Academic Edi o s: Al onso De la
Rubia Riaza and Moisés Ma quina
Recei ed: 4 Decembe 2024
Re ised: 8 Janua y 2025
Accep ed: 9 Janua y 2025
Published: 20 Janua y 2025
Ci a ion: De-la-C uz-To es, B.;
Na a o-Cas o, M.;
Ruiz-de-Ala cón-Quin e o, A.
Le e aging he Chain on Goals Model
in Foo ball: Applica ions o A ack
and De ensi e Play. Appl. Sci. 2025,
15, 998. h ps://doi.o g/
10.3390/app15020998
Copy igh : © 2025 by he au ho s.
Licensee MDPI, Basel, Swi ze land.
This a icle is an open access a icle
dis ibu ed unde he e ms and
condi ions o he C ea i e Commons
A ibu ion (CC BY) license
(h ps://c ea i ecommons.o g/
licenses/by/4.0/).
A icle
Le e aging he Chain on Goals Model in Foo ball: Applica ions
o A ack and De ensi e Play
Blanca De-la-C uz-To es 1,* , Miguel Na a o-Cas o 2and Anselmo Ruiz-de-Ala cón-Quin e o 3
1Depa men o Physio he apy, Uni e si y o Se ille, c/A icena s/n, 41009 Se ille, Spain
2
Depa men o Applied Ma hema ics I, E.T.S. o A chi ec u e, Uni e si y o Se ille, A d. Reina Me cedes s/n,
41012 Se ille, Spain
3Foo ball and Handball Academy, S ee n◦12B, o ice 6, 41960 Se ille, Spain; [email p o ec ed]
*Co espondence: bc [email p o ec ed]
Abs ac : In oduc ion: Foo ball analysis has expe ienced signi ican g ow h in ecen
yea s as an applied esea ch ield. This s udy aims o con ibu e o his a ea by applying
he chain on goals model o analyze bo h he a acking and de ensi e phases o oo ball
ma ches. Addi ionally, i in oduces ou p ac ical concep s o be e unde s and playe
and eam pe o mance in Spain’s p o essional oo ball leagues. Me hod: Da a o he
2023/24 season we e collec ed om Foo ball Re e ence, co e ing bo h men’s (LaLiga)
and women’s (LigaF) leagues. Va iables analyzed included eam pe o mance, a ack
and de ensi e pe o mance, goals sa ed abo e a e age (GSAA), goals and possession
alue (PV), expec ed goals (xG), and xG on a ge (xGOT) o a ack and de ensi e phases.
Fou p ac ical concep s analyzed we e o -ball mo emen (PV-xG), playe ’s o ensi e
quali y (xG-xGOT), eam’s posi ioning (PVA-xGA), and playe ’s de ensi e quali y (xGA-
xGOTA). Desc ip i e and compa a i e s a is ical analyses we e pe o med o compa e
all a iables be ween he wo leagues using an Independen S uden ’s es . Addi ionally,
co ela ion coe icien s we e calcula ed o examine he ela ionships be ween he ou
concep s. Resul s: Signi ican di e ences we e obse ed be ween leagues in de ensi e
pe o mance (p= 0.03) and GSAA (p< 0.001). P ac ical concep s e ealed dispa i ies in
o -ball mo emen and eam’s posi ioning (p< 0.001 in bo h). No co ela ions we e ound
be ween o -ball mo emen and playe ’s o ensi e quali y o be ween eam’s posi ioning
and playe ’s de ensi e quali y. Conclusions: The Spanish women’s league exhibi ed
de ensi e weaknesses, conceding mo e goals and showing lowe goalkeepe pe o mance.
PV was he mos in luen ial a iable in he women’s league, while xG was c i ical in he
men’s league.
Keywo ds: da a analysis; oo ball; expec ed goals on a ge ; pe o mance indica o s
1. In oduc ion
Foo ball da a analysis e e s o he p ocess o collec ing, p ocessing, and in e p e ing
s a is ical in o ma ion ela ed o oo ball ma ches, playe s, and eams o gain insigh s
ha can enhance pe o mance, decision-making, and s a egy. Wi h ad ancemen s in
echnology and da a science, oo ball da a analysis has become a c ucial ool o clubs,
coaches, and scou s o imp o e e e y hing om game ac ics o playe de elopmen [1,2].
In he ea ly days o oo ball, he use o da a was ex emely limi ed, o en e ol ing
a ound simple me ics such as goals sco ed, assis s, yellow and ed ca ds, sho s on a ge ,
o possession pe cen age [
3
]. Coaches elied on hei expe ience and in ui ion, while pe o -
Appl. Sci. 2025,15, 998 h ps://doi.o g/10.3390/app15020998
Appl. Sci. 2025,15, 998 2 o 11
mance assessmen s we e mos ly subjec i e. Tac ics we e de eloped based on obse a ion
a he han quan i iable me ics [3].
In he 1990s, oo ball saw a g owing in e es in s a is ical acking. The in oduc ion
o companies like Op a in 1996 ma ked a u ning poin [
4
]. These companies began o
eco d and analyze mo e de ailed aspec s o he game, such as passing accu acy, ackles
and in e cep ions, dis ance co e ed, o numbe o c osses and co ne s [
4
,
5
]. These da a
allowed clubs o s a making mo e in o med decisions abou playe pe o mances and
ma ch s a egies.
The ea ly 2010s ma ked he beginning o he Big Da a e olu ion in oo ball. Clubs
began o accumula e as amoun s o da a, no jus om ma ches bu also om aining
sessions. Simul aneously, he in oduc ion o ad anced s a is ical models e olu ionized
how pe o mance was measu ed, as hey highligh ed he ole o he sho , speci ically he
cha ac e is ics be o e and a e he sho [
6
–
10
]. These included expec ed goals (xG) [
11
,
12
]
o expec ed goals on a ge (xGOT) [
13
]. xG is a s a is ical me ic used in oo ball o measu e
he quali y o sco ing chances and he likelihood o a gi en sho esul ing in a goal. The
alue o his me ic assigned o a sho ep esen s i s “goal p obabili y” and is de e mined
by a ious ac o s such as he dis ance o he sho , he shoo ing angle, he ype o sho
(e.g., heade o s ike), he posi ioning o de ende s, and he play sequence leading up
o he a emp [
14
]. xG quan i ies he likelihood o a sho esul ing in a goal on a scale
om 0 o 1, whe e a highe xG alue indica es a g ea e p obabili y o sco ing [
9
,
10
]. In
con as , he expec ed goals on a ge (xGOT) me ic o e s a mo e de ailed analysis by
inco po a ing no only he quali y o he sco ing oppo uni y bu also he execu ion o he
sho i sel . xGOT assesses he p obabili y o a goal a e he sho has been aken and is on
a ge , conside ing ac o s such as sho placemen , powe , and he goalkeepe ’s posi ioning
and eac ion ime. This e inemen p o ide s xGOT a deepe laye o analysis, ocusing on
he in e play be ween shoo ing quali y and goalkeeping e ec i eness [13].
Following his app oach, in 2024, Ruiz-de-Ala cón-Quin e o and De-la-C uz-To es [
15
]
in oduced an analysis model ha emphasizes he p ocess o e he ou comes, aiming o
o e mo e comp ehensi e insigh in o playe s’ o eams’ pe o mance du ing a ma ch o
h oughou season. This model, e e ed o as he “chain on goals model”, di e s om o he
models by inco po a ing mul iple me ics ins ead o elying on a single one [
6
,
11
,
12
]. The
model was s uc u ed a ound ou p ima y me ics: goals sco ed, possession alue (PV),
xG, and xGOT. Each me ic unc ions as a link in a chain, wi h he model p emised on he
idea ha hese in e connec ed da a poin s collec i ely o m a comp ehensi e ep esen a ion
o pe o mance. Fu he mo e, he in eg a ed analysis o hese me ics o e s oppo uni ies
o de i e no el and insigh ul in o ma ion ele an o oo ball analy ics. This chain on goals
model was designed o p o ide a mo e p ecise e alua ion o playe and eam pe o mance
in oo ball ma ches. Using da a om he Spanish men’s and women’s oo ball leagues,
he s udy [
15
] e ealed ha xG and xGOT we e he me ics mos s ongly co ela ed wi h
ma ch ou comes, as hey closely aligned wi h goals sco ed. Such insigh s enable coaches o
iden i y he s eng hs and weaknesses o hei eams, speci ically be o e and a e he sho .
To da e, he scien i ic li e a u e on xG and xGOT me ics is limi ed [
9
,
11
,
16
–
18
], and his
emains he only a icle on he chain on goals model in oo ball. Mo e s udies applying his
model o aspec s o oo ball a e needed o assess i s b oade po en ial. The e o e, he aim o
his a icle was o p o ide a aluable con ibu ion by applying he chain on goals model o
bo h he a acking and de ensi e phases o a oo ball eam. Addi ionally, we in oduced
ou p ac ical concep s o enhance he unde s anding o playe and eam pe o mance
wi hin he con ex o Spanish oo ball leagues. Th ough his p ac ical in e p e a ion, he
model could o e coaches a signi ican compe i i e ad an age by enabling hem o iden i y,
wi h p ecision, he s eng hs and weaknesses o hei playe s and eams. These insigh s
Appl. Sci. 2025,15, 998 3 o 11
can be pinpoin ed ac oss a ious si ua ions: o ensi e o de ensi e phases, be o e o a e
sho on a ge , indi idual playe quali y, o o e a ching eam s a egies. By le e aging his
model, coaches can d i e meaning ul imp o emen s in pe o mance.
2. Ma e ials and Me hods
2.1. Sample
The sample in ol es analyzing da a om wo Spanish p o essional oo ball leagues,
LigaF (women’s i s di ision) and LaLiga (men’s i s di ision), o he 2023–2024 season.
The analysis co e s 30 ma chdays om LigaF and 38 ma chdays om LaLiga, using da a
sou ced om Foo ball Re e ence (www. b e .com (accessed on 20 Oc obe 2024)), which
elies on da ase s om Op a (S a s-Pe o m) (www. o mob.com (accessed on 20 Oc obe
2024)). As a as he au ho s a e awa e, hese da ase s a e p edominan ly inaccessible o
he b oade public [
18
,
19
]. O ganiza ions like Op a and S a s Bomb independen ly ga he
hese da a and dis ibu e hei indings exclusi ely h ough p op ie a y pla o ms. The
limi ed anspa ency, combined wi h he lack o insigh in o he algo i hms employed o
compu e hese me ics—a phenomenon o en e med “black-boxing”—hampe s he abili y
o ully unde s and and in e p e he p ocesses unde lying he gene a ion o speci ic me ic
alues. Howe e , hey ha e been alida ed and a e widely used in he oo ball analy ics
communi y [20,21].
2.2. Design and E hics Commi ee
A desc ip i e and compa a i e s udy was conduc ed. This in ol ed pe o ming
a compa a i e analysis o he end-o -season agg ega ed ma ch s a is ics collec ed o e a
compe i i e season om p o essional Spanish oo ball eams in bo h he men’s and women’s
leagues. The s udy ecei ed app o al om he local e hics commi ee o Uni e si y o
Se ille (p o ocol code 2024–1326 and da e o app o al 26 June 2024).
2.3. Me hodology
The s udy a iables we e g ouped in o h ee dimensions: o e all a iables ( eam
pe o mance, a ack pe o mance, de ensi e pe o mance, and goals sa ed abo e a e age),
me ics om he chain on goals model (goals, PV, xG, and xGOT o he a ack and de en-
si e phase), and ou p ac ical concep s (o -ball mo emen and playe ’s o ensi e quali y
o a ack phase, and eam’s posi ioning and playe ’s de ensi e quali y o de ensi e phase).
These concep s we e de eloped by he au ho s, d awing on hei ex ensi e expe ience o
o e 25 yea s as da a analys s in oo ball. The i s wo me ics o he phases co espond o
he eam’s s a egies, whe eas he la e wo me ics p o ide insigh s in o he indi idual
pe o mance o he playe s. The in eg a ed analysis o hese me ics p o ides oppo uni ies
o gene a e no el and insigh ul a iables, o e ing g ea e complexi y and ele ance o
oo ball analy ics. The au ho s p oposed ha hese concep s ep esen a p ac ical in e p e-
a ion o he s udied me ics, acili a ing a deepe unde s anding o coaches in e alua ing
bo h playe and eam pe o mance.
Table 1p esen s he de ini ions o he a iables o each dimension. Acco ding o ex-
pe s in oo ball analy ics, all esul s o each a iable om he i s and second dimensions
we e no malized pe ma ch (90 min) o enhance unde s anding and in e p e a ion. This
s anda diza ion is essen ial in da a analysis s udies in oo ball o enable compa ison o da a
ac oss di e en na ional leagues, as no all leagues ha e he same numbe o eams and, con-
sequen ly, ma ches. This is also ele an o in e na ional compe i ions, whe e eams do no
all play he same numbe o ma ches due o he a ying s uc u es o quali ica ion phases.
Appl. Sci. 2025,15, 998 4 o 11
Table 1. De ini ions o he a iables o each dimension.
Dimensions Va iables De ini ions
O e all
Team pe o mance A e age poin s pe ma ch
A ack pe o mance A e age o goals sco ed
pe ma ch
De ensi e pe o mance A e age o goals conceded
pe ma ch
Goals sa ed abo e
a e age (GSAA)
(xGOTA-de ensi e
pe o mance)
Goals expec ed o be conceded
by goalkeepe (GK) minus
ac ual goals conceded
Chain on
goals model
Goals
The o al numbe o goals
sco ed by he eam pe ma ch
du ing he season
Possession alue (PV)
The p obabili y o a eam
sco ing om hei possession
du ing he a ack phase
Expec ed goals (xG)
The quali y o a sho based on
his o ical da a, p o iding an
es ima e o how likely a sho is
o esul in a goal du ing he
a ack phase.
Expec ed goals on
a ge (xGOT)
The pos -sho quali y o
on- a ge e o s a goal du ing
he a ack phase
Possession alue
agains (PVA)
The p obabili y ha a eam will
allow i sel o be sco ed on
du ing i s de ensi e phase
Expec ed goals agains (xGA)
The p obabili y o a conceded
sho o become a goal du ing
you de ensi e phase.
Expec ed goals on a ge
agains (xGOTA):
The pos -sho quali y o he sho
a emp s conceded du ing i s
de ensi e phase
P ac ical concep s
O -ball mo emen (PV-xG)
The abili y o playe s no
ca ying he ball om he
a acking eam o o e a passing
solu ion o he eamma e.
Playe ’s o ensi e quali y
(xG-xGOT)
The abili y o a shoo e o sho
on a ge become a goal
a oiding goalkeepe opposi ion
Team’s posi ioning (PVA-xGA)
The ac ions pe o med by he
playe s o he de ending eam
on space agains hei
opponen s wi hou showing any
kind o ma king.
Playe ’s de ensi e quali y
(xGA-xGOTA)
The abili y o a de ende playe
o p e en a goal once ha he
a acke shoo
Appl. Sci. 2025,15, 998 5 o 11
2.4. S a is ical Analysis
The da a we e s a is ically analyzed using SPSS ( e sion 18; SPSS Inc., Chicago, IL,
USA). The Shapi o–Wilk es was used o pe o m no mali y analysis, and he esul
indica ed a no mal dis ibu ion. The s a is ical analysis pe o med a desc ip i e s udy o all
a iables exp essed as he a e age and he s anda d de ia ions, as well as he pe cen iles
(30 h and 70 h o LaLiga and 20 h and 80 h o LigaF). The di e ence in he calcula ion o
he pe cen iles be ween he men’s and women’s oo ball leagues is due o he ac ha he
women league has ewe eams and ewe compe i ions du ing he season.
Pea son co ela ion coe icien ( ) compa ed he in e ac ions be ween a iables and R2
analyzed he co ela ion be ween o - he-ball mo emen and playe ’s o ensi e quali y and
eam’s posi ioning and playe ’s de ensi e quali y. This in es iga ion applied he ollowing
c i e ia o de e mine he magni ude o he co ela ion ( ): <0.1 i ial, 0.1 o 0.3 small, 0.3 o
0.5 mode a e, 0.5 o 0.7 la ge, 0.7 o 0.9 e y la ge, and 0.9 o 1.0 almos pe ec .
Finally, a compa a i e s udy was conduc ed o compa e all a iables be ween bo h
leagues, using Independen S uden ’s - es . S a is ical signi icance was se a p< 0.05.
E ec sizes (Cohen’s d) we e also calcula ed o assess whe he he signi icance indings
also held p ac ical signi icance (small < 0.2; medium 0.5; and la ge > 0.8).
3. Resul s
Conside ing he de ini ions o he a iables p esen ed in Tables 1and 2illus a es
he dis ibu ion o alues ha we e calcula ed o all a iables men ioned along he en i e
season, including mean, s anda d de ia ion, and pe cen ile dis ibu ion, o bo h leagues.
In he o e all dimension only, de ensi e pe o mance (measu ed as he a e age numbe o
goals conceded pe ma ch) and GSAA showed s a is ically signi ican di e ences be ween
he wo leagues (p= 0.03 and d= −0.57; p< 0.001 and d = −1.26, espec i ely).
Table 2. The alues o he a iables o he o e all dimension and chain in goals model me ics
in each league. p alue o be ween-g oups s a is ical signi icance (Independen S uden ’s - es )
a e epo ed.
Va iable
LigaF LaLiga pValue LigaF LaLiga
Mean ±SD Mean ±SD Weakness Index
(20 h)
S eng h Index
(80 h)
Weakness Index
(30 h)
S eng h Index
(70 h)
Pe o mance 1.41 ±0.68 1.36 ±0.54 0.63 0.94 2.02 1.05 1.56
O ensi e
pe o mance 1.58 ±0.95 1.32 ±0.48 0.58 1.05 2.02 1.00 1.53
De ensi e
pe o mance −1.57 ±0.55 −1.32 ±0.33 0.03 −1.93 −0.97 −1.45 −1.17
GSAA −0.19 ±0.19 0.00 ±0.11 <0.001 −0.36 0.04 −0.08 0.06
PV 1.25 ±0.67 1.34 ±0.28 0.39 0.84 1.52 1.14 1.50
xG 1.39 ±0.74 1.30 ±0.31 0.83 0.95 1.69 1.12 1.37
xGOT 1.35 ±0.67 1.32 ±0.34 0.85 0.95 1.74 1.12 1.50
PVA −1.25 ±0.33 −1.34 ±0.18 0.50 −1.55 −1.03 −1.42 −1.24
xGA −1.39 ±0.40 −1.30 ±0.21 0.27 −1.64 −0.97 −1.434 −1.14
xGOTA −1.38 ±0.42 −1.32 ±0.25 0.30 −1.60 −0.93 −1.41 −1.14
Abb e ia ions: GSAA, goals sa ed abo e a e age; PV, possession alue; xG, expec ed goals; xGOT, expec ed goals
on a ge ; SD, s anda d de ia ion.
Table 3p esen s he e e ence alues o he ou p ac ical concep s in each league.
Signi ican di e ences we e obse ed only in o -ball mo emen (p< 0.001 and d = 1.31)
and eam’s posi ioning (p< 0.001 and d = −1.34) when compa ing he wo leagues.
Appl. Sci. 2025,15, 998 6 o 11
Table 3. The alues o he ou p ac ical concep s in each league. p alue o be ween-g oups
s a is ical signi icance (Independen S uden ’s - es ) a e epo ed.
Va iable
LigaF LaLiga pValue LigaF LaLiga
Mean ±SD Mean ±SD Weakness Index
(20 h)
S eng h Index
(80 h)
Weakness Index
(30 h)
S eng h Index
(70 h)
O -ball mo emen 0.14 ±0.12 −0.04 ±0.15 <0.001 0.05 0.24 −0.09 0.01
Playe ’s o ensi e
quali y −0.04 ±0.17 0.02 ±0.11 0.13 −0.17 0.10 −0.08 0.10
Team’s posi ioning −0.14 ±0.14 0.04 ±0.13 <0.001 −0.25 0.00 −0.06 0.12
Playe ’s de ensi e
quali y 0.01 ±0.08 −0.02 ±0.09 0.93 −0.07 0.05 −0.05 0.02
Fo LigaF, he co ela ion coe icien s be ween o - he-ball mo emen and playe ’s
o ensi e quali y we e =
−
0.1207 and R2 = 0.0146 and be ween eam’s posi ioning and
playe ’s de ensi e quali y we e =
−
0.1074 and R2 = 0.0115. Fo LaLiga, he co ela ion coe -
icien s be ween o - he-ball mo emen and playe ’s o ensi e quali y we e =
−
0.1324 and
R2 = 0.0175 and be ween eam posi ioning and playe ’s de ensi e quali y we e =
−
0.0280
and R2 = 0.008. In all cases, he le el o co ela ion was i ial. This implied ha he
p ac ical concep s o each phase o he game could be conside ed independen o one
ano he , ensu ing ha he weakness o s eng h o one phase did no in luence he o he s.
Figu es 1and 2es ablish he ela ionship o o -ball mo emen and playe ’s o ensi e
quali y and eam’s posi ioning and playe ’s de ensi e quali y o all eams in he women’s
and men’s leagues, espec i ely. F om hese igu es, he s eng hs and weaknesses o each
eam can be iden i ied, whe he in he de ensi e o a ack phase, a any gi en poin in ime
o a he conclusion o he season, as demons a ed in his s udy. In he de ensi e e alua ion
igu es, he x-coo dina e ep esen s he eam’s posi ioning, while he y-coo dina e ep e-
sen s he playe ’s de ensi e quali y. The e o e, a eam’s posi ion u he o he igh on he
x-coo dina e indica es be e eam’s posi ioning, while a posi ion u he o he le e lec s a
lowe posi ioning alue. On he y-coo dina e, an upwa d shi co esponds o highe playe
de ensi e quali y, whe eas a downwa d shi indica es lowe playe de ensi e quali y. In
he a ack e alua ion igu es, he x-coo dina e ep esen s he o -ball mo emen , while he
y-coo dina e ep esen s he playe ’s o ensi e quali y. Thus, g ea e o -ball mo emen is
indica ed by a posi ion u he o he igh on he x-axis, whe eas a posi ion u he o he
le e lec s lowe o -ball mo emen . On he y-axis, an upwa d shi co esponds o highe
playe o ensi e quali y, whe eas a downwa d shi indica es lowe playe o ensi e quali y.
Figu e 1. Con .
Appl. Sci. 2025,15, 998 7 o 11
Figu e 1. The ela ionship be ween he eam’s posi ioning wi h playe ’s de ensi e quali y (abo e)
and o -ball mo emen wi h playe ’s o ensi e quali y (below) o each eam in he women’s league.
Appl. Sci. 2025, 15, x FOR PEER REVIEW 8 o 12
Figu e 2. The ela ionship be ween eam’s posi ioning wi h playe ’s de ensi e quali y (abo e) and
off-ball mo emen wi h playe ’s offensi e quali y (below) o each eam in he men’s league.
4. Discussion
The da a om his s udy offe aluable expe imen al e idence ha can effec i ely
in o m he pe o mance o oo ball playe s and eams. Wi h ega d o he a iables p e-
sen ed in Table 1, he p ima y finding was he es ablishmen o e e ence alues o he
a iables ha cons i u e he chain on goals model in oo ball (Table 2), applicable o he
a8ack and de ensi e phases o eams in bo h he Spanish women’s and men’s oo ball
leagues. No ably, he e is simila i y be ween he wo leagues. Howe e , in he o e all di-
mension, he de ensi e pe o mance (a e age numbe o goals conceded pe ma ch) and
GSAA we e s a is ically diffe en when compa ing bo h leagues (p = 0.03 and p < 0.001,
espec i ely) (Table 2). These significan diffe ences had a medium and la ge effec size,
espec i ely. Rega ding de ensi e pe o mance, he au ho s concluded ha mo e goals
Figu e 2. The ela ionship be ween eam’s posi ioning wi h playe ’s de ensi e quali y (abo e) and
o -ball mo emen wi h playe ’s o ensi e quali y (below) o each eam in he men’s league.
Appl. Sci. 2025,15, 998 8 o 11
4. Discussion
The da a om his s udy o e aluable expe imen al e idence ha can e ec i ely
in o m he pe o mance o oo ball playe s and eams. Wi h ega d o he a iables p e-
sen ed in Table 1, he p ima y inding was he es ablishmen o e e ence alues o he
a iables ha cons i u e he chain on goals model in oo ball (Table 2), applicable o he
a ack and de ensi e phases o eams in bo h he Spanish women’s and men’s oo ball
leagues. No ably, he e is simila i y be ween he wo leagues. Howe e , in he o e all
dimension, he de ensi e pe o mance (a e age numbe o goals conceded pe ma ch) and
GSAA we e s a is ically di e en when compa ing bo h leagues (p= 0.03 and p< 0.001,
espec i ely) (Table 2). These signi ican di e ences had a medium and la ge e ec size,
espec i ely. Rega ding de ensi e pe o mance, he au ho s concluded ha mo e goals
we e conceded in he women’s league, indica ing a weake de ensi e sys em in his league.
Conce ning GSAA, his me ic analyzes he balance be ween GK pe o mance and shoo e
pe o mance. A posi i e GSAA ou come indica es ha he GK’s pe o mance is be e han
he shoo e ’s, whe eas a nega i e ou come sugges s he opposi e. I he GSAA alue is
“0”, i signi ies a neu al balance be ween GK and shoo e [
22
]. Ou da a e ealed ha he
men’s league was balanced, as he e was an equilib ium be ween he pe o mance o he
shoo e and he GK. In con as , he women’s league exhibi ed an imbalance, sugges ing a
poo e pe o mance by he GK.
Conce ning he second objec i e, he au ho s sough o p esen ou p ac ical con-
cep s based on he me ics o he chain on goals model, aimed a assis ing coaches and
echnical s a in be e unde s anding a eam’s ac ical pe o mance and ha o i s play-
e s (Table 3). Figu es 1and 2illus a ed he analysis and in e ela ionships o hese ou
concep s ac oss all p o essional eams in he Spanish league, bo h women’s and men’s,
du ing 2023–2024 season. One o he p ima y esponsibili ies o analys s is o ho oughly
examine he da a o e iew pe o mance me ics, enabling coaching s a o pinpoin a -
eas o imp o emen , such as missed oppo uni ies, de ensi e weaknesses, o necessa y
ac ical adjus men s [
23
]. The e o e, by analyzing hese concep s, we can disce n whe he
oo ball e o s s em om he eam’s s a egy o om indi idual playe quali y. Speci ically,
he concep s o “o -ball mo emen ” and “ eam’s posi ioning” p o ide insigh s in o he
eam’s s a egy, while “playe ’s o ensi e quali y” and “playe ’s de ensi e quali y” ela e
o he quali y o he indi idual playe s. No ably, he concep s de ining he de ensi e and
a ack phases showed a low co ela ion. The au ho s sugges ha his disc epancy a ises
because “o -ball mo emen ” and “ eam posi ioning” e lec he o e all s a egy o he
eam, whe eas “playe ’s o ensi e quali y” and “playe ’s de ensi e quali y” a e indica i e
o indi idual playe quali y. As a esul , he wo se s o concep s ope a e independen ly
om each o he . Cu iously, he wo me ics e lec ing in o ma ion abou eam s a egy
di e ed signi ican ly be ween he wo leagues (p< 0.001 in bo h cases), wi h a la ge e ec
size in bo h cases. Rega ding o -mo emen , he da a indica ed ha PV was mo e decisi e
in he women’s league, while xG was mo e c i ical in he men’s league. This inding aligns
wi h a p e ious s udy [
15
], which ound ha he p edic i e alue o PV in ela ion o ma ch
ou comes in he Spanish women’s league showed a s onge co ela ion han in he men’s
league. Conce ning eam’s posi ioning, he da a e ealed ha , om a collec i e pe spec i e,
he men’s league demons a ed be e de ensi e posi ioning han he women’s league. The
au ho s hypo hesize ha , while he oo ball pi ch dimensions a e he same o bo h leagues,
he physical dimensions o men and women playe s di e . Consequen ly, he abili y o
co e he playing ield du ing he de ensi e phase may be g ea e in he men’s league.
Based on hese indings, he di e ences be ween leagues iden i ied in he s udy may
be a ibu ed o he limi ed esou ces ha women’s leagues con inue o ace, including
Appl. Sci. 2025,15, 998 9 o 11
insu icien unding, a ia ions in s yle o play, physical p epa a ion, and o he ac o s, all
o which can in luence he le el o compe i ion.
The analysis o oo ball da a has p og essed om basic s a is ics o a powe ul ool
ha impac s e e y aspec o he game, including eam and playe pe o mance e alua ion
as well as in-ma ch decision-making [
1
]. This is why, while p e ious s udies ha e compa ed
success ul (winning) and unsuccess ul (losing) oo ball eams [
24
–
26
], his analysis o e s a
no el app oach by inco po a ing mo e ad anced me ics. This allows o a mo e in-dep h
e alua ion o he ac o s associa ed wi h spo ing success. This s udy p o ides aluable
e e ence alues om eli e oo ball clubs ha can aid in shaping ac ical s a egies (Tables 2
and 3). Simila o a p e ious s udy [
15
], his a icle es ablishes e e ence alues o model
me ics based on da a om op- ie clubs, such as hose in he Spanish men’s and women’s
leagues. The au ho s also p o ide a pe cen ile dis ibu ion o indica e e e ence alues
conside ed as s eng h indica o s (p70 o he men’s league and p80 o he women’s
league), cap u ing sco es o eams compe ing a he Eu opean le el by he inal ma chday.
Con e sely, alues iden i ied as indica o s o weakness (p30 o he men’s league and p20
o he women’s league) ep esen sco es o eams in elega ion posi ions o a lowe - ie
league by he las ma chday (Tables 2and 3).
4.1. Limi a ion Sec ion
The e a e se e al limi a ions o his s udy. (1) The da a used in his esea ch come
om one o Eu ope’s majo leagues, he Spanish socce league. The e o e, hese da a
should be conside ed indica i e and canno be gene alized. Applying his me ic o o he
Eu opean leagues o on a global scale could p o e o be insigh ul; (2) The esul s o his
s udy we e de i ed om a single da a p o ide ; howe e , he da a ha e been alida ed
and a e widely u ilized wi hin he oo ball analy ics communi y [
20
,
21
]; (3) The scien i ic
li e a u e ega ding his model and i s me ics is qui e limi ed. Fu he esea ch is equi ed
o apply hese new me ics o echnical and ac ical s a egies, which would be highly
bene icial o coaches and echnical s a ; (4) Today, he in o ma ion ob ained om he
applica ion o he chain on goals model is based on de ec ing s eng hs and weaknesses in
oo ball eams. S udies ha ela e his in o ma ion wi h oo ball solu ions o imp o ing
he pe o mance o eams and playe s a e necessa y; (5) The s udy was pe o med using a
s a ic me hod, as opposed o a dynamic app oach. Ne e heless, his s a ic me hod may
p o e o be pedagogically aluable o coaches in decision-making du ing ma ches [23].
4.2. P ac ical Applica ion
The da a e eal pa e ns o play ha help coaches e ine ac ics, such as exploi ing
weaknesses in he opponen ’s o ma ion, capi alizing on space c ea ed by opposing de end-
e s, and enhancing playe s’ skills o boos hei pe o mance. In ac , he Spanish men’s
league should p io i ize he de elopmen o i s o wa ds’ alen , jus as he women’s league
should ocus on enhancing he skills o i s GKs.
A de ailed analysis o he eams allows he au ho s o aise he ollowing e lec ions: In
LigaF, Se illa FC (SEV) eco ded he lowes sco es o bo h eam’s posi ioning and playe ’s
de ensi e quali y, indica ing poo de ensi e o ganiza ion and limi ed abili y o de ende s
o p e en goal-sco ing oppo uni ies. Coaches should ocus on imp o ing bo h he o e all
de ensi e s uc u e and he indi idual skills o de ende s o be e p e en sho s on goal.
Con e sely, Ba celona FC (FBC) achie ed a high sco e o o -ball mo emen bu a low
sco e o playe ’s o ensi e quali y, sugges ing ha he eam c ea es nume ous goal-sco ing
oppo uni ies bu s uggles o con e hem in o goals. Coaches should p io i ize enhancing
he shoo ing skills o shoo e s.
