Introduction: Profiling of cricket bowlers is performed with motion analyses systems that require the placement of markers on the bowler’s body and on the ball. Conventional smart balls such as cricket and baseballs provide only one speed and one spin rate datum at the release point, which is insufficient for biomechanical profiling. Method: In this study, we used an advanced smart cricket ball that measures the angular velocity at 815 Hz and calculates four further physical performance parameters (resultant torque, spin torque, power and angular acceleration) and five new skill parameters (precession, normalised precession, precession torque, efficiency and ratio of angular acceleration to spin rate), which we used for profiling and talent identification of spin bowlers. Results: The results showed that the spin rate is a function of physical (torque) and skill proficiency, namely how efficiently the torque is converted to angular velocity rather than being wasted for precession. The kind of delivery also influences the efficiency, as finger-spin deliveries were less efficient than wrist-spin ones by 6.8% on average; and topspin deliveries were generally more efficient than backspin ones by 15% on average. We tested three bowlers in terms of physical and skill performance during a 10-over spell, revealing that some parameters can improve or decline. When profiling a topspinner, we detected from the performance parameters a lower skill performance than expected, because there was an initial arm motion for backspin delivery before releasing the ball with a topspin. After training intervention, the skill parameters improved significantly (the efficiency increased from 39% to 59%). Conclusions: The advanced smart cricket ball is a classic example of mobile computing for sport performance analysis that can conducted indoors as well as outdoors, generating instant data from 10 performance parameters that provide critical feedback to the coach and bowler.

In the off-spin bowling grip, the ball is clamped between index and middle fingers. Spin bowlers attempt to select a spread angle between these two fingers that achieves comfort and optimises performance. The aim of this paper was to investigate whether the standard grip is superior to narrow and wide grips. The bowling performance parameters were obtained from a smart cricket ball. Smart ball data revealed that the performance parameters varied with grip type. The following parameters were optimum at the standard grip: spin rate, resultant torque, spin torque, peak angular acceleration, and peak power. The following parameters were optimum at standard and wide grips: efficiency. The following parameters were optimum at standard and narrow grips: pitch angle of spin axis. The following parameters were optimum at the wide grip: precession and the precession torque. In general, the data tended to show that the standard grip is most effective for spin bowling. However, more research is needed to confirm this result, because the precession and precession torque were optimum at the wide grip, suggesting that this may have a superior performance over the standard and narrow grips.

A smart cricket ball was used to investigate the influence of increased spin rate on the bowling performance parameters. In three spin bowlers, the performance parameters were compared before and after increasing the spin rate. The first bowler increased the spin rate by 22%, decreased the normalised precession the angle at which the spin rate vector moves into the torque vector—the lower the more efficient), and increased the torque, angular acceleration and power, showing an improvement in all performance parameters. The second bowler showed no improvement in any performance parameters. The third bowler increased the spin rate marginally, but insignificantly; but improved the normalised precession dramatically (reducing it by 50%). The research results suggest that the mere intention to improve the spin rate changes bowling technique in way that optimises normalised precession, even if the spin rate does not actually increase.

Profiling of spin bowlers is currently based on the assessment of translational velocity and spin rate (angular velocity). If two spin bowlers impart the same spin rate on the ball, but bowler A generates more spin rate than bowler B, then bowler A has a higher chance to be drafted, although bowler B has the potential to achieve the same spin rate, if the losses are minimized (e.g., by optimizing the bowler’s kinematics through training). We used a smart cricket ball for determining the spin rate and torque imparted on the ball at a high sampling frequency. The ratio of peak torque to maximum spin rate times 100 was used for determining the ‘spin bowling potential’. A ratio of greater than 1 has more potential to improve the spin rate. The spin bowling potential ranged from 0.77 to 1.42. Comparatively, the bowling potential in fast bowlers ranged from 1.46 to 1.95.

A pitcher’s action, when delivering a fastball, was analyzed from the data provided by a smart baseball. The spin rate at the release of the ball was merely 15.7 rps, however, the peak torque was excessively high, namely 0.396 Nm. The reason why the pitcher was not able to translate the torque entirely to angular kinetic energy and this to the spin rate was that the spin axis changed its direction suddenly three times when moving across the ball’s surface. This resulted in angles between torque and angular velocity vectors of greater than 90°, high precession and precession torque, and negative spin torques, causing a very low efficiency (5.4%) and a slow spin rate at the release of the ball.

Spin bowling deliveries in cricket, finger spin and wrist spin, are usually (Type 1, T1) performed with forearm supination and pronation, respectively, but can also be executed with opposite movements (Type 2, T2), specifically forearm pronation and supination, respectively. The aim of this study is to identify the differences between T1 and T2 using an advanced smart cricket ball, as well as to assess the dynamics of T1 and T2. With the hand aligned to the ball’s coordinate system, the angular velocity vector, specifically the x-, y- and z-components of its unit vector and its yaw and pitch angles, were used to identify time windows where T1 and T2 deliveries were clearly separated. Such a window was found 0.44 s before the peak torque, and maximum separation was achieved when plotting the y-component against the z-component of the unit vector, or the yaw angle against the pitch angle. In terms of physical performance, T1 deliveries are easier to bowl than T2; in terms of skill performance, wrist spin deliveries are easier to bowl than finger spin. Because the smart ball allows differentiation between T1 and T2 deliveries, it is an ideal tool for talent identification and improving performance through more efficient training.