kAm“}@H J@F 42? A=2J E96 =@?8 82>6 2 =:EE=6 3:E >@C6[” (256 E@=5 %96 pDD@4:2E65 !C6DD[ C676CC:?8 E@ 9@H 4@==686 A=2J6CD 42? =@@< 2E E96:C 7FEFC6D] “{@@<[ x 42? 86E A2:5 E96 D2>6 x H@F=5 86E A2:5 E96 v {628F6[ E96 D2>6 x H@F=5 86E A2:5 @? 2 EH@\H2J W4@?EC24EX[ D@>6 8FJD 2C6 86EE:?8 7:CDE\C@F?5 >@?6J]Qk^Am

kAmp?5 >@C6 >@?6J @? E96 H2J]k^Am

kAmxEVD 366? 7@FC J62CD D:?46 4@==686 2E9=6E6D k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^=2HD\DA@CED\e73`_362c`fe24e2h`a`bg46f7_2fec6QmH6C6 A6C>:EE65 E@ AC@7:E @77 E96 FD6 @7 E96:C ?2>6[ :>286 2?5 =:<6?6DD W}x{Xk^2m[ @A6?:?8 E96 5@@C 7@C 2E9=6E6 4@>A6?D2E:@? E92E H2D @?46 7@C3:556? 3J }rpp CF=6D] }6IE H66<[ @? yF=J `[ >2C^2CE:4=6^?422\D6EE=6>6?E\cbdd4_53g33a622cacged_dhc7`df_dbQm@77:4:2= DE2CE @7 C6G6?F6 D92C:?8k^2m H96C6 D49@@=D 42? 368:? 5:C64E=J A2J:?8 2E9=6E6D k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^?422\9@FD6\D6EE=6>6?E\22b`eh_de6g`hc26637bcchdec`346_3Qm7@==@H:?8 E96 Sa]g 3:==:@? w@FD6 2?E:ECFDE D6EE=6>6?Ek^2m]k^Am

kAmu@C (256[ E92E =65 E@ D:8?:?8 %6I2D %649VD s2CC:@? (:==:2>D 27E6C acfDA@CED’ 7:7E9\C2?<65 EC2?D76C H:E95C6H 7C@> E96 5C27E]k^Am

kAm“q2D:42==J ?@H :7 J@F’C6 2? 62C=J 6?ECJ 2?5 J@F’C6 ?@E 2 E@A\a_[ E@A\aa A:4< — H96C6 E96 >@?6J D=@ED — J@F 42? AC6EEJ >F49 >2<6 E92E 4@==686[” E96 ?6H (@=7A24< 4@249 D2:5]k^Am

kAmxEVD 2== A2CE @7 2 D6:D>:4 492?86 E92E 92D C:AA=65 E9C@F89 4@==686 2E9=6E:4D D:?46 E96 A2?56>:4[ :ED :>A24E E@F49:?8 E96 }qp] !=2J6CD H:==:?8 E@ “E6DE E96 H2E6CD” E96 5C27E 367@C6 C6EFC?:?8 E@ D49@@= ?@H 92G6 2 =F4C2E:G6 @AE:@? E@ 4@?D:56C 282:?DE F?46CE2:? AC@ AC@DA64ED]k^Am

kAmp?5 :E D9@HD E96 ?F>36CD]k^Am

kAm“(:E9 2== E96 >@?6J E92E’D 36:?8 E9C@H? 2C@F?5 }x{[ J@F’C6 92G:?8 2 =@E =6DD A=2J6CD AFE E96:C ?2>6D :?[” k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^56EC@:E\A:DE@?D\5h64ggf52ecggeg4h`e4__4`6g45gfg4Qms6EC@:E !:DE@?D AC6D:56?E @7 32D<6E32== @A6C2E:@?D %C2;2? {2?85@?k^2m D2:5] “*@F’C6 92G:?8 AC6EEJ 8@@5 A=2J6CD AF==:?8 E96:C ?2>6D @FE]”k^Am

k9ams64=:?:?8 ?F>36C @7 62C=J 6?EC2?EDk^9am

kAm%9:D J62CVD 5C@A D:8?:7:42?E H96? 4@>A2C65 E@ E96 J62CD 367@C6 2?J@?6 925 962C5 @7 r~’xs\`h] %96C6 H2D 2 DA:<6 @7 4@==686 A=2J6CD ;F>A:?8 :?E@ E96 5C27E E96 A2?56>:4VD 27E6C>2E9[ H96? E96J H6C6 8C2?E65 k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^4@G:5\7:7E9\J62C\32D<6E32==\A=2J6CD\d_64e7dbe26`f4_7ffechc55_`4f6_ccQm2 7C66 6=:8:3:=:EJ J62Ck^2m E@ E6>A@C2C:=J >2<6 6G6? 2 7@FCE9\J62C D6?:@C 2? “62C=J” 6?EC2?E]k^Am

kAmqFE E9@D6 ?F>36CD 925 72==6? 2D E9@D6 7:G6\J62C A=2J6CD 4J4=65 @FE @7 4@==686 32D<6E32==[ 2?5 E96JVC6 ?@H 36=@H AC6\A2?56>:4 =6G6=D] %92E 564=:?6 4@:?4:56D H:E9 }x{’D yF=J a_a` 2CC:G2=[ 7C@> k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^?32\=:76DEJ=6\DA@CED\7@@E32==\4@==686\7@@E32==\eh4hd`hec44aah6h_`gea44`f_g2b3h`Qm2E9=6E6D 5@:?8 A2:5 2AA62C2?46D @C D@4:2=\>65:2 6?5@CD6>6?EDk^2m E@ 3@@DE6CD k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^?:=\4@==64E:G6D\325e52ac6_bfca452h7536ee53e246hdQm7@C>:?8 4@==64E:G6D @776C:?8 }x{ A24<286D 2>@F?E:?8 E@ 56 724E@ D2=2C:6Dk^2m]k^Am

kAmpD 2 C6DF=Eik^Am

kAm— t:89EJ\EH@ A=2J6CD 2AA62C65 @? E96 }qpVD =:DE @7 62C=J 6?EC2?ED AC:>2C:=J 7C@> p>6C:42? 4@==686D H:E9 2 D>2EE6C:?8 @7 @E96C E62>D[ 5@H? chT 7C@> a_ac W`eaX 2?5 ?62C=J cfT 4@>A2C65 E@ E96 7@FC\J62C 2G6C286 7C@> a_`e\`h W`db]dXjk^Am

kAm— %9:CEJ\EH@ C6>2:?65 27E6C H:E95C2H2= 5625=:?6D[ 5@H? 7C@> ea =2DE J62C 2?5 fa]_ 7C@> a_`e\`hjk^Am

kAm— p55:?8 :?E6C?2E:@?2= AC@DA64ED[ `_h A=2J6CD 564=2C65 7@C E96 5C27E[ 5@H? 7C@> a_` =2DE J62C 2?5 a_d]_ 7C@> a_`e\`hjk^Am

kAm— p?5 @?=J ce C6>2:?65[ 5@H? 7C@> ff a_ac 2?5 gb]g 7C@> a_`e\`h]k^Am

k9am|@C6 4@==686 A=2J6CD H6:89:?8 @AE:@?Dk^9am

kAmsF<6 4@249 y@? $496J6C F?56CDE2?5D 5C27E 5J?2>:4D[ 3@E9 7@C ?@\5@F3E 9625=:?6CD 2?5 AC@DA64ED 724:?8 =6DD 4=2C:EJ] w6 D66D 4@==686 2E9=6E6 4@>A6?D2E:@? 2D 2 “=68:E:>2E6 82>6492?86C]Qk^Am

kAm“w@A67F==J :E 2==@HD A=2J6CD E@ 564:56 H92E’D ECF=J 36DE 7@C E96:C 82>6[” $496J6C E@=5 E96 p!] “xE 2==@HD E96> E@ 2?2=JK6i ‘p> x 24EF2==J C625J 7@C E9:D @C ?@En’ (96C6 >@?6J 5@6D?’E 92G6 E@ 36 E96 564:5:?8 724E@C] q642FD6 :7 >@?6J’D E96 564:5:?8 724E@C[ E92E’D H9J J@F D66 <:5D ?@E DE:4<] %96 }qp’D 4FEE9C@2E] xE ;FDE :D]”k^Am

kAm%96 q=F6 s6G:=D 2C6 6IA64E65 E@ 92G6 E9C66 A=2J6CD D6=64E65 E96 7:CDE\C@F?5 (65?6D52J[ :?4=F5:?8 AC6DF>AE:G6 k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^2A\A=2J6C\@7\J62C\4@@A6C\7=288\e_5c4e635c64c72c74a3_f5fb365fb7_Qm}@] ` A:4< r@@A6C u=288k^2m 2=@?8D:56 E@A\`_ AC@DA64ED z@? z?F6AA6= 2?5 z92>2? |2=F249] %96J 2=D@ 925 A=2J6CD D@CE:?8 E9C@F89 5C27E 564:D:@?D]k^Am

kAmuC6D9>2? xD2:29 tG2?D — 2 D=6?56C H:?8 H:E9 6IA=@D:G6 D4@C:?8 A@E6?E:2= — H:E95C6H :?DE625 @7 492D:?8 7:CDE\C@F?5 DE2EFD E9C@F89 E96 5C27E AC@46DD] x?4@>:?8 EC2?D76C r65C:4 r@H2C5 7C@> (2D9:?8E@? $E2E6 C2A:5=J C@D6 5C27E 3@2C5D 27E6C E96 4@>3:?6 2?5 C6>2:?65 E96 5C27E]k^Am

kAm“%96C6’D ?@ DF3DE:EFE:?8 E96 >@?6J J@F’C6 8@:?8 E@ >2<6 :7 J@F’C6 2 E@A\`d[ E@A\a_ A:4<[” D2:5 $496J6C[ 6?E6C:?8 *62C c k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^>2C49\>25?6DD\7:?2=\7@FC\5F<6\;@?\D496J6C\34f3`__b26`b`34agb`h45f_e2547c22Qm2D DF446DD@C E@ C6E:C65 w2== @7 u2>6C |:<6 zCKJK6HD<:k^2m] “qFE :7 J@F’C6 ?@E D@=:5:7:65 2D 2 7:CDE\C@F?5 A:4<[ H9J C:D< :E H96? J@F 42? 92G6 2 D@=:5 J62C 2?5 2 492?46 E@ 8@ FA @C 36 E96 D2>6 A@D:E:@? E96 7@==@H:?8 D62D@?n”k^Am

k9amr@==686 4@>A6?D2E:@? C6\D92A:?8 E96 5C27E A@@=k^9am

kAm{2?85@?[ 9:>D6=7 2 7@C>6C sF<6 7:CDE\C@F?56C[ D66D E92E 6G@=FE:@?[ E@@]k^Am

kAmw:D !:DE@?D 925 E96:C 7:CDE A=2J@77 2AA62C2?46 D:?46 a_`h[ 3FE =24< 2 7:CDE\C@F?5 D6=64E:@? 2?5 @H? 2 D:?8=6 A:4< %9FCD52J’D D64@?5 C@F?5] u6H6C 42?5:52E6D 4@F=5 >2<6 E96 2=C625J :>A6C764E D4:6?46 @7 5C27E:?8 6G6? EC:4<:6C E9:D ?6H C62=:EJ]k^Am

kAmp44@C5:?8 E@ E96 }qp’D a_ac\ad C@@<:6 D42=6[ 2 A=2J6C 8@:?8 >:5H2J E9C@F89 E96 7:CDE C@F?5 H@F=5 >2<6 C@F89=J Sb]d >:==:@? 7:CDE\J62C D2=2CJ] %92E 7:8FC6 H@F=5 5C@A E@ 23@FE Sa]g >:==:@? 2E A:4< }@] a_[ Sa]b >:==:@? 2E }@] ad 2?5 Sa]` >:==:@? H:E9 E96 b_E9 2?5 7:?2= 7:CDE\C@F?5 5C27E66]k^Am

kAmp >:?:>F> 7:CDE\J62C }qp D2=2CJn #@F89=J S`]a >:==:@?]k^Am

kAm“%96D6 }x{ A24<286D 2C6 DE2CE:?8 E@ 86E FA E@ Sb E@ Sc E@ Sd E@ Se >:==:@? 5@==2CD[” {2?85@? D2:5] “%96D6 8FJD 2C6 ?@E 8@:?8 E@ AFE E96:C ?2>6 E@ 36 E96 adE9 A:4<[ @C 6G6? E96 `gE9 A:4<] %96J 2C6 8@:?8 E@ 8@ 324< E@ D49@@= 9@A6D @7 36:?8 2 =@EE6CJ A:4< ?6IE J62C] (:E9 E92E A@@= @7 A=2J6CD 564C62D:?8[ :E <:?5 @7 564C62D6D E96 @55D @7 E96 =6G6= @7 A=2J6C H6 86E 2E }@] bf[ ;FDE E96 AFC6 >2E96>2E:4D]”k^Am

k9amrFCC6?E }qp A=2J6CD @776C :?D:89Ek^9am

kAmx?5:2?2 !246CD 3:8 >2? %9@>2D qCJ2?E 2?5 ~<=29@>2 r:EJ %9F?56C 4@F?E6CA2CE xD2:29 w2CE6?DE6:?[ H9@ 3@E9 A=2J65 k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^?32\7:?2=D\E9F?56C\492>A:@?D\g_fe2b7c5e764h3_4a33335fh7`f67bgQmE96 D6G6?\82>6 }qp u:?2=D E92E 6?565 $F?52Jk^2m[ :==FDEC2E6 {2?85@?’D A@:?E]k^Am

kAm%96J H6C6 324<\E@\324< D64@?5\C@F?56CD a_`f WqCJ2?E 2E ca[ w2CE6?DE6:? 2E cbX[ AFD965 5@H? 2 5C27E 3@2C5 762EFC:?8 62C=J\6?ECJ 4@==686 A=2J6CD bb @7 E96 c` A:4]k^Am

kAmqCJ2?E A=2J65 EH@ 4@==686 D62D@?D 2E x?5:2?2 367@C6 DE:?ED H:E9 7:G6 }qp E62>D[ :?4=F5:?8 s6?G6C’D a_ab 492>A:@?D9:A DBF25] (@F=5 E96 23:=:EJ E@ >2<6 4@==686 >@?6J 92G6 492?865 9:D ;@FC?6Jnk^Am

kAm“%@ 36 9@?6DE[ x D66 :E 7C@> 3@E9 D:56D[Q qCJ2?E D2:5] Qx7 J@F’C6 ?@E 8@:?8 E@ 86E 5C27E65[ J@F F?56CDE2?5 E92E 2 <:5 ?665D >@?6J E@ =:G6 4@==686 2?5 6G6CJE9:?8] $@[ x F?56CDE2?5 H96C6 E96J’C6 4@>:?8 7C@> @? E92E 6?5]k^Am

kAm“qFE 7@C >6[ x E@@< E96 492?46] x 36E @? >JD6=7[ 2?5 x 36=:6G65 >JD6=7[ 2?5 x H@C<65 E@ E96 G6CJ 6?5] p?5 E96 E9:?8 23@FE >6 E92E :7 x H6?E 5@H?[ x H2D 8@:?8 5@H? DH:?8:?8] x 92?8 >J 92E @? E92E] u@C D@>6[ :E >:89E ?@E 36 E96 D2>6 42D6]Qk^Am

kAm%96 p>6C:42?\3@C? w2CE6?DE6:? >@G65 E@ v6C>2?J 2E “ 2?5 A=2J65 {:E9F2?:2 367@C6 36:?8 5C27E65] pD 96 AFE :Ei “x E9:?< 6G6CJ@?6’D ;@FC?6J 5:776C6?E]”k^Am

kAm“x E9:?< J@F D9@F=5 92G6 E96 C:89E A6@A=6 2C@F?5 J@F E@ <:?5 @7 8F:56 J@F[” D2:5 w2CE6?DE6:?[ 2 ?6H=J >:?E65 }qp 492>A:@?] “x >62?[ x H2D =F4J 525[ H9@ H2D 2 AC@76DD:@?2= 367@C6[ <:?5 @7 8F:565 >6] s6A6?5:?8 @? J@FC 4:C4F>DE2?46D[ :E’D 92C5 E@ EFC? 5@H? 8F2C2?E665 >@?6J] x7 E96C6’D 2? @AA@CEF?:EJ E@ 86E 2 8@@5 D:EF2E:@? E96 }qp[ J@F 5@ E92E] qFE :E’D 2 92C5 564:D:@?]”k^Am

k9amr@==686 ?@H 42? 36 >@C6 @7 2? 2==FC6k^9am

kAmpE }]r] $E2E6[ (256VD A:E49 E@ (:==:2>D :?4=F565 2 =625:?8 C@=6 2?5 2 D9@E 2E 3@@DE:?8 9:D 5C27E DE@4<]k^Am

kAm%96 e\7@@E\e ;F?:@C 2G6C2865 `d]` A@:?ED H:E9 k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^>2C49\>25?6DD\2C<2?D2D\E6I2D\E649\D4@C6\cg6f67`a2cdd336b4d4ee4263ag4_42dQm>F=E:A=6 3:8 }rpp %@FC?2>6?E A6C7@C>2?46Dk^2m 2D E96 #65 #2:56CD C624965 E96 t=:E6 t:89E[ k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^>2C49\>25?6DD\E6I2D\E649\7=@C:52\D4@C6\b2d527faa___5ff“ghf3daeabd5d2h7Qm?62C=J 362E:?8 6G6?EF2= 492>A:@? u=@C:52k^2m]k^Am

kAm“w6 H2D >@DE =:<6=J 8@:?8 E@ 36 2 D64@?5\C@F?5 5C27E A:4<[ 2?5 9:D A24<286 96C6 36EE6C E92? AC@323=J 96 H@F=5’G6 8@EE6? 2D 2 D64@?5\C@F?5 A:4<[” (256 D2:5[ 255:?8i “(6 46CE2:?=J E2=<65 23@FE E92E] (6 H6?E @G6C E92E] (6 H6?E @G6C E96 >2E9 @7 6G6CJE9:?8] (6 H6?E @G6C E96 A=2? @? 9@H E@ 244@>A=:D9 E92E]Qk^Am

kAm%92EVD ?@E E@ D2J :EVD 62DJ 2E E96 4@==686 =6G6= E9:D ?6H =2?5D42A6] k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^DA@CED\4@==686\32D<6E32==\>6?D\ffh“hg4g6d4b_5beh5_e4343`4aeag5Qm#@DE6C >2?286>6?Ek^2m EC:42:?E2:?:?8 7:?2?4:2= C6D@FC46D E@ A@E6?E:2==J =2?5 @?6 A=2J6C H9:=6 C:D<:?8 >:DD:?8 @FE @? @E96CD]k^Am

kAm“xE’D E96 H2J =:76 H@CD @7 H2:E:?8 @? E96 >@?6J 2?5 H2:E:?8 E96> @FE[ 2C6 E96 36DE A=2J6CD] %92E’D H9J E96J’C6 E96 5C27E AC@46DD] (6’C6 ?@E 8@:?8 E@ 36 D42C65 @7 E92E]”k^Am

kAm}@C D9@F=5 96[ ?@E H:E9 E96 2==FC6 @7 42>AFD =:76 E96D6 52JD]k^Am

k9C ^m

kAmp! q2D<6E32== (C:E6C %:> #6J?@=5D 2?5 p! $A@CED (C:E6C {2CCJ {286 4@?EC:3FE65 E@ E9:D C6A@CE]k^Am

k9C ^m

kAmp! }qpi k2 9C67lQ9EEADi^^2A?6HD]4@>^9F3^?32Qm9EEADi^^2A?6HD]4@>^?32k^2mk^Am

It’s no secret that 2K needs to overhaul both the MyCareer and MyPlayer modes that NBA 2K offers, and a College Hoops game is the best way to do that. 2K has dominated basketball video games for years now. As a result, since it has no competitors, it struggles to innovate. This is clear to see in MyCareer and MyPlayer. (And, for what it’s worth, the same could be said of EA’s Superstar mode in Madden.)

Career modes often struggle in the modern era of sports games because the money is made in online modes. College Hoops 2K8 is beloved by many for its offline Legacy mode, in which gamers play as coaches as they take over programs, recruit stars, and build dynastic teams. But what about a mode where you get to be the star recruit? In an age where variety is at an all-time low in sports games, having a college version of NBA 2K’s MyCareer, focused on a created athlete, would revitalize that side of basketball games for many who tend to skip buying new releases each year because not enough new features have been added. (Again, an EA parallel here is how refreshing College Football’s Road to Glory mode is compared to Madden’s Superstar mode.)

MyPlayer, 2K’s sort of mode within a mode, a hub in MyCareer where you customize your avatar outside of the mode’s narrative, is what would need to most revamping if it were repurposed for College Hoops. For so many 2K fans, it’s hard to even describe what you really get out of this thing anymore. OG fans can’t stand how much junk 2K has put in between you and just playing the game. And for younger fans, whether they like the experience of MyPlayer or not, the sheer cost of investing in their players is staggering.

No such hub exists in College Football. If 2K is as smart as EA, College Hoops would take a similar approach to storytelling and character-building as College Football, creating a streamlined mode like Road to Glory that improves upon something like Superstar by offering more fun, fewer transactions, and lots of free customizations. If such a mode were added alongside Legacy, players could immerse their avatars in an on-campus journey rather than just styling their characters off the court in NBA 2K.

How would you navigate NIL deals and playing for different coaches in college? What would you do if you got passed up by your dream school after they recruited you? Would you stay in school if you lost in the Final 4? There are so many fresh plot lines out there for a new College Hoops game. Running around a college campus sounds far more fun and immersive than some invented city at this point. And being able to continue that journey in NBA 2K, the way created College Football athletes can be ported over to Madden, would make the whole process that much more fulfilling.

The last few years have brought about a financial revolution in the business of college sports – especially football and basketball. And this economic revolution is intersecting with AI, our most explosive technological revolution maybe ever.

I spent some time with the founder of a just-launched company named Cache AI that is looking to insert itself into the middle of the college sports business maelstrom. Remember when universities used to brag about the graduation rates of their student athletes? As Dorothy might metaphorically say to Toto: “I’ve a feeling we’re not in Kansas anymore.” Or maybe we are.

The broadest driver of money in the college system is of course TV – linear and streaming, which craves live sports above all other content. All TV rights for college athletics totaled $1.9 billion in 2009, and $4.2 billion by 2022. And since then? In 2023 the Big Ten conference alone signed new rights deals for football with Fox, NBC and CBS that will in total bring over $1 billion a year to its member universities, more than double the prior deals. And in January 2024, ESPN extended its exclusive rights to the College Football Playoff, committing $1.3 billion per year through 2031, nearly three times what it paid under its prior deal.

Despite this seemingly endless money windfall, for athletes to be able to share in it they needed the U.S. Supreme Court. Who would have thought? In June 2021 the Court ruled that the NCAA could not bar payment of student athletes for their NIL (name, image and likeness) rights in marketing and promotion. A tsunami of payments to jocks followed, mostly by unregulated “collectives” (read: alumni boosters), with a few of the most eye-raising being the $6.5 million paid to Arch Manning, quarterback at the University of Texas and $4.1 million to Livvy Dunne, the LSU gymnast.

A new “system” for doling out these NIL payments has emerged just this month with the settlement of several antitrust suits brought by college athletes against the National College Athletic Association and the most powerful sports-oriented conferences and universities. In that settlement, athletes who competed over the last 10 years will receive nearly $2.8 billion for “back pay” from the NCAA. Beginning in 2025-26, each Division 1 school can pay its athletes up $20.5 million, an amount that will increase every year during the decade-long deal. But this deal hardly “solves” the NIL issue for athletes and universities. In many ways, it just restarts it.

Young athletes and their families if they are lucky have before them huge opportunities for monetizing their talents with brands and universities. But the NIL market today has little transparency for most athletes. The new NCAA settlement will create what it calls the “NIL Go Clearinghouse” to be run by Deloitte and which will determine if any NIL deal above $600 is for “valid business purposes” and represents “fair market value.” But good luck trying to figure out how this will work.

Putting aside the potential antitrust implications of universities that compete with each other creating a system to limit athlete compensation (but stay tuned there), there is no standard means of comparing the monetary value of athletes within and across sports, schools, conferences and brands. What is a “fair” value in the marketplace and how does anyone trust how to evaluate that? Into this breach comes the new kid on the block, Cache AI.

The company has built what it calls “the valuation intelligence engine for the talent economy.” As the company’s founder Kobi Wu told me, “Everyone [in college athletics] is thinking about ticket sales and money, but not about the players. We are all about the athletes.” Wu shared a conversation she had with a major college athletic director who told her “So you’re going to help athletes negotiate against me?” To which Wu responded – absolutely – what’s wrong with that?

Noting that schools and brands have as much incentive as athletes to properly estimate marketplace value, Cache AI is working through schools and universities to sign up student athletes and their families. Students will enter data at their discretion in areas such as on-field performance statistics, how their values align with brands, and their “community influence, reputation and visibility” including verifiable information from community service to grades to social media metrics. Since getting this to work demands some student homework, Wu joked that “kids like us, but families love us.”

The company hopes that their platform will become “the trusted standard for evaluating talent impact.” As the output of the input of thousands of athletes and millions of public data points, athletes receive a “CacheScore” (note the double entendre here) that provides a real-time standardized metric of relative marketability. In addition, the engine will provide a metric it calls “CacheValue” to predict future marketplace value.

The company went live with its app in just the last week. According to Wu, it already has over 2000 active student athletes, with 17,000 more in the queue. It’s goal it to get to 50,000 students by year-end and Wu told me that 100,000 is not out of the question. The service is free for students, and its revenues will come from seat licenses from corporate clients such as universities and brands. The company’s recruitment efforts start early, with high schools and athletes who want to assess their value as they enter the NIL world. And if you think that sounds young, I attended an event last week where several companies pitched their tech platforms for parents of kids as young as seven to track their on-field performance. Look out for pre-natal sports testing next.

As with any early-stage company, it takes a small village to make this work. The core team for Cache AI, in addition to Wu, includes data scientist Dr. Kruti Lehenbauer, former college athlete and sports marketer Laura Waters-Brown and ex-Google engineering exec Chris Johnson. The company is still in early days, with a small group of angel investors and early bootstrapping, and now out raising its Series A funding. There are many rivers to cross on the journey ahead.

Unquestionably Cache AI is onto something, but of course it is hardly the first to spy opportunity in the mix of sports, media, AI, and technology. Teamworks, which bills itself as “the operating system for sports,” just raised $235 million, with a valuation of $1 billion. Opendorse is out there with a platform for student athletes that looks like a combination of an influencer marketing agency and Cameo. In the NIL world, we’ve only just begun.

Will Wade’s work building N.C. State into an immediate winner included the pursuit of an entrant in the NBA Draft, just in case he returned to college. It wasn’t a huge risk: With all the cash flowing in college, the number of early entrants to the NBA Draft has continued to shrink.

This year’s NBA Draft starts Wednesday night with its lowest total of those prospects in at least 10 years. “Now you can play the long game a little bit more,” Wade told The Associated Press, referring to how college players can look at their futures. 

“Look, I can get paid the same I would get paid in the G League, the same I would get paid on a two-way (contract), some guys are getting first-round money.”

And more money is on the way.

It’s been four years since college athletes were permitted to profit off the use of their name, image and likeness (NIL), opening the door for athlete compensation that was once forbidden by NCAA rules. Next week, on July 1, marks the official start of revenue sharing where schools can begin directly paying athletes following the $2.8 billion House antitrust settlement.

For Wade, that led to signing Texas Tech’s Darrion Williams after 247sports’ fifth-ranked transfer withdrew from the draft.

“Basically now if you’re an early entry and you’re not a top-20, top-22 pick — where the money slots — you can pretty much make that in college,” the new Wolfpack coach said.

It’s all part of a seismic change that has rippled through college athletics since the pandemic, its impact touching the NBA. Players willing to “test the waters” in the draft before returning to school now have a lucrative option to consider against uncertain pro prospects.

[Related: 3 Best 2025 NBA Draft Fits for Rutgers Star Dylan Harper]

And it shows in the numbers.

“With all the money that’s being thrown around in NIL, you’re having a lot less players put their names in,” Detroit Pistons president of basketball operations Trajan Langdon said. “You’re having pretty good players pulling their names out.”

Declining number of early entrants

This year’s drop is significant when compared to the years before anyone had heard of COVID-19. There was a spike of college players jumping into the draft in the pandemic’s aftermath, when they were granted a free eligibility year to temporarily make even a fourth-year senior an “early” entrant.

But those numbers had fallen as those five-year players cycled out of college basketball, and they’re now below pre-pandemic levels. That decline coincides with NIL’s July 2021 arrival, from athletes doing paid appearances or social-media endorsements to boosters forming collectives offering NIL packages amounting to de facto salaries.

As a result:

— Eighty-two players appeared on the NBA’s list of early entrants primarily from American colleges with a smattering of other teams, down 49% from 2024 (162) and nearly 47% compared to the four-year average from 2016-19 (153.5);

— Thirty-two remained after withdrawal deadlines, down from 62 last year and 72.0 from 2016-19;

— Adding international prospects, 109 players declared for the draft, down from 201 last year and 205.0 from 2016-19;

— And only 46 remained, down from 77 in 2024 and 83.8 from 2016-19.

More college players weighing options

Duke coach Jon Scheyer understands draft dynamics, both for no-doubt headliners and prospects facing less clarity. He sees college athlete compensation as a “legitimate gamechanger.”

“Hopefully it allows players to decide what’s truly best for their game,” Scheyer told the AP. “It allows them to analyze: ‘Am I actually ready for this or not?’ Where money doesn’t have to be the deciding factor. Because if money’s the deciding factor, that’s why you see kids not stick. The NBA’s cutthroat. It just is.”

The Blue Devils are expected to have three players selected in the first-round Wednesday, including presumptive No. 1 pick Cooper Flagg alongside top-10 prospects Kon Knueppel and Khaman Maluach. They also had players sorting through draft decisions.

Freshman Isaiah Evans — a slender wing with explosive scoring potential — withdrew instead of chasing first-round status through the draft process. Incoming transfer Cedric Coward from Washington State rapidly rose draft boards after the combine and remained in the draft.

[Related: 3 Best 2025 NBA Draft Fits for Rutgers Star Ace Bailey]

“There’s no substituting the money you’re going to make if you’re a top-15, top-20 pick,” said Scheyer, entering Year 4 as successor to retired Hall of Famer Mike Krzyzewski. “But if you’re not solidified as a first-round pick, why risk it when you can have a solid year and a chance to go up or be in the same position the following season?”

College compensation is re-shaping the draft pool

Langdon, himself a former Duke first-rounder, sees that evolution, too.

His Pistons had their first playoff appearance since 2019, but lack a first-round selection and own a single pick in Thursday’s second round. Fewer candidates could make the already imperfect science of drafting even trickier in this new reality.

[Related: Top 10 men’s college basketball players with highest NIL valuations]

According to the NBA’s 2024-25 rookie scale, a player going midway through the first round would make roughly $3.5 million in first-year salary. That figure would drop to about $2.8 million at pick No. 20, $2.3 million at No. 25 and $2.1 million with the 30th and final first-round draftee.

A minimum first-year NBA salary? Roughly $1.2 million.

“These NIL packages are starting to get up to $3 to $4 to $5 to $6 million dollars,” Langdon said. “These guys are not going to put their name in to be the 25th pick, or even the 18th pick. They are going to go back to school in hopes of being a lottery pick next year. With that pool of players decreasing, it kind of decreases the odds of the level of player we get at No. 37, just the pure mathematics.”

Current NBA players offer insight

Indiana Pacers big man Thomas Bryant and Oklahoma City Thunder counterpart Isaiah Hartenstein, who both played in the seven-game NBA Finals that ended Sunday, illustrate Langdon’s point.

They were back-to-back second-rounders in 2017 (Bryant at 42, Hartenstein at 43), pushed down a draft board featuring early-entry college players in 33 of the 41 picks before them.

Bryant played two college seasons at Indiana before stints with five NBA teams, including Denver’s 2023 championship squad. Would the ability to make college money have changed his journey?

[Related: How much money did Cooper Flagg make in NIL during his one year at Duke?]

“To be honest, I see it from both sides,” Bryant said. “If you’re not going to get drafted, you understand that a kid needs money to live in college and everything. So, I understand where they’re coming from on that end.

“But for me, I took the chance. I bet on myself, and I believed in myself, and I worked to the very end. And the thing about me is that if I went down, I was going down swinging. I hang my hat on that. For some, it might not be the same case.”

The American-born Hartenstein moved to Germany at 11 and played in Lithuania before being drafted. As he put it: “I think everyone’s journey is different.”

“I think you should have the right people around you to kind of guide you,” said Hartenstein, a newly minted NBA champion. “I mean, I was lucky that my dad, who was a professional before, kind of guided me. Depending on your circumstances, it’s hard to turn down guaranteed money. If there’s an opportunity to get in a good situation in the NBA, you do that. But it’s a hard decision.”

College now can be more of an allure

At N.C. State, Wade’s pitch to Williams included a leading role and a shot at boosting his draft stock.

The 6-foot-6 junior averaged 15.1 points with multiple big NCAA Tournament performances as the Red Raiders reached the Elite Eight, nearly beating eventual champion Florida.

“He was most likely going to be a second-round draft pick, and his package here is better than probably he would’ve gotten as a second-round pick,” Wade said, adding: “We certainly talked about that. We went over that. We went over the math of everything. We went over the plan on how to accomplish that.”

That’s not to say it’s easy at the college level in this new landscape. Roster management is tricky, including a balancing act of maintaining financial resources to potentially land one player while risking missing out on others.

“It’s the way life works, it’s the way it should work,” Wade said. “If there’s no risk, there’s no reward. The riskiest players, in terms of waiting on the money and waiting them out, are the best players. That’s why they’re in the draft process. We’re not going to be scared of that.”

Nor should he, not with the allure of campus life these days.

Reporting by The Associated Press.

Want great stories delivered right to your inbox? Create or log in to your FOX Sports account, and follow leagues, teams and players to receive a personalized newsletter daily!

Get more from National Basketball Association Follow your favorites to get information about games, news and more

kAm“}@H J@F 42? A=2J E96 =@?8 82>6 2 =:EE=6 3:E >@C6[” (256 E@=5 %96 pDD@4:2E65 !C6DD[ C676CC:?8 E@ 9@H 4@==686 A=2J6CD 42? =@@< 2E E96:C 7FEFC6D] “{@@<[ x 42? 86E A2:5 E96 D2>6 x H@F=5 86E A2:5 E96 v {628F6[ E96 D2>6 x H@F=5 86E A2:5 @? 2 EH@\H2J W4@?EC24EX[ D@>6 8FJD 2C6 86EE:?8 7:CDE\C@F?5 >@?6J]Qk^Am

kAmp?5 >@C6 >@?6J @? E96 H2J]k^Am

kAmxEVD 366? 7@FC J62CD D:?46 4@==686 2E9=6E6D k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^=2HD\DA@CED\e73`_362c`fe24e2h`a`bg46f7_2fec6QmH6C6 A6C>:EE65 E@ AC@7:E @77 E96 FD6 @7 E96:C ?2>6[ :>286 2?5 =:<6?6DD W}x{Xk^2m[ @A6?:?8 E96 5@@C 7@C 2E9=6E6 4@>A6?D2E:@? E92E H2D @?46 7@C3:556? 3J }rpp CF=6D] }6IE H66<[ @? yF=J `[ >2C^2CE:4=6^?422\D6EE=6>6?E\cbdd4_53g33a622cacged_dhc7`df_dbQm@77:4:2= DE2CE @7 C6G6?F6 D92C:?8k^2m H96C6 D49@@=D 42? 368:? 5:C64E=J A2J:?8 2E9=6E6D k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^?422\9@FD6\D6EE=6>6?E\22b`eh_de6g`hc26637bcchdec`346_3Qm7@==@H:?8 E96 Sa]g 3:==:@? w@FD6 2?E:ECFDE D6EE=6>6?Ek^2m]k^Am

kAmu@C (256[ E92E =65 E@ D:8?:?8 %6I2D %649VD s2CC:@? (:==:2>D 27E6C acfDA@CED’ 7:7E9\C2?<65 EC2?D76C H:E95C6H 7C@> E96 5C27E]k^Am

kAm“q2D:42==J ?@H :7 J@F’C6 2? 62C=J 6?ECJ 2?5 J@F’C6 ?@E 2 E@A\a_[ E@A\aa A:4< — H96C6 E96 >@?6J D=@ED — J@F 42? AC6EEJ >F49 >2<6 E92E 4@==686[” E96 ?6H (@=7A24< 4@249 D2:5]k^Am

kAmxEVD 2== A2CE @7 2 D6:D>:4 492?86 E92E 92D C:AA=65 E9C@F89 4@==686 2E9=6E:4D D:?46 E96 A2?56>:4[ :ED :>A24E E@F49:?8 E96 }qp] !=2J6CD H:==:?8 E@ “E6DE E96 H2E6CD” E96 5C27E 367@C6 C6EFC?:?8 E@ D49@@= ?@H 92G6 2 =F4C2E:G6 @AE:@? E@ 4@?D:56C 282:?DE F?46CE2:? AC@ AC@DA64ED]k^Am

kAmp?5 :E D9@HD E96 ?F>36CD]k^Am

kAm“(:E9 2== E96 >@?6J E92E’D 36:?8 E9C@H? 2C@F?5 }x{[ J@F’C6 92G:?8 2 =@E =6DD A=2J6CD AFE E96:C ?2>6D :?[” k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^56EC@:E\A:DE@?D\5h64ggf52ecggeg4h`e4__4`6g45gfg4Qms6EC@:E !:DE@?D AC6D:56?E @7 32D<6E32== @A6C2E:@?D %C2;2? {2?85@?k^2m D2:5] “*@F’C6 92G:?8 AC6EEJ 8@@5 A=2J6CD AF==:?8 E96:C ?2>6D @FE]”k^Am

k9ams64=:?:?8 ?F>36C @7 62C=J 6?EC2?EDk^9am

kAm%9:D J62CVD 5C@A D:8?:7:42?E H96? 4@>A2C65 E@ E96 J62CD 367@C6 2?J@?6 925 962C5 @7 r~’xs\`h] %96C6 H2D 2 DA:<6 @7 4@==686 A=2J6CD ;F>A:?8 :?E@ E96 5C27E E96 A2?56>:4VD 27E6C>2E9[ H96? E96J H6C6 8C2?E65 k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^4@G:5\7:7E9\J62C\32D<6E32==\A=2J6CD\d_64e7dbe26`f4_7ffechc55_`4f6_ccQm2 7C66 6=:8:3:=:EJ J62Ck^2m E@ E6>A@C2C:=J >2<6 6G6? 2 7@FCE9\J62C D6?:@C 2? “62C=J” 6?EC2?E]k^Am

kAmqFE E9@D6 ?F>36CD 925 72==6? 2D E9@D6 7:G6\J62C A=2J6CD 4J4=65 @FE @7 4@==686 32D<6E32==[ 2?5 E96JVC6 ?@H 36=@H AC6\A2?56>:4 =6G6=D] %92E 564=:?6 4@:?4:56D H:E9 }x{’D yF=J a_a` 2CC:G2=[ 7C@> k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^?32\=:76DEJ=6\DA@CED\7@@E32==\4@==686\7@@E32==\eh4hd`hec44aah6h_`gea44`f_g2b3h`Qm2E9=6E6D 5@:?8 A2:5 2AA62C2?46D @C D@4:2=\>65:2 6?5@CD6>6?EDk^2m E@ 3@@DE6CD k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^?:=\4@==64E:G6D\325e52ac6_bfca452h7536ee53e246hdQm7@C>:?8 4@==64E:G6D @776C:?8 }x{ A24<286D 2>@F?E:?8 E@ 56 724E@ D2=2C:6Dk^2m]k^Am

kAmpD 2 C6DF=Eik^Am

kAm— t:89EJ\EH@ A=2J6CD 2AA62C65 @? E96 }qpVD =:DE @7 62C=J 6?EC2?ED AC:>2C:=J 7C@> p>6C:42? 4@==686D H:E9 2 D>2EE6C:?8 @7 @E96C E62>D[ 5@H? chT 7C@> a_ac W`eaX 2?5 ?62C=J cfT 4@>A2C65 E@ E96 7@FC\J62C 2G6C286 7C@> a_`e\`h W`db]dXjk^Am

kAm— %9:CEJ\EH@ C6>2:?65 27E6C H:E95C2H2= 5625=:?6D[ 5@H? 7C@> ea =2DE J62C 2?5 fa]_ 7C@> a_`e\`hjk^Am

kAm— p55:?8 :?E6C?2E:@?2= AC@DA64ED[ `_h A=2J6CD 564=2C65 7@C E96 5C27E[ 5@H? 7C@> a_` =2DE J62C 2?5 a_d]_ 7C@> a_`e\`hjk^Am

kAm— p?5 @?=J ce C6>2:?65[ 5@H? 7C@> ff a_ac 2?5 gb]g 7C@> a_`e\`h]k^Am

k9am|@C6 4@==686 A=2J6CD H6:89:?8 @AE:@?Dk^9am

kAmsF<6 4@249 y@? $496J6C F?56CDE2?5D 5C27E 5J?2>:4D[ 3@E9 7@C ?@\5@F3E 9625=:?6CD 2?5 AC@DA64ED 724:?8 =6DD 4=2C:EJ] w6 D66D 4@==686 2E9=6E6 4@>A6?D2E:@? 2D 2 “=68:E:>2E6 82>6492?86C]Qk^Am

kAm“w@A67F==J :E 2==@HD A=2J6CD E@ 564:56 H92E’D ECF=J 36DE 7@C E96:C 82>6[” $496J6C E@=5 E96 p!] “xE 2==@HD E96> E@ 2?2=JK6i ‘p> x 24EF2==J C625J 7@C E9:D @C ?@En’ (96C6 >@?6J 5@6D?’E 92G6 E@ 36 E96 564:5:?8 724E@C] q642FD6 :7 >@?6J’D E96 564:5:?8 724E@C[ E92E’D H9J J@F D66 <:5D ?@E DE:4<] %96 }qp’D 4FEE9C@2E] xE ;FDE :D]”k^Am

kAm%96 q=F6 s6G:=D 2C6 6IA64E65 E@ 92G6 E9C66 A=2J6CD D6=64E65 E96 7:CDE\C@F?5 (65?6D52J[ :?4=F5:?8 AC6DF>AE:G6 k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^2A\A=2J6C\@7\J62C\4@@A6C\7=288\e_5c4e635c64c72c74a3_f5fb365fb7_Qm}@] ` A:4< r@@A6C u=288k^2m 2=@?8D:56 E@A\`_ AC@DA64ED z@? z?F6AA6= 2?5 z92>2? |2=F249] %96J 2=D@ 925 A=2J6CD D@CE:?8 E9C@F89 5C27E 564:D:@?D]k^Am

kAmuC6D9>2? xD2:29 tG2?D — 2 D=6?56C H:?8 H:E9 6IA=@D:G6 D4@C:?8 A@E6?E:2= — H:E95C6H :?DE625 @7 492D:?8 7:CDE\C@F?5 DE2EFD E9C@F89 E96 5C27E AC@46DD] x?4@>:?8 EC2?D76C r65C:4 r@H2C5 7C@> (2D9:?8E@? $E2E6 C2A:5=J C@D6 5C27E 3@2C5D 27E6C E96 4@>3:?6 2?5 C6>2:?65 E96 5C27E]k^Am

kAm“%96C6’D ?@ DF3DE:EFE:?8 E96 >@?6J J@F’C6 8@:?8 E@ >2<6 :7 J@F’C6 2 E@A\`d[ E@A\a_ A:4<[” D2:5 $496J6C[ 6?E6C:?8 *62C c k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^>2C49\>25?6DD\7:?2=\7@FC\5F<6\;@?\D496J6C\34f3`__b26`b`34agb`h45f_e2547c22Qm2D DF446DD@C E@ C6E:C65 w2== @7 u2>6C |:<6 zCKJK6HD<:k^2m] “qFE :7 J@F’C6 ?@E D@=:5:7:65 2D 2 7:CDE\C@F?5 A:4<[ H9J C:D< :E H96? J@F 42? 92G6 2 D@=:5 J62C 2?5 2 492?46 E@ 8@ FA @C 36 E96 D2>6 A@D:E:@? E96 7@==@H:?8 D62D@?n”k^Am

k9amr@==686 4@>A6?D2E:@? C6\D92A:?8 E96 5C27E A@@=k^9am

kAm{2?85@?[ 9:>D6=7 2 7@C>6C sF<6 7:CDE\C@F?56C[ D66D E92E 6G@=FE:@?[ E@@]k^Am

kAmw:D !:DE@?D 925 E96:C 7:CDE A=2J@77 2AA62C2?46 D:?46 a_`h[ 3FE =24< 2 7:CDE\C@F?5 D6=64E:@? 2?5 @H? 2 D:?8=6 A:4< %9FCD52J’D D64@?5 C@F?5] u6H6C 42?5:52E6D 4@F=5 >2<6 E96 2=C625J :>A6C764E D4:6?46 @7 5C27E:?8 6G6? EC:4<:6C E9:D ?6H C62=:EJ]k^Am

kAmp44@C5:?8 E@ E96 }qp’D a_ac\ad C@@<:6 D42=6[ 2 A=2J6C 8@:?8 >:5H2J E9C@F89 E96 7:CDE C@F?5 H@F=5 >2<6 C@F89=J Sb]d >:==:@? 7:CDE\J62C D2=2CJ] %92E 7:8FC6 H@F=5 5C@A E@ 23@FE Sa]g >:==:@? 2E A:4< }@] a_[ Sa]b >:==:@? 2E }@] ad 2?5 Sa]` >:==:@? H:E9 E96 b_E9 2?5 7:?2= 7:CDE\C@F?5 5C27E66]k^Am

kAmp >:?:>F> 7:CDE\J62C }qp D2=2CJn #@F89=J S`]a >:==:@?]k^Am

kAm“%96D6 }x{ A24<286D 2C6 DE2CE:?8 E@ 86E FA E@ Sb E@ Sc E@ Sd E@ Se >:==:@? 5@==2CD[” {2?85@? D2:5] “%96D6 8FJD 2C6 ?@E 8@:?8 E@ AFE E96:C ?2>6 E@ 36 E96 adE9 A:4<[ @C 6G6? E96 `gE9 A:4<] %96J 2C6 8@:?8 E@ 8@ 324< E@ D49@@= 9@A6D @7 36:?8 2 =@EE6CJ A:4< ?6IE J62C] (:E9 E92E A@@= @7 A=2J6CD 564C62D:?8[ :E <:?5 @7 564C62D6D E96 @55D @7 E96 =6G6= @7 A=2J6C H6 86E 2E }@] bf[ ;FDE E96 AFC6 >2E96>2E:4D]”k^Am

k9amrFCC6?E }qp A=2J6CD @776C :?D:89Ek^9am

kAmx?5:2?2 !246CD 3:8 >2? %9@>2D qCJ2?E 2?5 ~<=29@>2 r:EJ %9F?56C 4@F?E6CA2CE xD2:29 w2CE6?DE6:?[ H9@ 3@E9 A=2J65 k2 9C67lQ9EEADi^^2A?6HD]4@>^2CE:4=6^?32\7:?2=D\E9F?56C\492>A:@?D\g_fe2b7c5e764h3_4a33335fh7`f67bgQmE96 D6G6?\82>6 }qp u:?2=D E92E 6?565 $F?52Jk^2m[ :==FDEC2E6 {2?85@?’D A@:?E]k^Am

kAm%96J H6C6 324<\E@\324< D64@?5\C@F?56CD a_`f WqCJ2?E 2E ca[ w2CE6?DE6:? 2E cbX[ AFD965 5@H? 2 5C27E 3@2C5 762EFC:?8 62C=J\6?ECJ 4@==686 A=2J6CD bb @7 E96 c` A:4]k^Am

kAmqCJ2?E A=2J65 EH@ 4@==686 D62D@?D 2E x?5:2?2 367@C6 DE:?ED H:E9 7:G6 }qp E62>D[ :?4=F5:?8 s6?G6C’D a_ab 492>A:@?D9:A DBF25] (@F=5 E96 23:=:EJ E@ >2<6 4@==686 >@?6J 92G6 492?865 9:D ;@FC?6Jnk^Am

kAm“%@ 36 9@?6DE[ x D66 :E 7C@> 3@E9 D:56D[Q qCJ2?E D2:5] Qx7 J@F’C6 ?@E 8@:?8 E@ 86E 5C27E65[ J@F F?56CDE2?5 E92E 2 <:5 ?665D >@?6J E@ =:G6 4@==686 2?5 6G6CJE9:?8] $@[ x F?56CDE2?5 H96C6 E96J’C6 4@>:?8 7C@> @? E92E 6?5]k^Am

kAm“qFE 7@C >6[ x E@@< E96 492?46] x 36E @? >JD6=7[ 2?5 x 36=:6G65 >JD6=7[ 2?5 x H@C<65 E@ E96 G6CJ 6?5] p?5 E96 E9:?8 23@FE >6 E92E :7 x H6?E 5@H?[ x H2D 8@:?8 5@H? DH:?8:?8] x 92?8 >J 92E @? E92E] u@C D@>6[ :E >:89E ?@E 36 E96 D2>6 42D6]Qk^Am

kAm%96 p>6C:42?\3@C? w2CE6?DE6:? >@G65 E@ v6C>2?J 2E “ 2?5 A=2J65 {:E9F2?:2 367@C6 36:?8 5C27E65] pD 96 AFE :Ei “x E9:?< 6G6CJ@?6’D ;@FC?6J 5:776C6?E]”k^Am

kAm“x E9:?< J@F D9@F=5 92G6 E96 C:89E A6@A=6 2C@F?5 J@F E@ <:?5 @7 8F:56 J@F[” D2:5 w2CE6?DE6:?[ 2 ?6H=J >:?E65 }qp 492>A:@?] “x >62?[ x H2D =F4J 525[ H9@ H2D 2 AC@76DD:@?2= 367@C6[ <:?5 @7 8F:565 >6] s6A6?5:?8 @? J@FC 4:C4F>DE2?46D[ :E’D 92C5 E@ EFC? 5@H? 8F2C2?E665 >@?6J] x7 E96C6’D 2? @AA@CEF?:EJ E@ 86E 2 8@@5 D:EF2E:@? E96 }qp[ J@F 5@ E92E] qFE :E’D 2 92C5 564:D:@?]”k^Am