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The effects of bowling lines and lengths on the spatial distribution of successful power-hitting strokes in international men’s one-day and T20 cricket

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This study examined 503 power-hitting strokes that resulted in the maximum of 6-runs being scored in international men’s one-day and T20 cricket. Chi-Squared analyses were conducted to determine if performance and situational variables were associated with the distribution (direction) of aerial power-hitting strokes. Results revealed that bowling length, bowling line, bowler type and powerplays were all significantly (p < 0.001) associated with ball-hitting distribution. Post-hoc analysis of the standardised residuals revealed that greater than expected 6ʹs were scored behind square and were associated with short-pitched bowling, fast bowling and the power-play. Similarly, bowling the half-volley length and the outside off line resulted in greater than expected 6ʹs on the off-side. The results suggest that bowlers should try to avoid offering width outside the off stump as well as bowling the half-volley and short-pitched lengths as these bowling lines and lengths present batters with greater opportunities to score maximum runs. Fast bowling is revealed to be more susceptible to power-hitting strokes than spin bowling. Conversely, batters may wish to target the areas behind square or on the off-side for opportunities to score maximum runs, and they should look to take full advantage of the powerplay field restrictions.
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The effects of bowling lines and lengths on the
spatial distribution of successful power-hitting
strokes in international men’s one-day and T20
cricket
Mikael Jamil, Samuel Kerruish, Marco Beato & Stuart A. McErlain-Naylor
To cite this article: Mikael Jamil, Samuel Kerruish, Marco Beato & Stuart A. McErlain-Naylor
(2022): The effects of bowling lines and lengths on the spatial distribution of successful power-
hitting strokes in international men’s one-day and T20 cricket, Journal of Sports Sciences, DOI:
10.1080/02640414.2022.2148074
To link to this article: https://doi.org/10.1080/02640414.2022.2148074
© 2022 The Author(s). Published by Informa
UK Limited, trading as Taylor & Francis
Group.
Published online: 21 Nov 2022.
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SPORTS PERFORMANCE
The eects of bowling lines and lengths on the spatial distribution of successful
power-hitting strokes in international men’s one-day and T20 cricket
Mikael Jamil
a
, Samuel Kerruish
a
, Marco Beato
a
and Stuart A. McErlain-Naylor
a,b
a
School of Health and Sports Sciences, University of Suffolk, Ipswich, UK;
b
School of Sport, Exercise and Health Sciences, Loughborough University,
Loughborough, UK
ABSTRACT
This study examined 503 power-hitting strokes that resulted in the maximum of 6-runs being scored in
international men’s one-day and T20 cricket. Chi-Squared analyses were conducted to determine if
performance and situational variables were associated with the distribution (direction) of aerial power-
hitting strokes. Results revealed that bowling length, bowling line, bowler type and powerplays were all
signicantly (p < 0.001) associated with ball-hitting distribution. Post-hoc analysis of the standardised
residuals revealed that greater than expected 6ʹs were scored behind square and were associated with
short-pitched bowling, fast bowling and the power-play. Similarly, bowling the half-volley length and the
outside o line resulted in greater than expected 6ʹs on the o-side. The results suggest that bowlers
should try to avoid oering width outside the o stump as well as bowling the half-volley and short-
pitched lengths as these bowling lines and lengths present batters with greater opportunities to score
maximum runs. Fast bowling is revealed to be more susceptible to power-hitting strokes than spin
bowling. Conversely, batters may wish to target the areas behind square or on the o-side for opportu-
nities to score maximum runs, and they should look to take full advantage of the powerplay eld
restrictions.
ARTICLE HISTORY
Received 20 May 2022
Accepted 10 November 2022
KEYWORDS
Batting; boundary;
performance analysis; ball
direction; powerplay; aerial
shots
Introduction
Cricket is an international team sport that is played between
two teams that comprise of batters and bowlers, all of whom
will be required to contribute to elding (Scanlan et al., 2016).
The objectives of batters include scoring runs and protecting
their wickets (not getting out), whereas the objectives of their
opposing bowlers are to restrict the number of runs they con-
cede, whilst also attempting to take the wickets of their oppos-
ing batters (Douglas & Tam, 2010). This dynamic interaction
between bowler and batter is further complicated by rules
which inuence eld restrictions, commonly known as power-
plays, where only a select number of elders are permitted
outside of the 30-yard markings on the playing eld (ICC,
2021a, 2021b). Throughout the contest between batter and
bowler, batters will exhibit a repertoire of attacking and defen-
sive strokes, whilst facing a range of bowling styles commonly
consisting of either fast or spin bowling variations (Mehta et al.,
2022; Sarpeshkar & Mann, 2011; R. A. Stretch et al., 2000).
Previous studies have revealed many key performance indica-
tors for batters in cricket including their ability to clear the
boundary, which is considered a major contributor to success
in limited overs cricket (Douglas & Tam, 2010; Irvine & Kennedy,
2017; Petersen, 2017; C. Petersen et al., 2008).
Limited overs international cricket exists in two forms, the
50-over One Day International (ODI) format and the 20-over,
International Twenty20 (IT20) form (ICC, 2021a, 2021b).
Research has suggested that the shorter T20 format has made
the game more physically challenging for both batters and
bowlers, primarily as this format necessitates a higher rate of
run-scoring and stroke play (Scanlan et al., 2016). In turn, this
has increased the pressure upon bowlers to maintain accuracy
and thereby diminished their margins for error (Douglas & Tam,
2010). Similarly, greater demands have been placed upon bat-
ters as this format necessitates more frequent high-intensity
actions, such as running and sprinting (C. J. Petersen et al.,
2010). As argued by Scanlan et al. (2016), these diering
game formats could impose unique requirements upon
players.
Whilst previous research has investigated the technique
factors associated with greater power hitting distance by bat-
ters (McErlain-Naylor, Peploe et al., 2021; Peploe et al., 2018,
2019) and greater ball speed (Felton & King, 2016; Felton et al.,
2020; Ramachandran et al., 2021) and spin (L. Sanders et al.,
2018, 2019) by bowlers, it should be acknowledged that “opti-
mal” batting or bowling performance is a result of many con-
tributing factors including technical, tactical, and contextual
aspects (McErlain-Naylor, King et al., 2021; McErlain-Naylor,
Peploe et al., 2021). Furthermore, the inter-dependency of the
batter–bowler interaction (Chris Peploe et al., 2014; Mcerlain-
naylor et al., 2020; Sarpeshkar et al., 2017) has been relatively
overlooked in previous studies, where batting or bowling have
been analysed in isolation. As stated by Petersen (2017), ball-
hitting distribution relative to the pitch is partly dependent on
the intention and accuracy of the bowler with regards to the
line and length of their delivery. Evidence of the inter-
dependent bowler–batter interaction has been noted in
CONTACT Mikael Jamil m.jamil2@uos.ac.uk School of Health and Sports Sciences, University of Suffolk, Ipswich, Suffolk, United Kingdom
JOURNAL OF SPORTS SCIENCES
https://doi.org/10.1080/02640414.2022.2148074
© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/),
which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
previous research. For example, ball trajectory has been
revealed to impact batters pre-impact movement (Sarpeshkar
et al., 2017). In addition, bowlers’ delivery methods have been
revealed to inuence batters’ response times, particularly when
playing front-foot strokes (Chris Peploe et al., 2014). Similarly,
Mcerlain-naylor et al. (2020), discovered that delivery method
and associated pre-release visual cues aected upper body
kinematics of batters when playing both front and back-foot
batting strokes. Postural cues in the bowler’s delivery stride as
they approach the crease have also been revealed to inuence
a batter’s anticipation of events (Williams & Jackson, 2019).
Taking the above into consideration, the purpose of this
study is to examine how bowling line and length can impact
the direction of successful power-hitting batting strokes in
international level limited overs cricket. This study will focus
exclusively on aerial batting strokes that resulted in 6-runs
being scored, the maximum available to any batter whilst
facing a bowling delivery. Furthermore, this study will deter-
mine whether other factors such as competition format (ODI or
IT20), eld restrictions (powerplays), bowling hand (left or right)
or bowling variations (fast, medium or spin) are associated with
power-hitting distributions.
Methods
Data and design
Data on successfully executed power-hitting strokes were com-
piled across two international men’s tournaments, the ICC
Men’s One-Day International World Cup 2019 and the ICC
Men’s International T20 World Cup 2016. Secondary data
were obtained from Opta (London, UK) and high levels of
reliability have been previously reported (Jamil et al., 2021).
The original sample consisted of 590 aerial power-hitting
strokes that resulted in a maximum of 6-runs being scored.
Eighty-seven of these strokes were removed from the sample
due to them being coded as “top-edge” – unintentional strokes
often executed successfully by chance (Khan et al., 2017). These
“edges” are not traditional, controlled cricket shots and often
present wicket taking opportunities to the elding team (Khan
et al., 2017; Regan, 2012). Consequently, these strokes were
excluded from the nal sample in order to maintain the focus
of this study on intentional power hitting and subsequent
recommendations. This resulted in a nal sample size of
(n = 503) controlled (assumed deliberate) aerial power-hitting
strokes, each of which resulted in 6-runs being scored. The data
set consisted of variables including: bowling line; bowling
length; bowling hand; bowling type; competition format; and
power-play (see, Table 1 for denitions). The eects of each of
these variables upon post-impact ball-distribution were
examined.
In the primary analyses, all 503 strokes were categorised as
landing (post-batter connection) either behind square or in-
front of square (Figure 1). In the secondary analyses, the cricket
pitch was divided into three segments and all strokes were
categorised as either ZONE 1, ZONE 2 or ZONE 3. The angles
of ball distribution were mirrored for right-handed and left-
handed batters (Figure 2). Figures 3 and 4 present an illustra-
tion of the bowling length and line categorisations analysed in
this study, respectively. Ethical approval for this study was
obtained by the ethics committee of the local institution.
Statistical analysis
Chi-Squared
2
) tests of independence were conducted to
determine whether there was any association between
Table 1. Definitions list for all variables provided by the data supplier.
Variable Definition
Bowling
Length*
Back of
a Length
A delivery short of a good length, but fuller than a short ball, which the batsman would ordinarily look to play off the back foot.
Full Toss A delivery that reaches the batsman in his normal stance without pitching.
Half Volley An over-pitched delivery between a good length and a Yorker.
Length Ball A delivery of a good length. This is a length that can put the batsman in two minds whether to play the ball off the front or back foot.
Short Ball A delivery which is well short of a length. For a quicker bowler this is likely to be a bouncer and for a slow bowler it will ordinarily be
a ball which has been dragged down.
Bowling
Line*
Down Leg When the ball pitches outside leg stump (but makes contact with the batter/bat and hence cannot be coded as a wide down leg
side).
Leg Stump When the ball pitches partially or wholly on the leg stump
Middle
Stump
When the ball pitches partially or wholly on the middle stump
Off Stump When the ball pitches partially or wholly on the off stump
Outside Off When the ball pitches outside off stump (but makes contact with the batter/bat and hence cannot be coded as a wide outside the off
side).
Bowler Hand Right Right handed bowlers
Left Left handed bowlers
Bowler Type Fast Seam
+
Typically, a bowler who regularly delivers their stock ball at high delivery speeds
Leg Spin Bowling, which typically deviates from the leg side to the off side after pitching
Medium
Seam
+
Typically, seam bowlers who do not achieve high delivery speeds when delivering their stock ball
Off-Spin Bowling, which typically deviates from the off side to the leg side after pitching
Power Play Yes Power play fielding restrictions are being enforced
No Power play fielding restrictions are not being enforced
Competition 50 Over 50 over format cricket
20 Over 20 over format cricket
*: Bowling Length and Bowling Line data were approximations and not based on XY tracking data – a highly specialised purpose designed grid system is utilised to
collect this data.
+: Speed data is not based on ball tracking data
2M. JAMIL ET AL.
Right Handed Batters
(outer circle)
Left Handed Batters
(inner circle)
Batter X
Bowler O
0°
180°180°
Behind Square
In-Front of Square
X
O
0°
Figure 1. Ball distribution angles for both right (red) and left (blue) handed batters, behind and in-front of square.
Batter X
Bowler O
30°
150°
270°
ZONE 1 Wicketkeeper arc
ZONE 2 Off-Side ZONE 3 Leg-Side
X
O
30°
150°
270°
ZONE 1 – Wicketkeeper arc
ZONE 3 – Leg-Side
X
O
ZONE 2 – Off-Side
Left-handed batter Right-handed batter
Figure 2. Ball distribution angles for left (blue) and right (red) handed batters, in all 3 (120°) zones .
JOURNAL OF SPORTS SCIENCES 3
power-hitting direction frequency and each of the indepen-
dent variables detailed above. Each ball bowled that resulted
in the maximum of 6-runs being scored (n = 503), contributed
to one and only one cell in each of the χ
2
tests conducted in
this study. The values of the cell expected counts were greater
than 5 for at least 80% of all expected count cells, and no
expected count value was less than 1 (McHugh, 2013). In cases
where 2 × 2 contingency tables were formed, the Fisher’s
Exact test were conducted (McHugh, 2013). In the event of
statistically signicant (p < 0.05) χ
2
test results, standardised
residuals were calculated to identify the specic cells making
the greatest contribution to the chi-square test result and thus
determine the source of the signicant result (Sharpe, 2015).
Bonferroni corrections were applied to account for the rela-
tively large number of cells present in the contingency tables
(Sharpe, 2015) and the associated critical values are presented
in Table 2. Cramer’s V eect sizes were also calculated
(McHugh, 2013) and interpreted with the thresholds of 0.1
small < 0.3, 0.3 moderate < 0.5, and strong 0.5 (Cohen,
1988). All statistical analyses were performed using IBM SPSS
(SPSS Statistics for Macintosh, Version 25.0. Armonk, NY: IBM
Corp).
Results
Primary analysis behind or in-front of square
Bowling length was signicantly associated with ball distribu-
tion for successful aerial power hitting strokes (p< 0.001), with
a moderate eect size (V = 0.382; Table 3). The type of bowler
was signicantly associated with ball distribution (p < 0.001),
with a small eect size (V = 0.248). Finally, the powerplay overs
were also revealed to be signicantly associated with ball
Length Half volley
(Approx. 2-5 metres)
(Good) Length ball
(Approx. 5-8 metres)
Back of a length
(Approx. 8-10 metres)
Short ball
(Approx.10+ metres)
ssoTlluF ecnuobtonseodllaB( )
Leg
Side
Off
Side
Figure 3. An illustration of bowling lengths analysed in this study. Bowling length data were not based on xy co-ordinates, but were approximations. Measurements are
approximate distances from the stumps. Furthermore, heights at which the ball arrives at the batter are also approximations. (Image presents a right-handed batter).
Figure 4. An illustration of bowling lines analysed in this study.
Table 2. Critical values used for Bonferroni adjusted p-values.
Variable Primary Analysis Secondary Analysis
Bowling Length ± 2.81 ± 2.94
Bowling Line - ± 2.94
Bowling Type ± 2.73 ± 2.86
Powerplay ± 2.50 ± 2.64
4M. JAMIL ET AL.
distribution (p < 0.001; V = 0.239, small). No signicant associa-
tions were discovered between shot distribution and bowling
line, bowling hand or competition format.
Post-hoc analysis of the standardised residuals (Table 4;
associated critical values are reported in Table 2) revealed
that short-pitched bowling, such as the short-ball (standardised
residual value 5.7) and the back of a length ball (3.0), resulted in
signicantly greater than expected (i.e., expected by chance)
successful aerial power-hitting strokes behind square. The half-
volley, the fullest pitched ball to reveal signicant eects,
resulted in signicantly fewer than expected 6-run scoring
strokes behind square (−3.6). Fast bowlers were revealed to
concede signicantly more than expected power-hitting
strokes behind square (3.4). Finally, signicantly more than
expected power-hitting strokes were played behind square
during the powerplay overs (4.4). No other signicant eects
were reported.
Secondary analysis 120
°
zones
Bowling length was signicantly associated with ball-hitting
distribution (p < 0.001; V = 0.338, moderate; Table 3). Bowling
Table 3. Chi – square test results and effects sizes.
Variable χ
2
p-value
(Primary Analysis) Cramer’s V χ
2
p-value
(Secondary Analysis) Cramer’s V
Bowling Length 73.445 < 0.001* 0.382 57.418 < 0.001* 0.338
Bowling Line 6.749 0.150 0.116 32.291 < 0.001* 0.253
Bowler Hand 0.591 0.442 0.034 1.548 0.461 0.055
Bowler Type 30.905 < 0.001* 0.248 16.746 0.010* 0.129
Power Play 28.778 < 0.001*
+
0.239 14.350 < 0.001* 0.169
Competition 2.469 0.120 0.070 3.500 0.174 0.083
*: Significant at p < 0.05, + Results of a Fisher Exact Test reported due to 2 × 2 contingency table.
Table 4. Observed counts (Expected counts) and standardised residual values – direction of the 6 (Primary analysis).
Behind Square Standardised Residual In-Front of Square Standardised Residual Total
Bowling
Length
Back of a Length 28 (15.9) 3* 63 (75.1) −1.4 91
Full Toss 3 (5.9) −1.2 31 (28.1) 0.6 34
Half Volley 2 (17) −3.6* 95 (80) 1.7 97
Length Ball 26 (38.7) −2.0 195 (182.3) 0.9 221
Short Ball 29 (10.5) 5.7* 31 (49.5) −2.6 60
Total 88 415 503
Bowler Type Fast Seam 69 (46) 3.4* 194 (217) −1.6 263
Leg Spin 6 (16.6) −2.6 89 (78.4) 1.2 95
Medium Seam 7 (8.6) −0.5 42 (40.4) 0.2 49
Off Spin 6 (16.8) −2.6 90 (79.2) 1.2 96
Total 88 415 503
Power Play No 56 (73.1) −2.0 362 (344.9) 0.9 418
Yes 32 (14.9) 4.4* 53 (70.1) −2.0 85
Total 88 415 503
*: Significant at Bonferroni corrected p-values (see critical values in Table 2).
Table 5. Observed counts (Expected counts) and standardised residual values – direction of the 6 (Secondary analysis).
Zone 1
(31–150) Standardised Residual
Zone 2
(151–270) Standardised Residual
Zone 3
(271–30) Standardised Residual Total
Bowling
Length
Back of a Length 7 (5.1) 0.9 9 (20.3) −2.5 75 (65.7) 1.2 91
Full Toss 2 (1.9) 0.1 4 (7.6) −1.3 28 (24.5) 0.7 34
Half Volley 0 (5.4) −2.3 40 (21.6) 3.9* 57 (70) −1.6 97
Length Ball 8 (12.3) −1.2 53 (49.2) 0.5 160 (159.5) 0.0 221
Short Ball 11 (3.3) 4.2* 6 (13.4) −2.0 43 (43.3) 0.0 60
Total 28 362 113 503
Bowling Line Down Leg 4 (3.4) 0.3 3 (13.6) −2.9* 54 (44) 1.5 61
Leg Stump 4 (2.1) 1.4 2 (8.2) −2.2 31 (26.7) 0.8 37
Middle Stump 2 (3.3) −0.7 12 (13.1) −0.3 45 (42.6) 0.4 59
Off Stump 6 (4.2) 0.9 12 (16.9) −1.2 58 (54.8) 0.4 76
Outside Off 12 (15) −0.8 83 (60.1) 3.0* 175 (194.9) −1.4 270
Total 28 362 113 503
Bowler Type Fast Seam 24 (14.6) 2.4 57 (58.6) −0.2 182 (189.8) −0.6 263
Leg Spin 0 (5.3) −2.3 19 (21.2) −0.5 76 (68.6) 0.9 95
Medium Seam 3 (2.7) 0.2 12 (10.9) 0.3 34 (35.4) −0.2 49
Off Spin 1 (5.3) −1.9 24 (21.4) 0.6 71 (69.3) 0.2 96
Total 28 362 113 503
Power Play No 16 (23.3) −1.5 96 (93.1) 0.3 306 (301.7) 0.2 418
Yes 12 (4.7) 3.3* 16 (18.9) −0.7 57 (61.3) −0.6 85
Total 28 362 113 503
*: Significant at Bonferroni corrected p-values (see critical values in Table 2).
JOURNAL OF SPORTS SCIENCES 5
line was also signicantly associated with the direction of 6-run
scoring strokes (p < 0.001; V = 0.253, small). Bowler type was
revealed to be signicantly associated with the direction of
aerial power-hitting strokes (p = 0.010; V = 0.129, small).
Finally, power-play was signicantly associated with the direc-
tion of the 6-run scoring strokes (p < 0.001; V = 0.169, small). No
signicant associations were discovered between shot distribu-
tion and bowling hand or competition format.
Post-hoc analysis of the standardised residuals (Table 5;
associated critical values are reported in Table 2) revealed
that the short-ball resulted in greater than expected 6-run
scoring strokes in ZONE 1 (4.2), representing the 120
°
arc
behind the wicketkeeper. The half-volley resulted in greater
than expected 6-run scoring strokes in ZONE 2 (3.9), which
represent the o-side for both right-handed and left-handed
batters. Bowling down the leg-side also resulted in fewer than
expected 6-run scoring strokes in ZONE 2 (−2.9). Bowling out-
side o stump on the other hand resulted in greater than
expected 6-run scoring strokes in ZONE 2 (3.0). Finally, signi-
cantly greater than expected power-hitting strokes were played
in ZONE 1 during the powerplay overs (3.3). No other signicant
eects were reported.
Discussion
This study aimed to investigate factors aecting the directional
distribution of aerial 6-run scoring power-hitting strokes in
international men’s cricket. Results revealed that bowling
length, bowling line, bowler type and powerplays all signi-
cantly aected the post-impact direction of the ball, although
bowling line was only revealed to have a signicant eect in
the secondary analyses when the playing surface was divided
into smaller zones. Of all variables analysed, bowling length
was revealed in this study to have the greatest impact upon the
distribution of power hitting strokes with medium eects all
other variables were revealed to have small eects. The hand-
edness of the bowler nor the competition format had any
signicant association with ball-hitting distributions in elite-
level cricket according to the results of this study.
The primary analysis revealed that shorter pitched bowling
resulted in greater than expected 6-run scoring strokes behind
square. Corresponding results were discovered in the second-
ary analysis where greater than expected 6-run scoring strokes
were performed in ZONE 1, the 120
°
arc behind the wicket-
keeper. Previous research has revealed that the short-pitched
delivery is the least eective wicket-taking delivery (Najdan
et al., 2014), however bowlers often tend to bowl it as
a means of intimidating the batter by targeting the upper
body (Kendall & Lenten, 2017). The results obtained in this
study suggest that batters are responding to the short-
pitched delivery with deliberate and controlled shots behind
square of the wicket. Previous research has revealed that short
bowling lengths that pitched 8+ metres away from the batters’
stumps elicited an initial back-foot movement by the batters
(Pinder et al., 2012). Therefore, the results of this study suggest
that batters are successfully executing shots such as the “hook”
and “late cut” shots (Khan et al., 2017). Both of these strokes are
back-foot shots that enable the batter to judge the trajectory of
the ball (Khan et al., 2017). The hook shot in particular is
a common response from a batter to a short pitched delivery
bowled by a pace bowler (O’Donoghue, 2016). Both of these
shots are considered high risk, for poorer performance out-
comes (R. A. Stretch et al., 2000) as they require batters to
play across the line of the ball, often with a near horizontal
bat (Khan et al., 2017). This additional risk demonstrated by
batters could be partly due to modern day limited overs cricket
necessitating greater urgency for attacking play and run scor-
ing strokes (Scanlan et al., 2016). Results also revealed that
bowling the half-volley length resulted in greater than
expected 6ʹs in ZONE 2, representing the o-side. This nding
does correspond with that of previous research that has dis-
covered the half-volley length to be particularly susceptible to
power-hitting strokes (Taliep et al., 2010). Furthermore, in their
study on the existence of monostable/metastable zones for
batters in cricket, Pinder et al. (2012), discovered fuller bowling
lengths between 2.5 and 3.5 metres away from the batters
stumps elicited a primary forward movement from opposing
batters. In addition, fuller bowling lengths have been revealed
to encourage front foot attacking strokes such as the “drive”
(Chris Peploe et al., 2014; Connor et al., 2020; Sarpeshkar &
Mann, 2011). This particular stroke is frequently played in-
front of square, to an over-pitched bowling delivery and is
one of the most common shots to be performed (R. Stretch
et al., 1998). It should be noted that balls that pitched on the
“yorker” length (approx. 0–2 metres away from the batters’
stumps) did not result in any 6-run scoring shots across the
two tournaments analysed in this study (explaining why this
length was not represented in the corresponding contingency
table). This reinforces the ndings of previous research that the
yorker length is generally regarded as being the hardest length
for batters to strike (Moore et al., 2012).
Bowling line was also revealed to signicantly aect the ball
distribution of 6-run scoring power strokes, but only in the
secondary analyses. Interestingly, only bowling deliveries out-
side of the line of the three stumps (o, middle and leg) were
revealed to signicantly aect ball distribution. Previous
research with a focus on the accuracy of bowling deliveries
has revealed that bowling within the line of the stumps can
restrict a batter’s ability to score runs (Phillips et al., 2012). In
their study, Phillips et al. (2012) regarded both the base and the
top of the o stump as ideal targets for bowlers to aim for.
Similarly, three out of ve targets in a study by Feros et al.
(2013) were situated at the top of each stump, with a fourth
target halfway up the middle stump. The results of the bowling
line variable also revealed ZONE 2 to be of particular interest.
Specically, bowling with “outside-o” lines resulted in greater
than expected 6-run strokes in this region on the o-side. This is
likely due to the o-side line encouraging o-side shots such as
the drive strokes detailed above as well as the “square cut” also
frequently played on the o-side (Khan et al., 2017). Fewer than
expected 6ʹs in ZONE 2 were scored with bowling deliveries of
a “down-leg” line. This is perhaps to be expected, as the down-
leg line would take the ball away from ZONE 2.
The type of bowler also aected ball distribution, with fast
bowlers being struck for greater than expected 6ʹs behind
square. These results conform with previous ndings that pace
on the ball allows batters to accumulate runs behind the wicket,
particularly if they are capable of re-directing the ball and thus
6M. JAMIL ET AL.
using the bowler’s speed of delivery to their advantage (Renshaw
& Holder, 2010). Another potential reason why fast seam bowling
may be susceptible to power hitting strokes behind square,
could be due to modern day batters more frequently performing
innovative shots such as the “ramp shot” (Portus & Farrow, 2011)
or, the “Dilscoop” (Dixit, 2018; Mann & Dain, 2013). Both the ramp
and the dilscoop are aerial (often premeditated) shots, which
target the vacant area behind the wicketkeeper and slip elders
(Mann & Dain, 2013). The creation of such strokes has been due
partly to the emergence of T20 cricket, which has led to batters
learning new techniques in order to score faster (Edgar, 2020).
Finally, greater than expected 6ʹs were struck within the
powerplay overs. These results suggest batters are taking more
risks in the powerplay overs, which have been known to result in
a greater number of runs scored on average as well as a greater
number of wickets, since their implementation (Silva et al., 2015).
Furthermore, this result may be indicative of modern batting
strategies of maximising run scoring opportunities in the power-
play, particularly as boundary strokes are riskier to perform in
non-powerplay overs due to the greater number of elders
guarding the boundary (Jamil et al., 2021; Najdan et al., 2014).
This study provides evidence that bowlers are at least partly
responsible for the ball-hitting distribution of the batter, speci-
cally through the line and length of their delivery as well as
their bowling style. Other factors outside of the bowler’s control,
such as the enforced elding restrictions caused by powerplays,
can also inuence the direction in which the ball is played. These
results therefore oer some practical implications which could
be considered by both batters and bowlers. Given that previous
research has revealed the short ball to be the least eective
wicket taking delivery (Najdan et al., 2014) and this study reveals
that the short ball oers 6-run scoring opportunities to the
batter, bowlers may wish to limit their use of the short-ball as
an eective bowling delivery in limited overs cricket, at least
when it is used in isolation. Some research suggests certain
types of bowling can be used eectively over a series of deliv-
eries as a means to eventually induce a false shot from a batter
(O’Donoghue, 2016), however the use of the short pitched ball
to this eect in limited overs cricket requires further research.
Furthermore, bowlers could look to bowl in line with the stumps
and restrict the width oered to batters on the o-side as
bowling outside the line of o stump has been revealed in this
study to oer 6-run scoring opportunities. It should be noted
that variations in pace, line and length do oer strategic advan-
tages (Justham et al., 2010), therefore bowling o-side lines
should not be completely disregarded by bowlers as they
need to maintain some unpredictability. Similarly, batters should
look to take advantage of the powerplay overs and attempt
aerial power-hitting strokes whilst the boundaries are less pro-
tected. In addition, batters should continue to attack the short
ball length and the half-volley length and when doing so target
the areas behind square or on the o-side to maximise their
6-run scoring opportunities. Similarly, if oered width with the
outside o line then batters could be encouraged to perform
o-side shots for potential 6-run scoring opportunities.
This study did have some limitations. Firstly, no data were
available on weather conditions, which can impact levels of
swing and spin for bowlers (Jamil et al., 2021; Petersen, 2017;
Scobie et al., 2020) and thus potentially impact the batters’
striking abilities. Second, information regarding whether the ball
was delivered by the bowler from over the wicket or around the
wicket was also lacking and this alteration of bowling angles
could therefore have also aected the distribution of the ball
post batting connection. Similarly, there were no data on the
exact speed of the balls bowled, which could potentially have
impacted the batter’s ability to strike the ball. Lastly, data on the
movement of the batters at the crease could also have potentially
impacted the present results. Some of the eects of these limita-
tions could have been placated somewhat by the inherent varia-
bility of the data set in this study. Whilst the authors of this study
have attempted to investigate/control for numerous factors that
impact batting/bowling performance, there are other factors that
are not controlled for, such as, the specic bowler/batter and
stadium attendances. Future researchers should look to expand
on this research and incorporate the data referred to above if it is
available. Future studies could also investigate ball distribution
trends in alternative formats such as test cricket, women’s cricket,
and the newly conceived “The Hundred” format.
Conclusion
This study revealed that bowling length, bowling line, bowler
type (style) and power-plays were all signicantly associated
with ball-hitting distributions of aerial 6-run scoring strokes.
Eect sizes revealed bowling length to have the greatest impact
of all variables analysed. Shorter pitched balls, such as the short
ball and the back of a length deliveries, resulted in greater than
expected 6ʹs behind square. Bowling the half-volley length
resulted in greater than expected 6ʹs being scored on the o-
side. Greater than expected 6ʹs were scored on the o-side to
balls bowled outside the line of o-stump. Fast bowlers con-
ceded greater than expected 6ʹs behind square. Powerplay
overs also resulted in greater than expected 6ʹs. This study oers
both bowlers and batters insight into their inter-dependencies.
The results suggest that shorter pitched bowling as well as the
half volley length oer batters greater 6-run scoring opportu-
nities and so bowlers may wish to bowl alternate lengths more
frequently and limit their half-volley and short pitched bowling.
From a batter’s perspective, targeting the short ball, the half-
volley or balls bowled wide on the outside o stump line may
be recommended if looking to score the maximum 6-runs avail-
able. Furthermore, batters should aim to maximise their oppor-
tunities to play power-hitting strokes during the powerplay
overs as the eld restrictions appear to be advantageous.
Disclosure statement
No potential conict of interest was reported by the author(s).
Funding
The author(s) reported there is no funding associated with the work fea-
tured in this article.
ORCID
Mikael Jamil http://orcid.org/0000-0001-6117-0546
Stuart A. McErlain-Naylor http://orcid.org/0000-0002-9745-138X
JOURNAL OF SPORTS SCIENCES 7
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Cricket fast bowling is a dynamic activity in which a bowler runs up and repeatedly delivers the ball at high speeds. Experimental studies have previously linked ball release speed and several technique parameters with conflicting results. As a result, computer simulation models are increasingly being used to understand the effects of technique on performance. This study evaluates a planar 16-segment whole-body torque-driven simulation model of the front foot contact phase of fast bowling by comparing simulation output with the actual performance of an elite fast bowler. The model was customised to the bowler by determining subject-specific inertia and torque parameters. Good agreement was found between actual and simulated performances with a 4.0% RMS difference. Varying the activation timings of the torque generators resulted in an optimised simulation with a ball release speed 3.5 m/s faster than the evaluation simulation. The optimised technique used more extended front ankle and knee joint angles, increased trunk flexion and a longer delay in the onset of arm circumduction. These simulations suggest the model provides a realistic representation of the front foot contact phase of fast bowling and is suitable to investigate the limitations of kinematic or kinetic variables on fast bowling performance.
Article
Objectives: Investigate rotational passive range of motion of the hips and shoulders for elite finger spin bowlers and their relationship with spin rate. Design: Correlational. Methods: Spin rates and twelve rotational range of motion measurements for the hips and shoulders were collected for sixteen elite male finger spin bowlers. Side to side differences in the rotational range of motion measurements were assessed using paired t-tests. Stepwise linear regression and Pearson product moment correlations were used to identify which range of motion measurements were linked to spin rate. Results: Side to side differences were found with more external rotation (p = 0.039) and less internal rotation (p = 0.089) in the bowling shoulder, and more internal rotation in the front hip (p = 0.041). Total arc of rotation of the front hip was found to be the best predictor of spin rate (r = 0.552, p = 0.027), explaining 26% of the observed variance. Internal rotation of the rear hip (r = 0.466, p = 0.059) and the bowling shoulder (r = 0.476, p = 0.063) were also associated with spin rate. Conclusions: The technique and performance of elite finger spin bowlers may be limited by the passive range of motion of their hips and shoulders. The observed side to side differences may indicate that due to the repetitive nature of finger spin bowling adaptive changes in the rotational range of motion of the hip and shoulder occur.