US20140162742A1

US20140162742A1 - Fantasy sports draft system

Info

Publication number: US20140162742A1
Application number: US13/712,403
Authority: US
Inventors: Tom Dempsey
Original assignee: Individual
Current assignee: Individual
Priority date: 2012-12-12
Filing date: 2012-12-12
Publication date: 2014-06-12

Abstract

A system to provide a recommendation of a player to select during a fantasy football draft. The system determines a projected competitiveness of a user's team, and determines what available player best increases their competitiveness. The determination may be based on a number of factors such as best available player, addressing statistical weaknesses of a team, players having the biggest statistical differential over other available players, positional scarcity, and the like.

Description

BACKGROUND OF THE INVENTION

1. Field of the Invention
The present invention relates generally to fantasy sports. More particularly the present invention relates to a fantasy sports system that facilitates drafting and makes recommendations of players to select.
2. Description of Related Art
Fantasy sports games are a common pastime and hobby enjoyed by millions of people world wide. By assigning points to various statistics, a particular player earns points for a team. The goal being to score the most points based on a team of players' statistics. Competition generally runs high as user's seek to beat their opponents. Users may play for pride, bragging rights, and often money. In some instances, wagers are made on fantasy teams, such as a league “buy-in” and bets on outcomes of particular match ups.
Because of the competitive nature and intensity of many fantasy sports users and “leagues” it is desirable to get any edge possible. Users often perform a great deal of research, consult “experts,” discuss with friends, and the like, to get such an edge. This research may be performed before the season in preparation for when an initial team is selected (the “draft”). This research may also be ongoing throughout the season to stay up to date on current trends, injuries, player development, and the like.
For most users, the most important part of setting up a strong team is the draft. This is where core players are selected, and, assuming things go as predicted, where winning teams are built. As such, strong research before the draft is vital to building a good team. However, during the draft there are many variables that are difficult to account for. One particularly difficult variable to account for is the player selections of the other users in the league. A user must consider not only the best player available, but the best player available for their team's specific needs, to address potential weaknesses. Often, these weaknesses may be difficult to see, and equally as difficult to remedy, during fast paced drafting.
Therefore, what is needed is a system that takes many factors into consideration as a fantasy sports draft progresses in order to provide a recommendation about the best player to select.

SUMMARY OF THE INVENTION

The subject matter of this application may involve, in some cases, interrelated products, alternative solutions to a particular problem, and/or a plurality of different uses of a single system or article.
In one aspect, a method of providing a recommended pick in a fantasy draft is provided. The method is computerized, and may start by receiving league settings. Once the settings are received, the computer may provide a default value or values for an unfilled roster spot. The values for each empty roster spot may represent expected or average statistics for the roster spot of the particular position. As the empty roster spots are filled, the default values are replaced with the projected statistics of the player filling the roster spot. As the rosters begin to be filled, the computerized system may compare a user's team to the teams throughout the league, and may calculate a competitive landscape based on this comparison. Accordingly, the system may analyze available players and project their input on the team's competitive landscape were they to be drafted. Based on this analysis the computerized system may provide a recommended pick for the user that provides the most favorable projected enhancement to the user's team.
In another aspect, a method of calculating a value of a player during a fantasy sports draft is provided. The method begins by receiving league settings prior to the draft, and beginning the draft. As the draft progresses, a computerized system calculates a competitive landscape of a roster of each of a plurality of teams based on projected statistics of each player on a roster of each of the plurality of teams. For unused roster spots, the system projects a default value for the position. Once the competitive landscape is determined, the computer determines a numerical value for an available player which represents the projected statistics of the player and the impact he may have on aiding the user's team. The player having the highest numerical value is displayed to the user as the recommended pick. Finally, the competitive landscape is re-evaluated at least after each round of drafting and, in one embodiment, after each draft pick.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 provides a flow chart of an embodiment of the system contemplated herein.

FIG. 2 provides a view of an embodiment of a player recommendation output provided by the system contemplated herein.

FIG. 3 provides a flow chart showing inputs considered when providing a player recommendation.

FIG. 4 provides a flow chart of an embodiment of the system contemplated herein.

DETAILED DESCRIPTION

The detailed description set forth below in connection with the appended drawings is intended as a description of presently preferred embodiments of the invention and does not represent the only forms in which the present invention may be constructed and/or utilized. The description sets forth the functions and the sequence of steps for constructing and operating the invention in connection with the illustrated embodiments.
Generally, the present invention concerns a system that analyzes a user's team during a fantasy draft, identifying the best players available to strengthen the team, based on a number of factors. Preferably, a key factor considered by the system is competitiveness of the user's team roster in relation to the rest of the team's rosters in the league.
This system may be implemented in a number of different platforms and embodiments. For example, in varying embodiments, the system may be implemented on any computing device, such as a mobile device, tablet computer, cloud or server based system, a desktop or laptop computer, and the like.
Further, the system may be implemented in any number of ways to analyze a fantasy draft. In one embodiment, the system may be integrated into a fantasy sports system and accessible through a computerized drafting system. In this embodiment, the system may be a special feature of the draft system, and may be activated or deactivated. In another embodiment, the system may be an “add-on” or “plug-in” type of application that may be configured to log into a fantasy sports system such as the league settings or draft, and automatically extract data from the draft system while remaining a separate application. In this way a user could use the system externally from a draft interface while the information from the draft is automatically extracted. In yet another embodiment, the system may be configured to receive manual input of draft status and related information such as statistics, league rules, and the like. In this embodiment, a user may follow the draft and manually input player selections by each team. The system generally is configured to be able to be run in a background of a computing interface, and capable of being hidden and brought up easily by, for example, a click of a mouse or finger swipe.
The term user as used herein is intended to refer to a user of the system described herein. The user being a team owner in a fantasy sports league.
The term player as used herein refers to a player in a sports league who accumulates statistics based on their game play. The player may be selected for a user's fantasy roster, and the player's statistics are used to accumulate points for the user's team.
The term competitive landscape as used herein refers to a user's team's competitiveness compared to the other teams in the league. The competitive landscape may be expressed in any way capable of indicating the competitiveness of a user's team. Examples of competitive landscape expression may be projected wins and losses, projected winning percentage, projected total points, rankings of projections in varying statistical categories, ranking of projected overall statistics, and the like.
Initially, the system may be set up to record all settings relating to the draft such as league scoring, keeper selections (if applicable), draft type and position, player rank (either automatic or manually selected by a user), projected statistics, and the like. These settings may be manually inputted by a user in one embodiment. In another embodiment, the system may automatically retrieve the settings by logging into a fantasy draft system, and/or accessing a related database.
During the draft, the system may calculate a user's team's projected competitive landscape based on the team's roster and the rosters of the other teams in the league. This calculation may happen continuously, or may be recalculated at the end of each draft round. This calculation may include calculating end-of-season outcomes such as a user's wins and losses based on league schedule, calculating a user's projected total points, and/or projected overall statistics depending on varying embodiments and league settings. These calculations may be used to identify the needs of a user's team, and in turn the system may return a suggested player selection to best address the identified needs. In one embodiment, to accommodate for unfilled draft positions, the system may assume an expected level of statistics for that position based on, for example, average positional statistics across a particular sports league from the last year (or other similar time frame, last two years, last five years, and the like).
Moreover, during the draft, in this embodiment, once a player is selected, the system may update its projection based on the selected player's projected statistical contributions. These contributions may be based on any number of factors including historical statistics, expected contributions, projections from “experts,” news regarding the player and team, system automatic pre-rankings, and the like.
As noted above, the system is configured to interpret and calculate projected competitiveness of a team's roster as the draft progresses, and provide a suggested player pick for a team based on this data. Further, win-loss projections and/or overall projected points may be calculated for each team in the league, not just the system user's team.
The system may utilize one or a plurality of algorithms to interpret and calculate projected competitiveness referred to herein as a “competition algorithm.” These competition algorithms may be based on the projected statistics of the players making up each team's roster, stage in the draft, league settings, and the like.
The system may further utilize one or a plurality of algorithms to identify the best player available based on the projected competitiveness. These algorithms may be referred to herein as “player algorithms.”
The player algorithms may be based on any number of factors including, but not limited to specific statistical weaknesses of the team, stage of the draft, draft strategy, projected total season points, projected week to week points of a team, both statistically and positionally, biggest differential between players (either at a position or overall) to give a user a larger statistical differential from one player to another, position scarcity, consistency, and the like.
In certain leagues called “auction leagues” where players are auctioned with a given budget, a player algorithm may further consider an available remaining budget of a user.
The recalculation of the player and competitiveness algorithms may be calculated at the end of each draft round, or may be calculated continuously after each pick is made.
In one embodiment, the player algorithm or algorithms may output a “z-score” based on calculated factors noted above. The player having the highest “z-score” will be recommended. Further the player algorithm or algorithms may calculate z-scores for a plurality of players, each available player having their own z-score based on their projections and/or conditions of the draft.
In one embodiment, these factors may be given default weight as determined by the system. In another embodiment, the user may be able to adjust the weighting from the default value. In a further embodiment, a user may be able to make selections to adjust the weighting of factors considered by the algorithm. For example, a user may select a “best available” option, a “biggest differential” option, or a “position scarcity” option.
In an embodiment wherein the user selects a best available option, the player algorithm will weight overall projected statistics higher than other factors.
In an embodiment wherein the user selects a biggest differential option, the player algorithm will identify statistics of a players team that are particularly weak, and recommend a player that helps the user most in those areas. The player algorithm should also consider strong overall players, however. In one embodiment, the system may identify players with high scores in the particular weak statistic, then the system may sum and average their remaining projected statistics. Finally, the system may provide a player that has a high differential to the weak statistics, who also has the highest average scoring at the remaining statistical areas.
In an embodiment wherein the user selects a position scarcity option, the player algorithm will highly weight players with large statistical differentials compared to other players at their position. These players will be identified and, based on user team needs, recommended. In a further embodiment, a user may be able to view specific positions to identify positional differentials specifically.
The player and competitiveness algorithm or algorithms may provide a user with one or a plurality of outputs. As noted, a key output may be the suggested draft pick based on considered factors. In further embodiments, the system may provide additional outputs such as competitiveness rank, a list of ranked suggested players, and supporting evidence for the proposed selection, among other things. These specifics may include projected total points, with weekly and seasonal options, projected wins and losses and overall record (if applicable), projected overall rank, projected winning percentage, and the like. Further, the system may provide a detailed post-draft summary once the draft is completed, as well as a detailed statistical output summarizing the draft, players, and picks. This detailed statistical output may further identify weaknesses of a user's team that may be addressed through waiver additions or trades.
In a further embodiment, the system may, in addition to providing a top suggested pick, provide rankings of available players based on the same player algorithm/s.
In one embodiment, this ranking may be based on calculated z-score. For example, the system may provide the top five suggested picks, top 10, top 20, and so on. This embodiment may allow a user to see more than just the selected pick, and make a decision between the top few picks. In yet another embodiment, in addition to providing a top suggested pick, the system may provide rankings of available players based on other algorithms with different weighting.
In yet another embodiment, the system may provide top picks for each category of factors considered. For example, in one embodiment, the system may provide three player suggestions: a best overall player, a best available player based on position scarcity, and a player providing the biggest differential between his projected statistics and the next closest player at the position. In a further embodiment, an ordered list of players may be provided for each factor considered. For example: the top ten best overall players may be presented, along with the top ten players based on position scarcity, and top ten players based on biggest differential.
While the system is generally used to provide passive suggestions for player picks during a draft, in one embodiment, the system may be configured to automatically draft its recommended player. This embodiment may act as an advanced automated draft system, allowing a user to be completely hands-off.
Turning now to FIG. 1, a flow chart of an embodiment of the system is provided. The flow chart begins with the initialization of the draft environment. This involves inputting league settings into a computerized system so that it receives the league settings. Further, the initialization may involve providing default statistical values for empty roster spots, and/or using the system to log into the fantasy draft system, which may (or may not) be separate from the system contemplated herein. The system may be on standby while waiting for the user's turn to make a pick.
Once it becomes the user's turn, the system accumulates current statistics for each team. These statistics may include the current rosters of each team, and, if not already inputted during initialization, the projected statistics of the players on the rosters. This accumulation may be performed by manually inputting the draft picks of the other teams into the computer in one embodiment. In another embodiment, the system may be configured to automatically receive the picks and related draft status by accessing the drafting platform directly.
Once the statistics of the teams are accumulated, the computerized system compares all of the teams in synthesized competition, based on their projected statistics and, depending on league setup, optionally the league schedule. The system then uses a competition algorithm to return a projected standings and/or winning percentage. The projected standings and winning percentages include detailed statistical data, including identifying statistical weaknesses on the user's team compared to other teams.
Based on the results of the synthesized competition, the system then performs an analysis using a player algorithm to identify the available player that most enhances a user's team. This analysis may be performed in different ways, and may be based on a number of factors, as discussed above. In one embodiment, the player algorithm may analyze and identify players who may best boost a team statistically. In a further embodiment, the player algorithm may re-analyze projected standings and/or winning percentage with an available player, and identify the player that best increases the overall standings. Once determined by the system, the recommended player is presented to the user. The system may provide only one suggestion, or may provide a list of top suggestions to allow the user to choose.
Once the player recommendation is made, the system waits for the user to pick. Once the pick is made, the system again waits until it is the user's pick again in the next round.
FIG. 2 provides an exemplary embodiment of an output by the system showing the recommended player and support for the recommendation. In this embodiment, a win-loss % with and without the player is provided. In addition, the players projected statistics are shown, compared to a league average, and the differential.
FIG. 3 provides a detail view of additional factors that may be considered by the player algorithm when providing the player recommendation. In addition to the projected standings and winning percentages calculated by the computer, other factors may be weighted as well. A player algorithm may be utilized to consider and weigh these factors. Additional factors to consider in making the available player recommendation include the best available player based on overall statistics, the biggest differential from one player to another, position scarcity, and positional needs of the team picking.
While several variations of the present invention have been illustrated by way of example in preferred or particular embodiments, it is apparent that further embodiments could be developed within the spirit and scope of the present invention, or the inventive concept thereof. However, it is to be expressly understood that such modifications and adaptations are within the spirit and scope of the present invention, and are inclusive, but not limited to the following appended claims as set forth.

Claims

What is claimed is:

1. A method of providing a recommended pick in a fantasy draft comprising the steps of:

receiving league settings by at least one computer;

providing a default value for an unfilled roster spot of a user's team roster;

calculating a competitive landscape of the user's team roster compared to a rest of the league, using a competition algorithm of the at least one computer;

calculating a recommended pick, by the at least one computer using a player algorithm, based on the calculated competitive landscape, the recommended pick selected to provide a most favorable competitive landscape;

selecting a player to fill the unfilled roster spot;

replacing the default value for the unfilled roster spot with a projected statistic of the player, using the at least one computer.

2. The method of providing a recommended pick in a fantasy draft of claim 1 wherein the step of calculating the competitive landscape comprises the steps of:

comparing a plurality of team rosters, including the roster of the user, based on projected statistics;

providing a projected end-of-season outcome.

3. The method of providing a recommended pick in a fantasy draft of claim 1 wherein the step of receiving league settings by the at least one computer comprises receiving a manual input of the league settings.

4. The method of providing a recommended pick in a fantasy draft of claim 1 wherein the step of receiving league settings by the at least one computer comprises automatically receiving the settings by logging into a fantasy sports server and accessing a data comprising the league settings.

5. The method of providing a recommended pick in a fantasy draft of claim 1 wherein the step of selecting a player to fill the unfilled roster spot comprises automatically selecting the recommended player by the at least one computer.

6. The method of providing a recommended pick in a fantasy draft of claim 1 wherein the step of providing the recommended pick comprises providing a player name, and a calculation, by the at least one computer, of the increase in competitive landscape with and without the recommended pick.

7. The method of providing a recommended pick in a fantasy draft of claim 1 wherein the step of calculating a recommended pick is further based on a projection of a best available player.

8. The method of providing a recommended pick in a fantasy draft of claim 1 wherein the step of calculating a recommended pick is further based on a player having a greatest projected statistical differential from a second best player.

9. The method of providing a recommended pick in a fantasy draft of claim 1 wherein the step of calculating a recommended pick is further based on a player position scarcity.

10. The method of providing a recommended pick in a fantasy draft of claim 1 wherein the step of calculating a recommended pick is further based on position needs of a user's roster.

11. The method of providing a recommended pick in a fantasy draft of claim 1 wherein the step of calculating a recommended pick further comprises providing an ordered list comprising a plurality of recommended picks.

12. The method of providing a recommended pick in a fantasy draft of claim 1 wherein the step of calculating a recommended pick is based on a best available player and further comprising the steps of:

calculating a second recommended pick using the at least one computer based on a player position scarcity;

calculating a third recommended pick using the at least one computer based on a player having a greatest projected statistical differential from a second best player; and

displaying the recommended pick, the second recommended pick and the third recommended pick, to a user using the at least one computer.

13. The method of providing a recommended pick in a fantasy draft of claim 1 wherein the step of calculating the competitive landscape comprises identifying a statistical weakness of the roster of the user.

14. The method of providing a recommended pick in a fantasy draft of claim 1 wherein the step of calculating the competitive landscape is performed at an end of a draft round.

15. The method of providing a recommended pick in a fantasy draft of claim 1 wherein the step of calculating the competitive landscape is performed after each pick.

16. The method of providing a recommended pick in a fantasy draft of claim 1 wherein the step of calculating a recommended pick comprises creating a score and assigning it to a player, by the at least one computer, based on the calculated competitive landscape and the projected statistics of the player.

17. The method of providing a recommended pick in a fantasy draft of claim 16 further comprising the steps of:

creating a plurality of scores for a plurality of players, each of the plurality of players being assigned a score based on the calculated competitive landscape and the projected statistics of each of the plurality of players; and

providing an ordered list of the plurality of players based on the created plurality of scores.

18. A method of calculating a value of a player during a fantasy sports draft comprising the steps of:

receiving league settings by at least one computer;

calculating, using a competition algorithm of the at least one computer, a competitive landscape of a roster of each of a plurality of teams based on a projected statistic of each player on the roster of each of the plurality of teams;

determining a numerical value of an available player, using a player algorithm by the at least one computer, the numerical value being representative of projected statistics of the available player's ability to make a team better based on the calculated competitive landscape;

displaying, using the at least one computer, the available player having a highest numerical value assigned, the displayed available player being the recommended selection for a team currently drafting.

19. The method of calculating a value of a player during a fantasy sports draft of claim 18 further comprising the steps of:

determining a numerical value of a plurality of available players, using an algorithm on the at least one computer, the numerical values being representative of the projected statistics of the plurality of available players and calculated competitive landscape; and

displaying a plurality of available players and determined numerical values in a list, the list having higher valued players on top, in descending order of determined numerical value.

20. The method of calculating a value of a player during a fantasy sports draft of claim 18 wherein the step of calculating, using the at least one computer, a competitive landscape of a roster of each of a plurality of teams further comprises the step of assigning a default value for an unfilled roster spot of the roster of each of the plurality of teams, the default value being based on an average statistical season for the unfilled roster spot.