RIAF Journal ISSN: 2953-6693 Vol – 4 No. 2, July 2026
90
Articles
Francisco Freyre Vázquez
Universidad de Holguín, Cuba
ffreyrev@uho.edu.cu
ORCID https://orcid.org/0000-0001-9553-0626
Helmer A. Méndez Infante
Universidad de Granma, Cuba
hmendezi@udg.co.cu
ORCID https://orcid.org/0000-0002-4407-3469
Abstract: The chest pass constitutes one of the
fundamental technical-tactical actions in modern
basketball. This research aimed to analyze the
parameters of strength and speed in the execution
of the chest pass in a sample of 7 defensive
position players (age: 20.2 years; height: 183 cm;
weight: 80 kg; sports age: 15 years). Arm strength
(dynamometry), ball flight time, pass distance, arm
fat area, and arm circumference were measured.
Ball speed was calculated using the formula v =
d/t, and applied force using F = m·a. Results
showed an average ball speed of 1.62 m/s, an
average applied force of 1.39 N, and an average
power of 4.16 W. Moderate correlations were
identified between arm strength and pass speed (r
= 0.50), as well as between pass speed and distance
achieved (r = 0.63). The coefficient of variation
was higher for ball speed (16.05%) than for arm
strength (7.85%), suggesting greater heterogeneity
in technical execution than in physical capacity. It
is concluded that specific training of upper body
explosive strength, complemented with adequate
body composition, could contribute to improving
the effectiveness of the chest pass in defensive
players.
Keywords: basketball; chest pass; defense; speed;
strength.
Force and Speed Analysis of the Chest Pass in Basketball: An Empirical
Investigation Involving Defensive Players
Francisco Freyre Vázquez
1
& Helmer A. Méndez Infante
2
RIAF. International Journal of Physical Activity
Universidad de Guayaquil, Ecuador
Frequency: Semi-Annual
Vol. 4, N° 2, 2026
revista.riaf@ug.edu.ec
Received: May 30th, 2026
Approved: July 1
st
, 2026
Published: July 25
th
, 2026
URL: https://revistas.ug.edu.ec/index.php/riaf
DOI: https://doi.org/10.53591/riaf.v4i2.3341
Authors who publish in RIAF acknowledge and accept the following
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RIAF Journal ISSN: 2953-6693 Vol – 4 No. 2, July 2026
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• 10 m tape measure with 0.01 m precision to
measure pass distance
• Digital stopwatch with ±0.01 s precision to
measure ball flight time
• Official basketball with a mass of 0.62 kg
• Anthropometric caliper to measure arm fat
area (cm) and brachial circumference (mm)
Procedure
The procedure was developed in three phases:
1. Familiarization phase: Players completed
a familiarization session with the
measurement protocol, performing 10
warm-up passes.
2. Measurement phase: Each player
performed 5 chest passes from a fixed
distance of 5 meters to a partner. The best
time of each player was recorded. The
actual pass distance was measured from
the release point to the reception point.
3. Recording phase: Arm strength (3
maximum attempts), arm fat area, and
brachial circumference were measured
following standardized protocols.
Calculations Performed
Ball velocity: 
Where is velocity (m/s), is distance (m),
and is flight time (s).
Ball acceleration:
󰇛 󰇜
Where   m (arm acceleration
distance).
Applied force:
Where  kg (ball mass).
Generated power: 󰇛½
󰇜
where
 s (estimated contact time).
Statistical Analysis
A descriptive statistical analysis (mean, median,
standard deviation, coefficient of variation,
minimum and maximum values) was performed
for all variables. For the study of relationships
between variables, Pearson's correlation
coefficient was applied. All calculations were
performed using Jamovi statistical software.
Results
The results of the application of instruments
and techniques and the corresponding analyses
are presented below.
Table 1.
Raw data of the 7 defensive players
Basketball
Players
Arm
Strength (kg)
Speed
(s)
Distance
(m)
Arm Fat
Area (cm)
Circumference
(mm)
1
60.0
3.0
5.10
25.4
10.6
2
55.5
3.2
5.20
26.6
10.4
3
50.0
3.0
6.25
20.4
18.8
4
50.0
4.0
5.08
16.3
18.3
5
50.0
4.0
5.28
18.9
17.6
6
55.0
3.3
5.30
23.1
17.3
7
60.0
3.2
5.54
8.8
18.9
X
54.36
3.39
5.39
19.93
15.99
SD
4.27
0.42
0.38
6.02
3.64
CV%
7.85
12.39
7.05
30.21
22.76
Min
50.0
3.0
5.08
8.8
10.4
Max
60.0
4.0
6.25
26.6
18.9
Legend. Mean. SD. CV (%). Minimum. Maximum
Analysis of Table 1: The sample is homogeneous in arm strength (CV = 7.85%) and pass distance
RIAF Journal ISSN: 2953-6693 Vol – 4 No. 2, July 2026
93
(CV = 7.05%). However, arm fat area shows high variability (CV = 30.21%), indicating significant
differences in body composition. Pass speed shows moderate variability (CV = 12.39%).
Table 2.
Ball speed by basketball player
Basketball
Players
Distance (m)
Time (s)
Speed (m/s)
Speed (km/h)
1
5.10
3.0
1.70
6.12
2
5.20
3.2
1.63
5.87
3
6.25
3.0
2.08
7.49
4
5.08
4.0
1.27
4.57
5
5.28
4.0
1.32
4.75
6
5.30
3.3
1.61
5.80
7
5.54
3.2
1.73
6.23
X
5.39
3.39
1.62
5.83
SD
0.38
0.42
0.26
0.94
CV%
7.05
12.39
16.05
16.12
Min
5.08
3.0
1.27
4.57
Max
6.25
4.0
2.08
7.49
Legend. Mean. SD. CV (%). Minimum. Maximum
Analysis of Table 2: The mean ball velocity was 1.62 m/s (5.83 km/h), with a coefficient of variation
of 16.05%, indicating moderate heterogeneity in pass execution. Player 3 achieved the highest velocity
(2.08 m/s), while players 4 and 5 presented the lowest (1.27 and 1.32 m/s respectively).
Table 3.
Applied force by player
Basketball
Players
Speed
(m/s)
Acceleration
(m/s²)
Force
(N)
Force
(kgf)
1
1.70
2.41
1.49
0.15
2
1.63
2.21
1.37
0.14
3
2.08
3.60
2.23
0.23
4
1.27
1.34
0.83
0.08
5
1.32
1.45
0.90
0.09
6
1.61
2.16
1.34
0.14
7
1.73
2.49
1.55
0.16
X
1.62
2.38
1.39
0.14
SD
0.26
0.72
0.44
0.05
CV%
16.05
30.25
31.65
35.71
Min
1.27
1.34
0.83
0.08
Max
2.08
3.60
2.23
0.23
Legend. Mean. SD. CV (%). Minimum. Maximum
Analysis of Table 3: The mean force applied to the ball was 1.39 N (0.14 kgf), with high variability
(CV=31.65%). Player 3 applied the greatest force (2.23 N), exceeding player 4 (0.83 N) by 168%. Players
1 and 7, despite having the greatest arm strength (60 kg), did not achieve the greatest applied forces,
indicating possible inefficiency in the transfer of static to dynamic strength.
RIAF Journal ISSN: 2953-6693 Vol – 4 No. 2, July 2026
94
Table 4.
Power generated by basketball players
Basketball players
Speed (m/s)
Kinetic Energy (J)
Power (W)
1
1.70
0.90
4.5
2
1.63
0.82
4.1
3
2.08
1.34
6.7
4
1.27
0.50
2.5
5
1.32
0.54
2.7
6
1.61
0.80
4.0
7
1.73
0.93
4.6
X
1.62
0.83
4.16
SD
0.26
0.27
1.32
CV%
16.05
32.53
31.73
Min
1.27
0.50
2.5
Max
2.08
1.34
6.7
Legend. Mean. SD. CV (%). Minimum. Maximum
Analysis of Table 4: The mean power generated was 4.16 W, with high variability (CV=31.73%). Player
3 achieved the greatest power (6.7 W), while player 4 obtained the lowest (2.5 W). Power depends on the
square of velocity; therefore, small differences in velocity generate large differences in power.
Table 5.
Correlation matrix (Pearson's r)
Variables
Arm
Strength
Pass Speed
Distance
Fat Area
Circumference
Arm Strength
1.00
0.50
0.54
-0.42
-0.38
Pass Velocity
0.50
1.00
0.63
-0.35
0.25
Distance
0.54
0.63
1.00
-0.12
0.21
Fat Area
-0.42
-0.35
-0.12
1.00
0.08
Circumference
-0.38
0.25
0.21
0.08
1.00
Analysis of Table 5: The strongest correlation was between pass velocity and distance (r=0.63,
moderate-strong positive). Arm strength showed moderate correlation with velocity (r=0.50) and distance
(r=0.54). The negative correlation between arm strength and fat area (r=-0.42) indicates that lower
adiposity is associated with greater strength.
Table 6.
Comprehensive performance ranking
Position
Basketball
Players
Arm
Strength
(kg)
Pass Speed
(m/s)
Distance
(m)
Fat Area
(cm)
Score
Z
1°
3
50.0
2.08
6.25
20.4
+1.4
2°
7
60.0
1.73
5.54
8.8
+1.0
3°
1
60.0
1.70
5.10
25.4
+0.2
4°
2
55.5
1.63
5.20
26.6
-0.1
5°
6
55.0
1.61
5.30
23.1
-0.2
6°
5
50.0
1.32
5.28
18.9
-1.0
7°
4
50.0
1.27
5.08
16.3
-1.3
RIAF Journal ISSN: 2953-6693 Vol – 4 No. 2, July 2026
95
Statistic
Arm Strength (kg)
Pass Speed
(m/s)
Distance
(m)
Fat Area
(cm)
Score
Z
X
54.36
1.62
5.39
19.93
0.0
SD
4.27
0.26
0.38
6.02
0.9
CV%
7.85
16.05
7.05
30.21
–
Min
50.0
1.27
5.08
8.8
-1.3
Max
60.0
2.08
6.25
26.6
+1.4
Legend. Mean. SD. CV (%). Minimum. Maximum
Analysis of Table 6: Player 3 demonstrated the best comprehensive performance (Z-score=+1.4),
excelling in pass velocity (2.08 m/s) despite not having the greatest arm strength (50 kg). Player 7 ranked
second (Z=+1.0), distinguished by low fat area (8.8 cm) and high strength (60 kg). Players 4 and 5
presented the lowest performances (Z=-1.3 and -1.0 respectively).
Table 7.
General statistical summary
Variable
Mean
SD
CV (%)
Minimum
Maximum
Age (years)
20.2
-
-
-
-
Sports age (years)
15.0
-
-
-
-
Size (cm)
183
-
-
-
-
Weight (kg)
80
-
-
-
-
Arm Strength (kg)
54.36
4.27
7.85
50.0
60.0
Pass Time (s)
3.39
0.42
12.39
3.0
4.0
Pass Distance (m)
5.39
0.38
7.05
5.08
6.25
Ball Velocity (m/s)
1.62
0.26
16.05
1.27
2.08
Ball Velocity (km/h)
5.83
0.94
16.12
4.57
7.49
Applied Force (N)
1.39
0.44
31.65
0.83
2.23
Applied Force (kgf)
0.14
0.05
35.71
0.08
0.23
Power (W)
4.16
1.32
31.73
2.5
6.7
Arm fat area (cm)
19.93
6.02
30.21
8.8
26.6
Circumference (mm)
15.99
3.64
22.76
10.4
18.9
Analysis of Table 7: The variables with the least variability were pass distance (CV=7.05%) and arm
strength (CV=7.85%), indicating homogeneity in these aspects. The variables with the greatest variability
were arm fat area (CV=30.21%), applied force (CV=31.65%), and power (CV=31.73%), suggesting
significant differences in body composition and capacity to generate explosive strength.
Discussion
The results obtained in the present study
evidence a complex relationship between
anthropometric variables, static strength, and
chest pass velocity in defensive position players.
The mean pass velocity found (1.62 m/s) is
considerably lower than values reported in the
international literature. Gómez et al. (2023), in
their kinematic analysis of the chest pass in elite
players, reported mean velocities between 6.5 and
8.2 m/s, far exceeding those found in this sample.
This difference may be explained by several
factors: the competitive level of the players
studied, the measurement methodology
RIAF Journal ISSN: 2953-6693 Vol – 4 No. 2, July 2026
96
employed, or the specific characteristics of the
defensive position that prioritizes other aspects of
the game over pass velocity. Król and Golaś
(2022) point out that measurement methods can
significantly influence the values obtained,
recommending the use of motion capture systems
for greater precision. A particularly interesting
finding is that player 3, with only 50 kg of arm
strength (below the mean of 54.36 kg), achieved
the greatest pass velocity (2.08 m/s) and distance
(6.25 m).
This result contradicts the initial expectation
that greater static strength directly translates to
greater pass velocity. Rojas-Valverde et al. (2021)
found similar results in their study on the effects
of complex training on pass velocity, noting that
technical efficiency and neuromuscular activation
capacity may be more determining than
maximum static strength. Liu and Zhang (2022)
complement this idea by demonstrating that
fatigue affects upper limb kinematics, suggesting
that intermuscular coordination is key to
maintaining pass velocity.
The moderate correlation between arm strength
and pass velocity (r=0.50) found in this study
coincides with that reported by Wang et al.
(2023), who, using inertial sensors, found
correlations of similar magnitude (r=0.45-0.55)
between isometric strength and throwing
velocity. These authors propose that the transfer
of static to dynamic strength depends largely on
the specificity of the sporting gesture, which
would explain why players with high arm strength
(players 1 and 7 with 60 kg) did not achieve the
greatest pass velocities.
Regarding body composition, a moderate
negative correlation was observed between arm
fat area and arm strength (r=-0.42), indicating
that players with lower adiposity tend to present
greater strength. Camué-Sánchez and
Hechavarría-Vinent (2023), in their study on
special exercises in youth basketball, highlight the
importance of maintaining adequate body
composition indices to optimize technical
performance. Player 7, with the lowest fat area
(8.8 cm) and high strength (60 kg), exemplifies
this relationship. On the other hand, arm
circumference showed a weak positive correlation
with pass velocity (r=0.25), suggesting that lean
muscle mass may contribute positively to velocity
generation, provided it is not accompanied by
excessive adiposity. Chow and Atencio (2021),
from a complexity theory perspective, argue that
skill acquisition such as passing does not depend
exclusively on isolated variables like strength or
velocity, but rather on the dynamic interaction of
multiple factors (technique, perception, decision-
making, physical condition). This approach
would explain why in our sample exists high
variability (CV=16.05% for velocity) despite
acceptable homogeneity in arm strength
(CV=7.85%).
Finally, Kato et al. (2021), in their three-
dimensional analysis of passing in basketball,
highlight that the defensive position has specific
requirements that may prioritize precision and
speed of execution over raw ball velocity. This
could partially justify the relatively low velocity
values found, suggesting that defensive players
might be sacrificing pass velocity in favor of other
parameters such as safety or placement.
Conclusions
1. The mean chest pass velocity in the
defensive players studied was 1.62 m/s,
with high interindividual variability
(CV=16.05%), identifying player 3 as
having the best performance (2.08 m/s)
and players 4 and 5 as having the lowest
RIAF Journal ISSN: 2953-6693 Vol – 4 No. 2, July 2026
97
performance (1.27 and 1.32 m/s
respectively), which evidences the need to
standardize execution technique within
the group
2. There is no direct and determining
relationship between static arm strength
and pass velocity, as demonstrated by
the case of player 3 (50 kg of strength)
who surpassed players 1 and 7 (60 kg of
strength) in velocity, suggesting that
technical and neuromuscular factors are
equally or more important than
maximum strength in chest pass
effectiveness.
3. Body composition influences pass
performance, evidenced by the negative
correlation between arm fat area and arm
strength (r=-0.42), and by the better
relative performance of player 7 (lower fat
area: 8.8 cm; high strength: 60 kg), which
recommends incorporating body
composition control as part of the
training process for defensive players.
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Declaration of conflicts of interest: The
authors declare no conflict of interest regarding
the contents of this work and its publication in
the journal RIAF.
Declaration of author participation:
Francisco Freyre Vásquez: Participated in the
elaboration of the theoretical systematization and
the construction of the introduction,
methodology, results of the study, and
bibliographic references.
Helmer A. Méndez Infante: Elaborated the
methodology, the applied empirical instruments,
the discussion, and conclusions.