Every­where you turn to­day you're hear­ing about the ben­e­fits of im­ple­ment­ing Ar­ti­fi­cial In­tel­li­gence (AI) in sports. And no doubt about it, there are nu­mer­ous ben­e­fits in­clud­ing the im­proved ac­cu­ra­cy and pre­ci­sion that it can pro­vide.

With the help of sen­sors and cam­eras, AI tech­nol­o­gy can cap­ture da­ta on ath­letes' move­ments with a high de­gree of ac­cu­ra­cy. This da­ta can then be analysed us­ing ma­chine learn­ing al­go­rithms, al­low­ing coach­es and train­ers to iden­ti­fy even the slight­est de­vi­a­tions from the ide­al form or tech­nique.

With the help of re­al-time and ret­ro­spec­tive an­a­lyt­ics, coach­es and ath­letes can now mon­i­tor their per­for­mance dur­ing a game and make de­ci­sions on the fly with­out hav­ing to wait for post-game re­sults. This en­ables them to ad­just their strate­gies and plays in re­al time while track­ing and re­spond­ing to the op­po­si­tion's tac­tics. We're see­ing it in dif­fer­ent sports, par­tic­u­lar­ly crick­et and foot­ball with our na­tion­al teams even though it hasn't quite caught on with our do­mes­tic clubs.

At the 2022 ICC T20 World Cup, the tour­na­ment used AI for the first time to help with play­er se­lec­tion, per­for­mance analy­sis, and match pre­dic­tions. The AI sys­tem was used to help se­lect the squads for each team, tak­ing in­to ac­count a va­ri­ety of fac­tors such as play­er form, fit­ness, ex­pe­ri­ence, and past per­for­mance in T20 crick­et as well as match pre­dic­tions. Apart from that, AI was al­so used to help with the lo­gis­tics of the tour­na­ment. With so many teams and play­ers in­volved, it was im­por­tant to have a sys­tem in place that could help track every­thing in­clud­ing the sched­ul­ing of the match­es.

An ex­am­ple of the use of AI in foot­ball is the analy­sis of da­ta to im­prove play­er per­for­mance. Ma­chine learn­ing sys­tems are used to col­lect and analyse da­ta such as run dis­tance, speed, num­ber of pass­es, etc. This da­ta helps coach­es to make the right de­ci­sions about train­ing and prepa­ra­tion of play­ers. Trinidad and To­ba­go head coach An­gus Eve along with staff mem­ber Saron Joseph are get­ting more ac­cus­tomed to the sys­tem.

AI can al­so be used to cre­ate unique sport­ing events and games. AI can analyse play­er be­hav­iour, pre­dict pos­si­ble sit­u­a­tions and cre­ate sce­nar­ios that can sur­prise spec­ta­tors. Such games can be or­gan­ised both in re­al time and on­line to in­crease view­er­ship.

But AI has sig­nif­i­cant ben­e­fits in sports in­struc­tion, it al­so pos­es sev­er­al chal­lenges as out­lined in SportsEdTV. Over-re­liance on tech­nol­o­gy in sports in­struc­tion can have sev­er­al neg­a­tive con­se­quences. For ex­am­ple, sup­pose coach­es and train­ers re­ly too heav­i­ly on AI sys­tems for ath­lete as­sess­ment and feed­back. In that case, they may miss im­por­tant nu­ances in an ath­lete's per­for­mance that on­ly a hu­man coach could de­tect. This could lead to a lack of in­tu­ition and cre­ativ­i­ty in coach­ing, ul­ti­mate­ly lim­it­ing the ath­lete's po­ten­tial.

Ad­di­tion­al­ly, some ath­letes may not re­spond well to an AI-on­ly coach­ing ap­proach and may need more per­son­alised feed­back and emo­tion­al sup­port to thrive. More­over, re­ly­ing sole­ly on AI sys­tems can lim­it a coach's abil­i­ty to adapt to un­ex­pect­ed sit­u­a­tions.

Pri­va­cy and da­ta se­cu­ri­ty con­cerns are cru­cial chal­lenges when us­ing AI in sports in­struc­tion. Col­lect­ing da­ta on an ath­lete's per­for­mance and move­ments can be in­va­sive, and ath­letes may be con­cerned about how their da­ta is used and shared. For ex­am­ple, if AI sys­tems col­lect da­ta on an ath­lete's phys­i­cal abil­i­ties, it may re­veal per­son­al in­for­ma­tion that the ath­lete may not want to share. There are al­so some con­cerns about bias and fair­ness in us­ing AI in sports in­struc­tion. AI sys­tems may re­in­force ex­ist­ing bi­as­es or lim­i­ta­tions in train­ing meth­ods if the da­ta used to de­vel­op the sys­tem does not rep­re­sent a di­verse range of ath­letes. Coach­es and train­ers must be mind­ful of these lim­i­ta­tions and work to en­sure that the da­ta used to de­vel­op AI sys­tems is di­verse and rep­re­sen­ta­tive.

Ad­di­tion­al­ly, mo­ti­va­tion is one of the im­por­tant fac­tors in sports. Every ath­lete is en­cour­aged and dis­cour­aged by the words and ac­tions their coach­es tell them. Hu­man in­ter­ac­tion is es­sen­tial for build­ing trust and rap­port be­tween ath­letes and their coach­es or train­ers.

AI has been mak­ing in­roads in­to var­i­ous in­dus­tries and sec­tors, in­clud­ing sports, for sev­er­al decades. Its ori­gins date back to the 1950s when re­searchers be­gan to ex­plore whether ma­chines could mim­ic hu­man in­tel­li­gence. It has since evolved from rule-based mod­els to ex­pert sys­tems and ma­chine learn­ing. The speed of de­vel­op­ment in the last few years has seen an in­crease in us­age to en­hance sports for play­ers, coach­es and fans alike.

The true pow­er of AI is in aug­ment­ing hu­man ca­pa­bil­i­ties, not re­plac­ing them. It's im­por­tant for the in­dus­try to con­sid­er and ad­dress these chal­lenges to re­alise its po­ten­tial.

Lean in­to the new tech­nol­o­gy, AI can open up new job op­por­tu­ni­ties, such as AI de­vel­op­ment and man­age­ment, and let em­ploy­ees spend more time be­ing crit­i­cal and cre­ative. Fur­ther col­lab­o­ra­tion be­tween hu­mans and AI can bring new and in­no­v­a­tive ways to im­prove all ar­eas of sport. This is be­cause it has the po­ten­tial to bring to­geth­er the best of both worlds. AI can pro­vide teams with valu­able in­sights and pre­dic­tions; hu­mans can pro­vide con­text, cre­ativ­i­ty and de­ci­sion-mak­ing skills.

Shaun Fuentes is the head of TTFA Me­dia. He was a FI­FA Me­dia Of­fi­cer at the 2010 FI­FA World Cup in South Africa and 2013 FI­FA U-20 World Cup in Turkey. The views ex­pressed are sole­ly his and not a rep­re­sen­ta­tion of any or­gan­i­sa­tion. shaunfuentes@ya­hoo.com