Dilican, 2025
Ulusla a ası Sağlık, Egze siz e Spo Bilimle i De gisi, (2025)
In e na ional Jou nal o Heal h,
Exe cise, and Spo Sciences
(IJOSS) ISSN: 3023-8382
RESEARCH ARTICLE / A aş ı ma Makalesi Open Access/Açık E işim
IJOSS
© The Au ho (s), 2024. Open Access.
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Da aD i en T aining: Enhancing A hle ic Pe o mance h ough Wea able
Technologies and A i icial In elligence
Ve i-Odaklı An enman: Giyilebili Teknolojile e Yapay Zekâ ile Spo cu Pe o mansının Yüksel ilmesi
Tunay DİLİCAN1
Abs ac
This e iew examines he inc easingly p ominen concep o da a-d i en aining in
con empo a y spo s science, discussing he ole o wea able echnologies and a i icial
in elligence in enhancing a hle ic pe o mance. Based on he exis ing body o published
esea ch, he li e a u e indica es subs an ial ad ancemen s in pe o mance assessmen , load
managemen , and inju y p e en ion. The la ge da ase s gene a ed h ough wea able de ices
can be analysed h ough AI algo i hms, enabling he de elopmen o highly indi idualised
aining models. Howe e , pe sis en challenges------such as da a secu i y, e hical s anda ds,
algo i hmic bias, and inancial accessibili y------con inue o limi he widesp ead adop ion o hese
echnologies. The e iew emphasises he need o u u e sys ems o be de eloped in a mo e
anspa en , accessible, and e hically g ounded manne . Ul ima ely, da a-d i en app oaches
signal a new e a in mode n spo , one ha ex ends beyond pe o mance op imisa ion o
encompass sus ainabili y and a mo e human-cen ed model o a hle ic aining.
Keywo ds: A i icial in elligence, Pe o mance, T aining
Öz
Bu de leme, son yılla da spo biliminde gide ek önem kazanan e i-odaklı an enman anlayışını
incelemek e; giyilebili eknolojile e yapay zekâ uygulamala ının spo cu pe o mansının
geliş i ilmesindeki olünü a ışmak adı . Yayımlanmış çalışmala emel alına ak, li e a ü a aması
sonucunda pe o mans ölçümü, yük yöne imi e saka lık önleme konula ında önemli gelişmele
olduğu gö ülmüş ü . Giyilebili cihazla a acılığıyla elde edilen büyük e i se le i, yapay zekâ
algo i mala ıyla analiz edile ek bi eyselleş i ilmiş an enman modelle inin oluş u ulmasına
imkân anımak adı . Bununla bi lik e, e i gü enliği, e ik s anda la , algo i mik önya gı e maliye
gibi so unla , eknolojile in yaygın kullanımını sını lamak adı . Çalışma, gelecek e bu
eknolojile in daha şe a , e işilebili e e ik emelle e dayalı biçimde geliş i ilmesinin ge ekliliğini
u gulamak adı . Sonuç ola ak, e i odaklı yaklaşımla , mode n spo un sadece pe o mans
op imizasyonu değil, aynı zamanda sü dü ülebili lik e insan me kezli an enman anlayışı
açısından da yeni bi dönemi emsil e mek edi .
Anah a Kelimele : Yapay zeka, Pe o mans, An enman
h ps://www.ijoss.o g/A chi e/issue2- olume3/ijoss-Volume2-issue3-33.pd
*
Co espondence:
Tunay DİLİCAN
unaydilican86@ho mail.com
1Bu sa Uludağ Uni e s iy
/O cid ID: 0000-0003-4686-6849
e-pos a:
unaydilican86@ho mail.com
h ps://doi.o g/10.5281/zenodo.17583376
Recei ed / Gönde im: 08.08.2025
Accep ed / Kabul: 15.09.2025
Published / Yayın: 24.10.2025
Volume 2, Issue 3, Oc obe , 2025
Cil 2, Sayı 3, Ekim, 2025
Dilican, 2025.
In e na ional Jou nal o Heal h, Exe cise, and Spo Sciences Vol 2, issue 3, Oc obe
2025 Page 408 o 418
In oduc ıon
In con empo a y spo s science, a hle ic pe o mance is no longe con ined o ques ions
such as ‘‘how much an a hle e ains’’ o ‘‘how s ong he a hle e is.’’ Ins ead, pe o mance
is inc easingly unde s ood h ough da a-d i en app oaches ha inco po a e a wide
ange o a iables, including aining load, eco e y dynamics, biomechanical analysis,
and pe sonalised pe o mance s a egies. In his con ex , wea able echnologies and
a i icial in elligence---suppo ed analy ic sys ems ha e become c i ical ools o
moni o ing, op imising, and sus aining a hle ic pe o mance. This e iew aims o
examine how hese eme ging ools and me hodologies a e eshaping pe o mance
enhancemen , wha oppo uni ies and limi a ions hey p esen , and he di ec ions in
which he ield may e ol e in he coming yea s.
To begin wi h, he ise o wea able senso echnologies wi hin spo ing en i onmen s
is pa icula ly no ewo hy. T adi ionally, spo s scien is s and coaches ha e elied on
labo a o y measu emen s o ield obse a ions o assess physiological indica o s, such as
hea a e, oxygen consump ion, and muscle ac i a ion. In ecen yea s, howe e , he
in oduc ion o GPS uni s, accele ome e s, gy oscopes, biosenso s, and sma ex iles has
enabled he eal- ime collec ion and p ocessing o his da a du ing aining and
compe i ion. Fo ins ance, se e al s udies ha e epo ed ha wea able senso s can ack
hea a e, muscle ac i a ion, join angles, and g ound eac ion o ces, p o iding aluable
insigh s in o bo h pe o mance and inju y isk (Alzah ani & Ullah, 2024). Mo eo e , a
comp ehensi e e iew highligh ed he widesp ead use o wea able echnologies in
measu emen , moni o ing, aining, and ehabili a ion p ocesses, while also no ing key
challenges ela ed o accu acy, cos , e hics, and da a secu i y (Segu a e al., 2018).
The as da a gene a ed by hese sys ems holds signi ican po en ial when
in e p e ed h ough a i icial in elligence and machine lea ning ools. AI sys ems no
only collec and isualise aw da a bu also de elop p edic i e and p esc ip i e models
o suppo load managemen , aining op imisa ion, a igue p edic ion, and inju y- isk
assessmen (Valiye & Mahmudo a, 2025). In eam spo s, o example, AI-assis ed
analy ics pla o ms moni o aining loads, on- ield mo emen pa e ns, and eco e y
s a uses o educe inju y isk and enhance decision-making. This echnological
ans o ma ion encou ages spo scien is s o shi om a pu ely capaci y-based
pe spec i e owa d a cul u e o e idence-in o med decision-making.
Ne e heless, despi e he conside able p omise o hese echnologies, se e al
impo an limi a ions emain. Technical ac o s such as measu emen accu acy, spo -
speci ic alidi y, senso placemen , and en i onmen al condi ions may in oduce e o
o a iabili y in o he da a (Olsen e al., 2025). In addi ion, issues ela ed o da a secu i y,
use p i acy, and e hical go e nance ha e become inc easingly p ominen . Regula ions
conce ning he collec ion, s o age, and sha ing o a hle e da a a e s ill no ully
s anda dised ac oss global spo ing con ex s. These conside a ions unde sco e he
necessi y o bo h echnological e inemen and he de elopmen o obus e hical
amewo ks as he ield con inues o e ol e.
F om an a i icial in elligence pe spec i e, howe e , se e al issues-----such as he
opaci y o ‘‘black-box’’ algo i hms, model alidi y, and adap i e capaci y----- emain
subjec s o ongoing deba e. AI models a e ypically ained on la ge da ase s; ye , he
ex en o which hese models can be gene alised ac oss di e en a hle es, pe o mance
le els, o en i onmen al con ex s con inues o be an ac i e a ea o in es iga ion (Al ukhi
e al., 2025). In his ega d, he concep o da a-d i en aining should no be in e p e ed
me ely as he use o echnology; a he , i encompasses he in eg a ion o echnology
Dilican, 2025.
In e na ional Jou nal o Heal h, Exe cise, and Spo Sciences Vol 2, issue 3, Oc obe
2025 Page 409 o 418
wi h human expe ise. Ins ead, i encompasses a mul i-s age p ocess in which da a
collec ed om wea able senso s a e ans o med in o meaning ul aining p og ammes,
coaches and spo scien is s make in o med decisions, AI-assis ed ools a e in eg a ed
in o he aining cycle, and he ou comes o hese p ocesses a e con inuously moni o ed.
In o he wo ds, he co e componen s o his amewo k o m a cyclical sys em ha
in ol es da a collec ion, da a analysis, applica ion, and eedback. Th ough his sys em,
aining load can be adjus ed acco ding o indi idual a hle e cha ac e is ics, adap a ion
o aining s imuli may be accele a ed, and ul ima ely, pe o mance imp o emen s can
be acili a ed.
In conclusion, his e iew will i s examine he in luence o wea able echnologies
and a i icial in elligence on a hle ic pe o mance, ollowed by an explo a ion o how
hese app oaches may be in eg a ed in o aining p ocesses, including p ac ical
applica ions, cu en limi a ions, and eme ging ends. Th ough his comp ehensi e
syn hesis, he e iew aims o o e spo scien is s, coaches, echnology de elope s, and
esea che s an expanded and nuanced pe spec i e on he e ol ing landscape o
pe o mance op imisa ion.
Concep ual F amewo k
To con ex ualise he in e connec ed ole o da a acquisi ion, compu a ional analysis,
and applied decision-making in mode n pe o mance science, his e iew adop s an
in eg a ed concep ual amewo k. In his model, wea able senso s ope a e as p ima y
da a gene a o s, a i icial in elligence sys ems unc ion as analy ical engines ha ex ac
meaning ul pa e ns, and coaches ansla e hese insigh s in o ac ionable pe o mance
s a egies. This iadic syne gy demons a es ha pe o mance op imisa ion eme ges
no om echnology alone, bu om he coo dina ed alignmen o measu emen
p ecision, analy ical in elligence, and applied spo expe ise.
As he in eg a ion o wea able echnologies and a i icial in elligence con inues o
expand, he ela ionship be ween da a quali y, model eliabili y, and p ac ical
applicabili y becomes inc easingly impo an . The e ec i eness o hese sys ems
depends no only on he accu acy o he collec ed da a bu also on he capaci y o
coaches, analys s, and spo scien is s o in e p e and con ex ualise hese ou pu s wi hin
eal aining en i onmen s. Thus, echnological inno a ion alone is insu icien ; ins ead,
i mus be accompanied by a comp ehensi e unde s anding o a hle e-speci ic demands,
aining p inciples, and physiological adap a ion mechanisms. Es ablishing his syne gy
be ween echnology and applied spo science c ea es a ounda ion upon which mo e
p ecise, indi idualised, and sus ainable pe o mance s a egies can be de eloped.
Key De ini ions
Fo concep ual cla i y, se e al key e ms used h oughou his e iew wa an explici
de ini ion. Wea able echnologies e e o senso -based de ices ha con inuously
cap u e physiological, biomechanical, o en i onmen al da a du ing aining o
compe i ion. A i icial in elligence encompasses compu a ional sys ems capable o
lea ning om da a and p oducing p edic i e o p esc ip i e ou pu s. Machine
lea ning-----a subse o AI-----is conce ned wi h algo i hms ha de ec unde lying pa e ns
in complex da ase s and e ine hei p edic ions o e ime. Da a-d i en aining deno es
a me hodological app oach in which aining decisions a e in o med by empi ical
e idence a he han in ui ion alone
Dilican, 2025.
In e na ional Jou nal o Heal h, Exe cise, and Spo Sciences Vol 2, issue 3, Oc obe
2025 Page 410 o 418
Ma e ials and Me hods
This s udy is a na a i e e iew aimed a compiling and syn hesising he cu en
scien i ic li e a u e on da a-d i en aining, wea able echnologies, and a i icial
in elligence applica ions in enhancing a hle ic pe o mance. The pu pose o he e iew
is o iden i y ecen esea ch de elopmen s in his ield, ou line eme ging ends, and
highligh he oppo uni ies and challenges encoun e ed in p ac ical applica ions. To his
end, pee - e iewed a icles, sys ema ic e iews, me a-analyses, epo s, and academic
heses published in Tu kish and English we e examined.
The li e a u e sea ch was conduc ed h ough PubMed, Scopus, Web o Science,
Google Schola , and Resea chGa e da abases. Du ing he sea ch p ocess, he ollowing
keywo ds we e used: “da a-d i en aining,” “wea able echnologies in spo s,” “a i icial
in elligence and a hle ic pe o mance,” “spo s analy ics,” “load managemen ,” and
“pe o mance moni o ing.”
Inclusion C i e ia
The ollowing c i e ia we e conside ed o inclusion:
Di ec ele ance o a hle ic pe o mance, aining managemen , o inju y
p e en ion;
Inco po a ion o wea able echnologies o AI-based analy ical me hods;
Publica ion in ei he English o Tu kish.
Resea ch Design
This s udy employed a na a i e (desc ip i e) e iew design. Unlike sys ema ic
e iews, he aim o na a i e e iews is no o es a speci ic hypo hesis bu a he o
summa ise, in e p e , and syn hesise exis ing indings wi hin he li e a u e in a hema ic
manne .
The esea ch design consis ed o h ee main s ages:
1. Li e a u e Sea ch
A sys ema ic sea ch o he a o emen ioned da abases was conduc ed, and he i les,
abs ac s, and ull ex s o he e ie ed s udies we e e iewed.
2. Da a Ex ac ion and Classi ica ion
Eligible s udies we e coded based on:
ype o esea ch (e.g., expe imen al, obse a ional, e iew),
ype o echnology used (e.g., GPS, accele ome e , a i icial in elligence,
machine lea ning),
spo discipline (e.g., oo ball, unning, swimming),
Mo eo e , epo ed pe o mance ou comes (e.g., endu ance, speed, load
managemen , inju y incidence).
3. Thema ic Syn hesis
The s udies we e syn hesised unde he ollowing hema ic ca ego ies:
Technological applica ions,
Dilican, 2025.
In e na ional Jou nal o Heal h, Exe cise, and Spo Sciences Vol 2, issue 3, Oc obe
2025 Page 411 o 418
Da a analy ics and a i icial in elligence app oaches,
Pe o mance moni o ing and load managemen ,
P ac ical limi a ions in applied se ings,
And e hical conside a ions.
This esea ch design enabled he e iew o encompass a b oad ange o li e a u e
while also iden i ying eme ging pa e ns and di ec ions ha may guide u u e esea ch
in his apidly de eloping ield.
Da a Analysis
In his e iew, he da a ex ac ed om he included s udies we e e alua ed using a
quali a i e con en analysis app oach. Ra he han applying quan i a i e s a is ical
p ocedu es, he key concep s, me hodological app oaches, epo ed ou comes, and
esea ch ends highligh ed in each s udy we e sys ema ically compa ed and analysed.
Each s udy was examined in ela ion o i s p ima y a iables, including:
he ype o wea able de ice used (e.g., GPS, hea - a e moni o s, EMG
senso s),
he pe o mance pa ame e s measu ed (physiological, biomechanical,
echnical– ac ical),
he a i icial in elligence o machine lea ning me hods implemen ed,
Mo eo e , he epo ed ou comes a e ela ed o pe o mance enhancemen
o isk educ ion.
These codes we e subsequen ly me ged in o b oade hema ic ca ego ies, om
which o e a ching ends in he ield we e iden i ied. The hema ic analysis
indica ed h ee majo pa e ns:
eal- ime da a acking and pe sonalised aining app oaches,
machine lea ning–based pe o mance p edic ion models,
Mo eo e , conside a ions ela ed o da a p i acy, e hics, and p ac ical
limi a ions mus also be aken in o accoun .
This analy ical p ocess p o ided he ounda ion o he de ailed discussion
o each heme p esen ed in he subsequen sec ions o he e iew.
Findings
Recen echnological ad ancemen s in spo s science—pa icula ly he eme gence o
wea able senso echnologies and AI-suppo ed analy ical me hods—ha e posi ioned
hese ools as c i ical ins umen s o moni o ing, op imising, and sus aining a hle ic
pe o mance. In his sec ion, he ise and applica ions o wea able echnologies in spo s
will be examined i s , ollowed by an explo a ion o how a i icial in elligence and
machine lea ning app oaches con ibu e o his domain. Finally, he combined
oppo uni ies and challenges ha a ise om he in eg a ion o bo h app oaches will be
analysed.
Dilican, 2025.
In e na ional Jou nal o Heal h, Exe cise, and Spo Sciences Vol 2, issue 3, Oc obe
2025 Page 412 o 418
Wea able Technologies and A hle ic Pe o mance
Wea able senso s include de ices such as GPS uni s, accele ome e s, gy oscopes,
hea - a e moni o s, and in elligen ex iles. Th ough hese ins umen s, a hle es’
physiological a iables (e.g., hea a e, oxygen consump ion), biomechanical pa ame e s
(e.g., join angles, muscle ac i a ion), and load- ela ed me ics (e.g., g ound eac ion
o ce, accele a ion) can now be moni o ed in eal ime o wi h minimal delay du ing bo h
aining sessions and compe i i e en i onmen s. Fo example, a sys ema ic e iew
in es iga ing wea able de ices in spo s such as ield hockey ound no able a iabili y in
measu emen accu acy ac oss de ices, al hough o e all u ilisa ion has been s eadily
inc easing (La ino & Ta u i, 2024).
F om he pe spec i e o achie ing small ye cumula i ely meaning ul pe o mance
gains, he ole o wea able echnologies has been widely discussed in he li e a u e. One
s udy ca ego ised wea able de ices in o h ee p ima y g oups: loca ion-based wea ables,
biome ic wea ables, and pe o mance-moni o ing wea ables. This classi ica ion is
aluable o coaches and spo scien is s, as i cla i ies which ypes o senso da a a e
associa ed wi h speci ic pe o mance ou comes (Migliaccio e al., 2024).
The ad an ages o e ed by wea able senso s in aining load managemen ha e also
been highligh ed. Resea ch has shown ha a iables such as o al loading, numbe o
di ec ion changes, and acu e- o-ch onic wo kload a ios a e equen ly assessed in
spo s en i onmen s whe e hese echnologies a e employed (Rebelo e al., 2023).
Acco ding o ecen epo s, wea able echnologies ha e become a g owing end
wi hin he i ness and spo s science sec o s, wi h hei global ma ke size p ojec ed o
each $ 186 billion by 2030 (Dohe y e al., 2024). Despi e his apid expansion, he
li e a u e also documen s se e al echnical and p ac ical limi a ions, including issues
ela ed o measu emen accu acy, spo -speci ic alidi y, senso placemen ,
en i onmen al condi ions, da a connec i i y, and he in e p e a ion o senso ou pu s.
S udies ha e u he demons a ed subs an ial in e -indi idual a iabili y in senso -
de i ed da a, emphasising he need o pe sonalised app oaches (Baldassa i e al., 2023).
Al hough wea able echnologies a e widely ecognised as powe ul ools o a hle e
moni o ing and aining managemen , hei p ac ical use depends on ca e ul
conside a ion o ac o s such as alida ion, s anda disa ion, and use compliance. These
elemen s emain essen ial o ensu ing ha wea able sys ems yield eliable and ac ionable
pe o mance insigh s.
A i icial In elligence and Machine Lea ning App oaches
The la ge olumes o da a gene a ed by wea able senso s a e no inhe en ly meaning ul
on hei own; his is whe e a i icial in elligence (AI) and machine lea ning (ML)
echniques become essen ial. These echnologies enable aw da a o be ans o med in o
ac ionable insigh s, allowing o he de elopmen o p oac i e s a egies in a eas such as
load managemen , a igue p edic ion, and inju y- isk assessmen . Fo ins ance, a
comp ehensi e e iew epo ed ha AI- and ML-based app oaches ha e made
signi ican ad ancemen s in spo s science, pa icula ly in inju y o ecas ing,
pe o mance analysis, and pe sonalised aining p og amme design (Reis e al., 2024).
Ano he s udy examined he applica ions o AI wi hin spo ing con ex s, including
Dilican, 2025.
In e na ional Jou nal o Heal h, Exe cise, and Spo Sciences Vol 2, issue 3, Oc obe
2025 Page 413 o 418
he challenges associa ed wi h e hical conside a ions and da a quali y, as well as
eme ging u u e di ec ions (Zhou e al., 2025). Speci ically, ML algo i hms a e
inc easingly used o analyse mo emen pa e ns, enabling ea ly de ec ion o a igue o
heigh ened inju y isk. In one in es iga ion, high-dimensional da a de i ed om
wea able senso s we e p ocessed using AI echniques o iden i y biomechanical isk
ac o s, demons a ing he po en ial p ac ical alue o such analyses (Musa e al., 2024).
Howe e , se e al ba ie s s ill hinde he b oade adop ion o AI in spo . These
include he opaci y o “black-box” algo i hms, a iabili y in da a quali y, and e hical
conce ns such as da a p i acy and algo i hmic bias. The e o e, AI- and ML-suppo ed
pe o mance analy ics equi e mo e han he me e implemen a ion o ad anced
echnologies; hey also necessi a e ensu ing ha hese sys ems a e eliable, alid,
e hically go e ned, and compa ible wi h end-use needs. This highligh s he impo ance
o in eg a ing echnological sophis ica ion wi h obus me hodological and e hical
amewo ks o maximise he p ac ical u ili y o AI in high-pe o mance spo .
In eg a ion o Wea able Technologies and A i icial In elligence: Pe o mance
Enhancemen and Sus ainabili y
In ecen yea s, he in eg a ion o a i icial in elligence and wea able echnologies has
eme ged as a ans o ma i e app oach wi hin spo s science, o e ing subs an ial
po en ial o enhancing pe o mance and imp o ing aining e iciency. Wea able
de ices—such as GPS-based sys ems, accele ome e s, EMG senso s, and hea - a e
moni o s—collec eal- ime physiological and biomechanical da a, which a e
subsequen ly analysed h ough AI algo i hms o gene a e pe sonalised pe o mance
models (Li & Washing on, 2024). This in eg a ion enables coaches o adop da a-d i en
decision-making p ocesses, acili a ing mo e p ecise managemen o key pe o mance
pa ame e s.
One o he mos signi ican ad an ages o AI-suppo ed wea able sys ems is hei
abili y o con e complex da ase s in o meaning ul insigh s. Machine lea ning
algo i hms, in pa icula , can iden i y pa e ns wi hin la ge olumes o da a o p edic
a iables such as aining load, inju y isk, o eco e y s a us, and can p o ide
pe sonalised ecommenda ions acco dingly (An, 2025). Fo example, s udies conduc ed
in p o essional oo ball and a hle ics ha e demons a ed ha hese sys ems can achie e
accu acy a es exceeding 85% in p edic ing aining loads.
Howe e , exis ing esea ch also highligh s se e al limi a ions conce ning he
sus ainable use o hese echnologies. Issues such as da a secu i y, economic accessibili y,
and he lack o long- e m alida ion o many de ices ep esen p ominen challenges.
S udies ha e no ed ha e hical conside a ions and da a bias in AI-suppo ed spo s
echnologies emain pa ly un esol ed, and ha algo i hmic bias may in oduce e o s
in o pe o mance assessmen s (Olyasanab & Annabes ani, 2024). Mo eo e , he
sus ainabili y o hese sys ems depends no only on hei echnical pe o mance bu also
on use compliance and he obus ness o da a-p i acy p o ocols.
A u he conce n ela es o economic easibili y. Many o he cu en AI-in eg a ed
wea able sys ems equi e high-cos ha dwa e and con inuous cloud-based da a-
p ocessing in as uc u es. This c ea es accessibili y ba ie s, pa icula ly o you h
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a hle es, ama eu leagues, and inancially cons ained clubs. Consequen ly, u u e
esea ch may bene i om p io i ising he de elopmen o mo e inclusi e, cos -e ec i e,
and anspa en sys ems ha ensu e da a secu i y while emaining p ac ical o a b oade
ange o use s.
Explici Resea ch Gaps
Despi e p omising ad ancemen s in wea able echnologies and AI-d i en analy ics,
se e al pe sis en esea ch gaps emain. Many s udies ely on na ow samples, sho -
e m obse a ions, and limi ed da a di e si y, which es ic he gene alisabili y o hei
esul s. Addi ionally, ew in es iga ions examine how hese echnologies pe o m unde
a ying en i onmen al condi ions, in di e en compe i i e le els, o ac oss di e se spo
disciplines. This lack o me hodological b ead h limi s ou unde s anding o long- e m
adap a ion, algo i hmic obus ness, and eal-wo ld applicabili y.
Gaps in he Li e a u e and Fu u e Di ec ions
Al hough he exis ing li e a u e highligh s he conside able po en ial o in eg a ing
wea able echnologies and a i icial in elligence o enhancing a hle ic pe o mance,
mos s udies emain a he pilo s age o a e limi ed o speci ic spo s disciplines
(Samped o, 2023). Resea ch examining he e hical dimensions o hese echnologies
indica es ha issues such as da a owne ship and in o med consen om a hle es a e
equen ly o e looked in p ac ice, which may jeopa dise a hle es’ long- e m
psychological and legal igh s. Addi ionally, he di e si y and quali y o da a used in AI-
based pe o mance analysis emain limi ed. A comp ehensi e e iew no ed ha
insu icien da a di e si y pe sis s as a signi ican challenge in many spo s- ela ed AI
sys ems, ul ima ely es ic ing he gene alisabili y o he algo i hms. Consequen ly,
u u e esea ch may bene i om he adop ion o mo e he e ogeneous samples and
mul imodal da a sou ces—such as senso -based measu emen s, ideo analysis, and
en i onmen al pa ame e s (Radanlie , 2025).
Me hodological gaps also exis conce ning long- e m pe o mance moni o ing and
sus ainable adap a ion. Many echnological s udies conduc ed on a hle es a e es ic ed
o sho - e m expe imen al designs, despi e e idence ha aining adap a ion un olds
o e ex ended pe iods, o en spanning se e al yea s (Ca on & Dalbo, 2025). This c ea es
a me hodological ba ie o a comp ehensi e unde s anding o he long- e m impac o
wea able echnologies on pe o mance de elopmen .
Looking owa d u u e di ec ions, AI-assis ed sys ems a e expec ed o play an
inc easingly p ominen ole in pe sonalised aining and p edic i e heal h moni o ing.
In pa icula , he in eg a ion o eal- ime senso da a wi h cloud-based AI sys ems may
enable a hle es o op imise aining load mo e e ec i ely and an icipa e inju y isk wi h
g ea e accu acy. A he same ime, he es ablishmen o in e na ional s anda ds
conce ning e hics, p i acy, and da a ai ness will likely se e as a c i ical de e minan o
he u u e adop ion and scalabili y o hese echnologies.
S uc u ed Di ec ions o Fu u e Resea ch
Fu u e esea ch may bene i om adop ing mo e igo ous and mul idimensional
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app oaches. Longi udinal coho s udies could cla i y how a hle es adap o AI-assis ed
aining o e ex ended pe iods, while mul imodal da ase s—in eg a ing senso da a,
ideo analy ics, and con ex ual a iables—may enhance ecological alidi y.
Technological de elopmen s in explainable AI, edge compu ing, and decen alised da a
go e nance could imp o e anspa ency and secu i y. E hically, in e na ionally aligned
s anda ds conce ning consen , p i acy, and algo i hmic ai ness will be c ucial o
ensu ing esponsible deploymen .
Human–AI In e ac ion in Pe o mance Decision-Making
Al hough AI sys ems p o ide sophis ica ed p edic i e capabili ies, decision-making in
high-pe o mance en i onmen s mus emain undamen ally human-cen ed. Coaches
in e p e algo i hmic ou pu s h ough con ex ual knowledge, expe ien ial judgemen ,
and a hle e-speci ic nuances ha compu a ional models canno ully eplica e. Thus, AI
should se e no as a eplacemen o expe insigh bu as an augmen a i e ool ha
enhances a coach’s abili y o de ec sub le pe o mance de ia ions, manage unce ain y,
and design pe sonalised aining s a egies.
Limi a ions o This Re iew
This e iew is subjec o ce ain limi a ions. The li e a u e sea ch was es ic ed o
speci ic da abases and o s udies published in English and Tu kish, which may ha e
excluded ele an esea ch in o he languages. As a na a i e e iew, he syn hesis does
no ollow he s ic me hodological p o ocols o sys ema ic e iews, in oducing he
possibili y o selec ion bias. Fu he mo e, he e ogenei y ac oss s udy designs limi s
di ec compa abili y. These limi a ions highligh he need o mo e sys ema ic and
longi udinal in es iga ions.
Conclusion
This e iew examined con empo a y ends in he use o wea able echnologies and
a i icial in elligence applica ions o moni o ing, e alua ing, and enhancing a hle ic
pe o mance. The li e a u e sugges s ha da a-d i en app oaches ha e signi ican ly
con ibu ed o pe o mance gains in bo h p o essional and ama eu spo s. In pa icula ,
he accu acy o AI-based sys ems in eal- ime da a collec ion, load managemen , and
inju y- isk p edic ion has s eadily imp o ed. Wea able de ices possess he capaci y o
measu e no only physical pe o mance indica o s bu also physiological and
psychological eedback, he eby o e ing no able po en ial o pe sonalising aining
p ocesses.
Ne e heless, issues such as da a secu i y, e hical esponsibili y, algo i hmic bias, and
use p i acy emain un esol ed. These conce ns unde sco e he need o obus e hical
and legal amewo ks o accompany echnological ad ancemen s. Addi ionally, he
exis ing li e a u e e eals ha many s udies ely on sho - e m pilo applica ions and a e
limi ed in scope o speci ic spo disciplines. This p esen s a me hodological challenge
o assessing he long- e m e ec s o AI and wea able sys ems on a hle ic de elopmen .
P ac ical Implica ions o Applied Se ings
