
differently from the current pricing.
[0060] In yet another aspect, there is provided a computer readable
medium comprising computer executable instructions that when
executed by a casino table game yield management data processing
system, perform operations comprising: determining, for each of a
plurality of time intervals, that one or more open tables
associated with a game type should be priced differently than a
current pricing during that time interval; and displaying a
plurality of visual elements in a grid comparing the game type
against the plurality of time intervals, each visual element being
indicative of whether the one or more open tables should be priced
differently from the current pricing.
[0061] In yet another aspect, there is provided a casino table game
yield management data processing system comprising the computer
readable medium above.
[0062] In yet another aspect, there is provided a method, in a
casino table game yield management data processing system, of
providing pricing data for open tables in a casino gaming
environment. The method comprises determining, for each of a
plurality of time intervals, that there is unmet customer demand at
one or more price points associated with a game type during that
time interval; and displaying a plurality of visual elements in a
grid comparing the game type against the plurality of time
intervals, each visual element being indicative of unmet customer
demand.
[0063] Turning now to the figures, a yield management system 35 is
shown, which comprises a yield management server 30, which
processes data stored in a casino table player database 40 as shown
in FIG. 1. The processed data can be provided over a network 20 as
also shown in FIG. 1. The casino table player database 40 stores
information indexed by time, which can contain one or more of the
following: minimum bet (or price point) of the open tables, the
headcount at each of the open tables, and the average wager and
seat position of each player at the open table. The data in the
casino player database can come from a variety of sources and
several sources at once, including but not limited to an existing
casino player ratings system, manual data entry from a Tablet PC,
automated data collection technologies such as RFID embedded casino
chips or video analytics. The yield management server 30 processes
the data and produces various user interface (UI) dashboards that
can be viewed by a client 10 provided, e.g., at a gaming station
12. It can be appreciated that the dashboards can also be displayed
at any computer, such as one that is located in a casino manger or
executive's office and the gaming station 12 is shown in FIG. 1 for
illustrative purposes only.
[0064] FIG. 2 is a block diagram showing an example of a
configuration for the yield management data processing system 35
shown in FIG. 1. The casino table player database 40 is responsible
for capturing and storing all of the information necessary to
effectively analyze a casino game floor and improve the yield
management. This information may include the set of current open
tables and the players on these tables with their wagers. The
information can include one or more of the following: the table
minimum, the number of players at the tables, the number of spots
being played, and the wager at each spot.
[0065] A business rules editor and data store 50 is shown for
editing and storing business rules. The business rules correspond
to data that contains information regarding how the gaming floor
will be managed by a yield management analysis module 52. The
business rules can function by storing the information in a file
for easy access, and modifications by a user. Any basic text editor
can be sufficient to access, edit and save the pertinent data. This
file or data can be saved in a database indexed on the period of
time that this information was applicable for. This allows a
historical review of the casino state for any relevant time
period.
[0066] The business rule data can be accessed on demand by the
user, or by the yield management analysis module 52, to review,
modify or access its content. Once created or modified, casino game
operations model data 54 can be loaded automatically when the
system is reset or initialized, or can be manually uploaded to
override the current information.
[0067] The following describes sample information that a user can
provide for the business rules. It can be appreciated that the
following example is illustrative and should not be considered
exhaustive.
[0068] The user can specify optimal occupancy levels (or target
occupancy) for each price point. This is the desired average number
of players seated on a table game at a specific price point. The
target occupancy numbers are specified in the business rules and
are used to determine the ideal number of tables that need to be
opened for a given time period given the demand at that time
period.
[0069] The casino game operations model data 54 is a file store
that contains the representation of the casino floor and the data
relevant to the efficiency in operating these resources. The casino
game operations data functions by storing the information in a
content centered manner for easy access, and modifications by a
user. Any basic text editor is sufficient to access, edit and save
the pertinent data. This file or data can be saved in a database
indexed on the period of time that this information was applicable
for. This allows a historical review of the casino state for any
valid time period.
[0070] The casino game operations model data 54 may be accessed on
demand by the user, or by the yield management analysis module 52,
to review, modify or access its content. Once created or modified,
the casino game operations model data 54 can be loaded
automatically (or otherwise accessed) when the system is reset or
initialized, or can be manually uploaded to override the current
information.
[0071] Information that a user needs to provide for the casino game
operations are the list of tables that will be managed by the yield
management system 35, the number of spots available on each table,
the game type of each table and the location of the table relative
to a casino pit.
[0072] The purpose of the yield management analysis module 52 is to
analyze the data from the player ratings system (e.g. the casino
table player database 40) and use the casino game operations model
data 54 to determine, for each time period, the aggregated actual
number of open tables, the aggregated number of ideal open tables
based on the player demand, how pricing for the open tables can be
changed, and where there exists unmet demand for a particular game.
The yield management analysis module 52 also has the capability to
aggregate any of these data over several time periods.
[0073] A daily summary dashboard generator 56 is also provided, in
order to prepare a summary of an individual day for at least one
game in the casino. A graph can be generated for each game of the
casino showing the actual number of open tables at each hour, the
ideal number of open tables at each hour, and whether the actual
number of open tables is above or below the ideal number of open
tables during that hour. In addition to this, the daily summary
dashboard generator can also be used to show graphically how the
pricing at particular open tables could be changed, and where there
exists unmet demand for a particular price point.
[0074] A game trend dashboard generator 58 is provided in order to
prepare a summary of one game in the casino to show the trends for
the same game at the same time period for a user defined selection
of dates. A graph can be generated for the game in the casino for
the selected dates showing the aggregated actual number of open
tables during each hour, the aggregated ideal number of open tables
during each hour, a graphic showing the aggregated pricing changes
of open tables, and a graphic showing the aggregated unmet demand
for a particular price point. The aggregation can be an average,
median, mean, weighted average or percentile. The user can select
any time period for the analysis and can exclude days such as
holidays or special events that can skew the trends.
[0075] A casino trend dashboard generator 60 is provided to
aggregate all the data from all the games for a user defined
selection of dates in a grid. This module creates a grid that shows
each game and day against each hour of the day. Each element in the
grid can show whether the aggregated ideal number of tables is over
or under the aggregated actual number of tables for that day and
hour, the aggregated pricing changes for that game and hour, and
the aggregated unmet demand for that game an hour. The casino trend
dashboard generator 60 also allows the user to select/deselect
games to show in the grid, and arrange the grid by each game, or by
each day of the week, as will be shown in greater detail in the
screen shots described below.
[0076] A dashboard display unit 62 is also provided to displays the
dashboards generated by the daily summary dashboard generator 56,
the game trend dashboard generator 58, and the casino trend
dashboard generator 60. The dashboard display unit 62 sends the
user selected information relevant to each of the dashboard
generators 56, 58, 60, so that a particular dashboard generator 56,
58, 60 displays relevant information.
[0077] FIG. 3 shows a daily overview summary UI 70. The daily
overview summary UI 70 includes, for one or more games, a first
visual element 72 associated with each of a plurality of intervals,
e.g. a portion of a line graph as illustrated, that shows the
actual number of open tables during that time interval, and a
second visual element 74 that is indicative of whether the actual
number of open tables is above or below an ideal number of tables
during that time interval. From the daily overview summary UI 70,
the user can pick any day to populate the summary for each game in
the casino. A chart is populated for each game in the casino, and
the actual number of open tables and ideal number of open tables
are plotted in each chart. For the purpose of this description, we
use the Blackjack Games in the casino shown. An indication of the
maximum capacity of each game 76 is also shown on the chart so that
the user can quickly determine where they have capacity to open
more games. The actual number of open tables are sampled at each
time period, in this example, on the hour. The ideal number of open
tables are determined from the average player supply for that hour
in the casino and the optimal or target occupancies for each price
point. The ideal number of tables for each price point are
aggregated to determine the actual number of tables to open. The
second visual element 74 in this example comprises shading of the
chart, which changes for time periods when the ideal and actual
number of tables are significantly different, so as to draw the
attention of the user to these areas. The actual open and ideal
open tables for the each game show the operator how they were
spread for the day, and time periods where they were significantly
over or under the actual number of open tables. The upper
horizontal bars 78 above each chart show where the pricing of the
open tables can be changed and the length of the bars indicate how
long this lasted at the indicated price point. These bars help the
operator determine how the open tables pricing was managed for the
day, and how many changes the system 35 suggests. The lower
horizontal bars 80 below each chart show where there exists unmet
demand, and the numbers in the bars 82 show for which price points
the unmet demand exists. The length of the bar 80 shows for how
long the unmet demand lasted. This helps the operator determine
where there exists opportunity to open more tables and capture
un-served player segments the indicated price points. The data
integrity 84 indicates the quality of the casino table player
database, in this example, broken down by each eight hour shift of
the casino. This helps the user determine how accurate or reliable
their data is for each shift. The data freshness 86 shows the users
who worked in each shift, and how the compared with the other users
in the same shift. A different color can be used to highlight users
who need improvement in collecting information for the casino table
player data store 40. This helps the operator quickly determine the
users to need to improve on data collection.
[0078] FIG. 4 shows an example of a pop-up 88 displayed when the
user moves their mouse over any hour on the actual number of tables
open graph, i.e. in association with a particular first visual
element 72. The popup 88 shows the actual number of open tables for
that hour, the number of open tables of that game type in each pit
and the number of tables that the casino is over or under the ideal
number of tables for that hour. In this example, at 14:00, the
casino had 13 tables open in that hour, and was 4 under the ideal
number of tables for that hour. This popup 88 helps the operator
quickly determine where the open tables were located. If the user
clicks on the pop-up 88, it takes them to a floor view UI 110 (see
FIG. 8).
[0079] FIG. 5 shows an example of a pop-up 90 displayed if the user
moves their mouse over any hour on the ideal number of tables open
graph, i.e. in association with a particular one of the second
visual elements 74, e.g. the shading for a particular hour
interval. The popup 90 shown in FIG. 5 shows the ideal number of
open tables for that hour and the number of tables that the casino
is over or under the ideal number of tables for that hour. In this
example, at 14:00, the casino required 17 tables open in that hour,
and was 4 under the ideal number of tables for that hour. A chart
of each price point, showing the average demand for that hour is
also shown. A table showing the number of players, the player
occupancy, the number of open tables and the table occupancy is
shown for each price point. The total is also shown as the last
row. This table gives the user a summary of all the price points
for that hour and that game. If the user clicks on this item, it
takes them to the floor view UI 110 (see FIG. 8) at this time.
[0080] FIG. 6 shows an example of a pop-up 92 displayed if the user
moves their mouse over any of the upper horizontal bars 78 that
show how the pricing could be changed for a particular price point.
The popup 92 indicates a reason why the system suggested converting
tables of that game type to the indicated price point. The
description text 94 also shows how long the suggested change
lasted. In addition to this, if available, the information on each
user 96 who was managing those tables is shown, and their action if
the suggestion was sent out to them at the time it happened. The
suggested options to change the price of another open table to the
current price point are also shown, with a graphic of the open
table(s) 98. If the user clicks on this item, it takes them to the
floor view UI 110 at this time (see FIG. 8).
[0081] FIG. 7 shows an example of a popup 100 displayed if the user
moves their mouse over any of the lower horizontal bars 80 that
show where there exists unmet demand. The popup 100 shows which
price points have an unmet demand, and how long this unmet demand
lasted for. The unmet demand is an indication that even if there
are sufficient tables open for the current players, there may be
players who are willing to play at a lower price point, which is
profitable for the casino, but the casino does not have any tables
that that price point to serve those players. If the user clicks on
this item, it takes them to the floor view UI 110 at this time (see
FIG. 8).
[0082] Returning to FIG. 3, by clicking at any point in the chart,
the system 35 opens the floor view UI 110, showing the open tables
112 at that time at the casino, and how the players are seated on
the tables 112. FIG. 8 shows a floor view UI 110 for 12:58 at this
casino for the open Blackjack Games. Each open table 112 shows the
price point (or minimum bet) of the table, how many spots are
occupied, and fills it in with the average wager at each occupied
spot. A list of price change suggestions or recommendations 114
applicable for that hour are also shown on this page. The floor
view UI 110 is an indication of what the floor looks like at that
time, and gives the operator the ability to verify and validate
whether the ideal number of open tables is required, or if a
pricing change is justified, or whether unmet demand really exists
at that time.
[0083] FIG. 9 shows a game trend summary UI 116 for an individual
game at the casino, which may be displayed by selecting the trends
button 87 shown in FIG. 3. The game trend summary UI 116 provides
an analysis of several days of data and shows the information in a
single chart 118. The user can pick any game and any day to analyze
the charts 118 using a day selection portion 120. The user can also
pick any other day to include or exclude from the analysis. This
gives the operator the ability to exclude days from the analysis or
compare different days in the same chart. In this example, 6
Saturdays are combined in to one game trend chart, and the user can
quickly determine where the ideal number of tables is significantly
different from the actual number of tables, where recurring pricing
changes suggestions occur, and where recurring unmet demand
opportunities exist. The single summary chart gives a quick
snapshot of where there are opportunities to improve
profitability.
[0084] FIG. 10 shows an example of a pop-up 122 displayed if the
user moves their mouse over any hour on the aggregated graph 118.
The popup 122 shows the aggregated actual number of open tables for
that hour, the aggregated ideal number of tables to open for the
hour, the number of tables that the casino is over or under the
ideal number of tables for that hour, and the minimum number of
ideal tables based on the demand. In this example, at 14:00, the
casino had 16 tables open aggregated as an average for that hour,
and was 2 under the ideal number of tables for that hour since
there were 18 tables aggregated on average suggested ideally, and a
minimum of 17 tables aggregated on average ideally open for the
hour. This popup helps the operator quickly determine the trends
for that hour of the day, compared to other selected days of the
same game.
[0085] FIG. 11 shows an example of a pop-up 124 displayed if the
user moves their mouse over the aggregated suggested pricing
changes 126 at the indicated price point. Shading is used to
determine the frequency of the occurrence of the suggested price
change, and the length of the bar indicates the duration of the
suggested price change. The popup 124 shows the price point that
the system 35 is suggesting tables to be converted to, the actual
duration of the suggestion, and optionally, the exact dates from
the selected dates that had the issue. A threshold can be applied
to hide any pricing changes that didn't occur in that hour for at
least a certain number of dates from the selected dates.
[0086] FIG. 12 shows an example of a pop-up 128 displayed if the
user moves their mouse over the aggregated unmet player demand 130
at the indicated price points. Shading is used to determine the
frequency or severity of the occurrence of the unment demand, and
the length of the bar indicates the duration of the unment demand.
The popup 128 shows the price point that the system indicates that
an unment demand exists, the actual duration of the unmet demand,
and optionally, the exact dates from the selected dates that had
the issue. A threshold can be applied to hide any unment demand
that didn't happen in that hour for at least a certain number of
days from the selected dates.
[0087] FIG. 13 shows an example of an optimal or target occupancies
pop-up 132, when the user selects to view the optimal or target
occupancies button 134. The information in the pop-up 132 gives the
user an idea of what optimal player occupancies were used for each
price point when determining the ideal number of tables.
[0088] FIG. 14A illustrates an example of a set of computer
executable operations that may be executed in navigating between
the views shown in FIGS. 3 through 8. After detecting selection of
the daily overview at 136, the daily overview UI 70 is displayed at
138. While in the daily overview UI 70, several pop-ups may be
displayed as discussed above. At 140, the system 35 determines if
the user has performed a mouse over of a point on the graph 72. If
so, the pop-up 88 is displayed at 142 and if not, the system
continues to A. If the pop-up 88 is displayed, the system 35 then
determines at 144 if the pop-up 88 has been selected. If so, the
floor view 110 is displayed at 146 and if not, the system 35
continues to A. Similar workflow may be provided for detecting a
mouse over of the shaded areas in each time interval at 148-154,
for the upper bars 78 at 156-162, and for the lower bars 80 at
164-170.
[0089] FIG. 14B illustrates an example of a set of computer
executable operations that may be executed in navigating between
the views shown in FIGS. 9 through 12. At 172 the system 35 detects
selection of the trends button 87 and displays the trends UI 116 at
174. While in the trends UI 116, several pop-ups may be displayed
as discussed above. At 176, the system 35 determines if the user
has performed a mouse over of the graph 118. If so, the pop-up 122
is displayed at 178 and if not, the system continues to A. Similar
workflow may be provided for detecting a mouse over of the upper
bars 126 at 180-182, for the lower bars 130 at 184-186, and for
selection of the occupancy targets button 134 at 188-190.
[0090] FIG. 15 shows an example of a casino trend summary UI 200,
which is aggregated for all games offered in the casino and every
day of the week. In FIG. 15, the Game View tab 202 is selected
which shows each game, and any recurring table spread opportunities
for any day of the week. These opportunities are aggregated over a
time period selected by the user, for a set of games also selected
by the user. The capacity of the games is shown to give the user an
idea of how many tables are present in the casino for that game
type, and each column in the grid 204 is an hour in this example.
There are three types of opportunities shown in this grid 204.
[0091] (1) Under spread opportunities: These are opportunities
where the casino needed to open more games, because the aggregated
ideal number of tables is significantly higher than the aggregated
actual number of tables for the selected time period. In FIG. 15,
these opportunities are shown in blue, which is reflected with a
corresponding shade in the drawings (for example the cells
containing 1 in the lower leftmost corner of grid 204).
[0092] (2) Overspread opportunities: These are opportunities where
the casino needed to close tables, because the aggregated ideal
number of tables is significantly lower than the aggregated actual
number of tables for the selected time period. In FIG. 15, these
opportunities are shown in orange, which is reflected with a
corresponding shade in the drawings (for example see cells
containing a 2 in the upper leftmost corner of the grid 204).
[0093] (3) Capacity opportunities: These are opportunities where
the casino needed to open more games, because there is sufficient
demand to open more tables of the game type, but there is no
physical capacity on the casino floor to add this game. In FIG. 15,
these opportunities are shown in grey, which is reflected with a
different corresponding shade in the drawings when compared to
those in orange (for example see cells containing a 2 and along SP
games on Saturday in the grid 204). The advantage of presenting all
the opportunities in this game view grid 204 is so that the user
can immediately see how each game in the casino is performing, and
which games have the most opportunity to improve the table spread.
The user can also quickly determine where there is a recurring
capacity issues for every day of the week, and whether they should
add more games of this game type on the casino floor to meet the
demand. If there is no opportunity to improve the table spread,
then the row for the day and game can be omitted, for example there
is no row for Mondays for the Baccarat game because there doesn't
exist any opportunity to improve spread.
[0094] FIG. 16 shows an example of a pop-up 206 displayed if the
user moves their mouse over any of the elements that indicate that
the game is underspread. The number inside the cell shows how many
tables this game is underspread by. In FIG. 16, the SP Games on
Fridays are underspread as shown at 3 pm, and the popup 206
indicates how long this opportunity has lasted, in this example
from 12 pm-3 pm. At the selected hour, it is underspread by 2
tables, and there were 2 aggregated actual tables open, and the
system suggested having 4 ideal tables open. For convenience, the
game type name and the capacity is also shown in the popup. This
popup 206 gives the user an immediate view of how many tables were
actually open at the selected time, and is easy to visualize. If
the user clicks on this item, it takes them to the game trend
summary UI 116 at this time (see FIG. 9) for the particular game
and days included in the analysis.
[0095] FIG. 17 shows an example of a pop-up 208 displayed if the
user moves their mouse over any of the elements that indicate that
the game is overspread. The number inside the cell shows how many
tables this game is overspread by. In FIG. 17, the Baccarat games
on Wednesdays are overspread as shown at 10 pm, and the popup 208
indicates how long this opportunity has lasted, in this example
from 7 am-11 am. At the selected hour, it is overspread by 2
tables, and there were 4 aggregated actual tables open, and the
system 35 suggested having 2 ideal tables open. For convenience,
the game type name and the capacity is also shown in the popup 208.
If the user clicks on this item, it takes them to the game trend
summary UI 116 at this time (see FIG. 9) for the particular game
and days included in the analysis.
[0096] FIG. 18 shows an example of a pop-up 210 displayed if the
user moves their mouse over any of the elements that indicate that
the game requires additional capacity. The number inside the cell
shows how many tables this game needs additional capacity. In FIG.
18, the SP games on Saturdays need additional capacity as shown at
5 pm, and the popup 210 indicates how long this opportunity has
lasted, in this example from 5 pm-7 pm. At the selected hour, the
game needs additional capacity of 2 tables, and there were 5
aggregated actual tables open, and the system suggested having 7
ideal tables open. The capacity for this game at the casino is 5
tables. For convenience, the game type name and the capacity is
also shown in the popup 210. If the user clicks on this item, it
takes them to the game trend summary UI 116 at this time (see FIG.
9) for the particular game and days included in the analysis.
[0097] FIG. 19 shows an example of selection of a day view tab 212,
which represents the same data in the grid 204 as the game view,
but this time arranged by each day of the week, rather than each
game. This view 212 is useful to give the operator an indication of
how each hour of each day is performing. It also can be used to
allocate labour from one game that is overspread to another game
that is underspread. For example, the casino can close a baccarat
game that is overspread from 7 am-10 am on Saturdays, and allocated
the dealer to Pai Gow Tiles at the same time. This view 212 enables
the user to find opportunities where the staff can be
reallocated.
[0098] FIG. 20 shows a settings window 214 which appears when a
"settings" button 216 is clicked. The settings window 214 enables
the user to analyze only certain games, certain areas, and include
or exclude additional weeks of data to summarize in the grid 204.
This helps filter out weeks that may have had special events which
could skew the results, or select only certain games for
analysis.
[0099] FIG. 21 shows a grid 204' with aggregated betting minimums
opportunities 220. Each row is for a single price point and game at
the casino. The game view 222 shows all the opportunities for each
game type, and where the system 35 suggests to convert additional
tables to the indicated price point. The number inside each cell
indicates how many weeks the issue has been recurring for, and
lower values can be filtered out to exclude on this page so as to
only focus on the pricing changes that occur most frequently. The
two types of betting minimums opportunities shown are:
[0100] (1) High Occupancy opportunities: These indicate where the
players are experiencing higher than optimal occupancy and to
convert some tables to the current minimum.
[0101] (2) Low Occupancy opportunities: These indicate where the
players are experiencing lower than optimal occupancy, and to
convert some games to the current minimum to entice other players
to join the game. This view gives the user a very clear ideal of
how the pricing can be changed to improve profitability for each
game type, and when this happens during the week.
[0102] FIG. 22 shows an example of a pop-up 224 displayed if the
user moves their mouse over any of the elements that indicate that
the pricing needs to be changed due to the games being at high
occupancy. The number inside the cell shows the frequency of this
occurrence in the user selected weeks. In FIG. 22, the Baccarat
Games at the $50 price point are at high occupancy and this has
been recurring for 6 weeks as indicated in the cell. The popup
indicates this opportunity has lasted from 12 pm-8 pm. At the
selected hour, 2 pm, the system 35 suggested to convert more games
to the $50 price point due to a high occupancy. Each prior date in
the past where this change was suggested is shown in the popup 224.
This popup 224 gives the user immediate information on the exact
opportunity and when exactly in the past it occurred. If the user
clicks on this item, it takes them to the game trend summary UI 116
at this time (see FIG. 9) for the particular game and days included
in the analysis.
[0103] FIG. 23 shows an example of a pop-up 226 displayed if the
user moves their mouse over any of the elements that indicate that
the pricing needs to be changed due to the games being at low
occupancy. The number inside the cell shows the frequency of this
occurrence in the user selected weeks. In FIG. 23, the Roulette
Games at are at low occupancy and this has been recurring for 4
weeks as indicated in the cell. The popup 226 indicates this
opportunity has lasted from 4 am-10 am. At the selected hour, 7 pm,
the system suggested to convert more games to the $10 price point
due to a low occupancy. Each prior date in the past where this
change was suggested is shown in the popup 226, in this case the 4
weeks. If the user clicks on this item, it takes them to the game
trend summary UI 116 at this time (see FIG. 9) for the particular
game and days included in the analysis.
[0104] FIG. 24 shows an example of the day view tab 228 for betting
minimums opportunities 220, which represents the same data in the
grid 204' as the game view from FIG. 21, but this time arranged by
each day of the week, rather than each game. This view 228 is
useful to give the operator an indication of how each hour of each
day is performing and which days have the most opportunity to
change pricing in order to improve profitability.
[0105] FIG. 25 shows a grid 234 with a game view 230 for aggregated
unmet demand opportunities 232. Each row is for a single price
point and game at the casino where there exists unmet demand. The
game view 230 shows all the opportunities for each game type, and
where the system 35 suggests to open additional tables at the
indicated price point. The number inside each cell indicates how
many weeks the issue has been recurring for, and lower values can
be filtered out to exclude on this page so as to only focus on the
pricing changes that occur most frequently. This view 230 gives the
user a very clear idea of when the unmet demand occurs for each
game type, and decide whether to open additional games at that
time.
[0106] FIG. 26 shows an example of a day view 236, which represents
the same data in the grid 234 as the game view from FIG. 25, but
this time arranged by each day of the week, rather than each game.
This view 236 is useful to give the operator an indication of how
each hour of each day is performing and which days have the most
opportunity to open tables and serve the unment demand at the
indicated price points in order to improve profitability.
[0107] FIG. 27A illustrates an example of a set of computer
executable operations that may be executed in navigating between
the views shown in FIGS. 15 through 18. At 240 the system 35
detects selection of the table spreads opportunities UI 200 and
displays the table spreads opportunities UI 120 at 242 (e.g. game
view 202 as shown in FIG. 15 and used in the example shown in FIG.
27A). While in the table spread opportunities UI 200, several
pop-ups may be displayed as discussed above. At 244, the system 35
determines if the user has performed a mouse over of an under
spread cell. If so, the pop-up 206 is displayed at 246. If the
pop-up 206 is displayed, the system 35 then determines at 258 if
the pop-up 206 has been selected. If so, the game trend UI 116 is
displayed at 250 and if not, the system 35 continues to A. Similar
workflow may be provided for detecting a mouse over of an over
spread cell at 252-258, and a cell at capacity at 2602-268.
[0108] FIG. 27B illustrates an example of a set of computer
executable operations that may be executed in navigating between
the views shown in FIGS. 21 through 23. At 270 the system 35
detects selection of the betting minimums opportunities UI 220 and
displays the table spreads opportunities UI 220 at 2728 (e.g. game
view 222 as shown in FIG. 21 and used in the example shown in FIG.
27B). While in the betting minimums opportunities UI 220, several
pop-ups may be displayed as discussed above. At 274, the system 35
determines if the user has performed a mouse over of a cell showing
an occupancy that is too high. If so, the pop-up 224 for that cell
is displayed at 276. If the pop-up 224 is displayed, the system 35
then determines at 278 if the pop-up 224 has been selected. If so,
the game trend UI 116 is displayed at 280 and if not, the system 35
returns to display of the UI 220. Similar workflow may be provided
for detecting a mouse over of cell showing an occupancy that is too
low at 282-288.
[0109] It will be appreciated that any module or component
exemplified herein that executes instructions may include or
otherwise have access to computer readable media such as storage
media, computer storage media, or data storage devices (removable
and/or non-removable) such as, for example, magnetic disks, optical
disks, or tape. Computer storage media may include volatile and
non-volatile, removable and non-removable media implemented in any
method or technology for storage of information, such as computer
readable instructions, data structures, program modules, or other
data. Examples of computer storage media include RAM, ROM, EEPROM,
flash memory or other memory technology, CD-ROM, digital versatile
disks (DVD) or other optical storage, magnetic cassettes, magnetic
tape, magnetic disk storage or other magnetic storage devices, or
any other medium which can be used to store the desired information
and which can be accessed by an application, module, or both. Any
such computer storage media may be part of the system 35, client
20, gaming station 12, etc., or accessible or connectable thereto.
Any application or module herein described may be implemented using
computer readable/executable instructions that may be stored or
otherwise held by such computer readable media.
[0110] It will be appreciated that the example embodiments and
corresponding diagrams used herein are for illustrative purposes
only. Different configurations and terminology can be used without
departing from the principles expressed herein. For instance,
components and modules can be added, deleted, modified, or arranged
with differing connections without departing from these
principles.
[0111] The steps or operations in the flow charts and diagrams
described herein are just for example. There may be many variations
to these steps or operations without departing from the spirit of
the invention or inventions. For instance, the steps may be
performed in a differing order, or steps may be added, deleted, or
modified.
[0112] Although the above principles have been described with
reference to certain specific example embodiments, various
modifications thereof will be apparent to those skilled in the art
as outlined in the appended claims.
* * * * *