DETAILED ACTION
Remarks
This office action is issued in response to communication filed on 11/10/25. Claims 1-16,18-19 and 21-22 are pending in this Office Action.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant's arguments filed on 11/10/25 with respect to rejection of claims under 35 USC 103 have been considered but are moot in view of the new ground of rejection.
Claims objection has been withdrawn by the examiner in response to the amendment that overcomes the objection.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-2, 4-9,11-16 ,18-19 and 21-22 are rejected under 35 U.S.C. 1023 as being unpatentable over Jayaram et al.(US Patent Application Publication 2021/0142066 A1, hereinafter “Jayaram”) and further in view of Pennacchio.(US Patent 9,895,610 B1, hereinafter “Pennacchio”)
As to claim 1, Jayaram teaches a method, comprising: receiving, by a computing system, event data corresponding to a game from a tracking system ;( Jayaram par [0068] teaches receiving and extracting events)
utilizing, by the computing system, one or more prediction models to predict a plurality of metrics that include a plurality of quality metric or a plurality of execution metrics based on the event data corresponding to the game; (Jayaram par [0072] teaches the analytic layer may involve various analytics and AI tools to perform analysis and interpretation of data retrieved from the real time sport event so that the analyzed data results in insights that make sense out of the pulled big data from real time event. Jayaram par [0101] teaches drop down list 410 which the examiner interprets as “execution metrics”)
generating, by the computing system, a plurality of insights via one or more machine learning models based on the event data and the plurality of metrics, (Jayaram Fig.4 teaches plurality of columns such as player POS, SHOTs, EFG and SEFG. The value in each of the cells of the column is being interpreted as “insights statements ”)
wherein the plurality of insights includes one or more insight statements corresponding to a plurality of player level streak insights or a plurality of team level streak insights; (Jayaram Fig.4 teaches plurality of columns such as player POS, SHOTs, EFG and SEFG. The value in each of the cells of the column is being interpreted as “insights statement”)
ranking, by the computing system, the plurality of insights using one or more artificial intelligence techniques based on the plurality of metrics; (Jayaram par [0101] teaches user can select among various types of available rankings. Rankings can be selected in a menu 404 for players , teams or others entities. Jayaram Fig.4 teaches plurality of columns such as player POS, SHOTs, EFG and SEFG. The value in each of the cells of the column is being interpreted as “insights statement”)
generating, by the computing system, at least one graphical element corresponding to at least one of the ranked plurality of insights (Jayaram par [0101] teaches user can select among various types of available rankings. Rankings can be selected in a menu 404 for players , teams or others entities. Jayaram Fig.4 shows the values of SHOTS, EFG,SEFG..which is “graphical element” )
embedding, by the computing system, the at least one graphical element into at least one video frame of the game.( Jayaram Fig.41 and par [0205] shows an overlay with the EFG values)
Jayaram teaching ranks for players and teams but fails to expressly teach ranking, by the computing system, the plurality of insights.
However, Pennacchio teaches ranking, by the computing system, the plurality of insights.( Pennacchio Fig.4 and col 8, lines 25-35 teaches ranking of top players in section 412 (by points) )
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Jayaram and Pennacchio to achieve the claimed invention. One would have been motivated to make such combination to enhance the degree of player excitement and involvement (Pennacchio col 1, lines 40-45)
As to claim 2, Jayaram and Pennacchio teach the method of claim 1, further comprising: generating, by the computing system, a combination of insights based on the generated plurality of insights and the ranking of the plurality of insights.( Jayaram par [0101] teaches a user can select among various types of available rankings 402 as indicated by drop down list 410)
As to claim 4, Jayaram and Pennacchio teach the method of claim 1, wherein the event data corresponding to the game comprises (x,y) coordinates of a plurality of players within the game and corresponding game context data. (Jayaram par [0068] teaches 3D motion capture “XYZ” data )
As to claim 5, Jayaram and Pennacchio teach the method of claim 1, wherein ranking, by the computing system, the plurality of insights using the one or more artificial intelligence techniques comprises: ranking the plurality of insights based on learned preferences of end users. (Jayaram par [0239] teaches ranking content items based on explicit user preferences)
As to claim 6, Jayaram and Pennacchio teach the method of claim 1, wherein generating, by the computing system, the graphical user interface comprising the event data corresponding to the game and at least one insight of the plurality of insights comprises: embedding the at least one insight of the plurality of insights within the event data to provide context for the event data. (Jayaram par [0211] teaches seeing fantasy scoring relevant metrics on screen during the game)
As to claim 7, Jayaram and Pennacchio teach the method of claim 1, wherein the graphical user interface corresponds to a social media post comprising the event data corresponding to the game and the at least one insight.( Jayaram par [0237] teaches social chat and comment functions may be inserted into a 3D scene of the live event as a running commentary adjacent to other graphics or legends associated with the event)
Claims 8-9 and 11-14 merely recites a non-transitory computer readable medium comprising instructions when executed by processor , performs the method of claims 1-2 and 4-7 respectively. Accordingly, Jayaram and Pennacchio teach every limitation of claims 8-9 and 11-14 as indicates in the above rejection of claims 1-2 and 4-7 respectively.
Claims 15-16 and 18-19 merely recite a system to perform the method of claims 1-2 and 5-6 respectively. Accordingly, Jayaram and Pennacchio teach every limitation of claims 15-16 and 18-19 as indicates in the above rejection of claims 1-2 and 5-6 respectively.
As to claim 21, Jayaram and Pennacchio teach the method of claim 1, wherein the plurality of team level streak insights includes a team points insight, a team turnovers insight, a team rebounds insight, a team blocks insight, a team first downs insight, a team hits insight, a team doubles insight, a team goals insight, or a team assists insight, and wherein the plurality of player level streak insights includes a player points insight, a player turnover insight, a player steals insight, a player assists insight, a player rebounds insight, a player catches insight, a player sacks insight, or a player hits insight. (Jayaram Fig.4 teaches ranking menu 410 includes rebounding)
As to claim 22, Jayaram and Pennacchio teach the method of claim 1, wherein the one or more prediction models are configured to predict the plurality of metrics based on a current state of the game.( Jayaram par [0235] teaches the outcome prediction may be associated with outcomes of individual offensive and defensive plays in the games and/or may be associated with scoring and/or individual player statistics at predetermined time intervals)
Claims 3 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Jayaram and Pennacchio and further in view of Gupta.( US Patent Application Publication 2004/0073947 A1, hereinafter “Gupta”)
As to claim 3, Jayaram and Pennacchio teach the method of claim 1 but fail to teach further comprising: pricing, by the computing system, each insight of the plurality of generated insights.
However, Gupta teaches pricing, by the computing system, each insight of the plurality of generated insights. (Gupta par [0009] teaches there may be a pay-for -use service from which identified highlights can be received for a fee)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Jayaram, Pennacchio and Gupta to achieve the claimed invention. One would have been motivated to make such combination to allow user to watch the most important part of the game.(Gupta par [0009])
As to claim 10, see the above rejection of claim 3.
Conclusion
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/HIEN L DUONG/Primary Examiner, Art Unit 2147