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Technology and Tracking in Sport Analysis

Info: 4561 words (18 pages) Dissertation
Published: 10th Dec 2019

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Tagged: SportsTechnology

The sport Camogie

Gaelic games were established in Ireland in the year 1884 (Reilly and Collins, 2008). These games include Gaelic football, hurling and in later years the female version of the hurling ball and stick game that is called camogie. Less attention is being paid to the female version of hurling because camogie is not regularly featured on television. Camogie is a ball and stick game very similar to other field sports such as field hockey and shinty (Shovlin et al., 2017). This sport is one of the most dynamic sports in the world (Reilly and Collins, 2008). In camogie, the players use a stick made of ash called a camán. The game is played with a small round ball called a sliotar which is made of cork filling with a leather outside (Reilly and Collins, 2008). The players use a helmet to protect the head, which in recent years is a requirement. Camogie is an invasion game with the aim to keep possession and outscore the opposition.  The pitch is 130m to 165m long. It is about 40% larger than a soccer pitch. At either end of the pitch, there are two goals (6.5 m) (Reilly and Collins, 2008). Camogie at senior level is played for 70 minutes with 35 minutes a side not including extra time with 10 minutes break at half-time. Fifteen players from each team are permitted on the pitch at one time. The teams can make up to 5 changes in the championship per game. There is a goalie, six defenders, two midfielders and six attackers (Gaelic Athletic Association, 2016).

There are many skill performed in the game. The ball can often be hit (striking) up to 80 to 90 meters in order to keep possession or score (Reilly and Collins, 2008). The hand pass, which is striking a ball with the hand over short distances, is another way of keeping possession. Hooking and blocking are skills used to tackle and to pick up the ball a roll or jab lift can be used. A sideline cut is a used when the ball is put out of play by the opponent team. In camogie, players are allowed to hand pass and strike the ball into the goal. The physical demands of this sport include strength, powers, stamina, speed, agility, hand-eye coordination and sports specific skills. The biomechanical demands of the sport include sprinting, acceleration, deceleration, jumping, landing and changing direction including cutting and turning (Reilly and Collins, 2008). There are many ways to assess (video, notations, GPS) these demands of the sport.

Player tracking technology

Video analysis has been used as motion analysis tool to monitor a player’s work rate in games. Player tracking was first introduced by using semi-automated video analysis systems called ProZone and Amisco. Prozone is a technology that can track players in training or competitions and started in many soccer stadiums in England (Harley et al., 2011). Locomotives data which include distance covered, speed and accelerations can be quantified. This system uses fixed cameras around the stadium. Bradley, (2009) used the Prozone system on male FA Premiere league footballers to determine activity levels and examine high-intensity running in a game. Technology has evolved quickly over the last few years. These systems are now being compared to the new and more flexible tracking system of Global Positing Systems (GPS) technology. Most recently GPS is one of the most widely used monitoring systems for sports personals to improve their sport. The GPS systems were firstly used to monitor single sports and now has evolved to monitor team sports such as soccer, rugby, and field hockey (Hodun et al., 2016). GPS units are worn by athletes rather than cameras fixed around a stadium. Latest research and development have started to analyze and process the data through computerized settings. This can be done in seconds and gives feedback quickly during competition. These systems are being used in elite club settings (Carling et al., 2008). GPS is used widely in many different team sports such as soccer, rugby, hockey, American football and GAA. GPS can be a used to measure movement patterns, distance and speed covered (Duffield et al., 2010).

The first GPS satellite was launched in 1978. The GPS was first used by the US army. In the year 2000, the president ordered for the GPS system to be shared with the civilians. A GPS is a tracking device which uses 24 satellites which orbit the earth. Then the units get signals from the satellite which can determine the place direction and speed of the athlete (Maddison and Ni Mhurchu, 2009). GPS is a valid tool used in female field sport to give strength and conditioning coaches’ information about players so they can develop training sessions and monitoring protocols. A particular concern for GPS is the standardization of methods to determine the occurrence of sprinting and high-intensity training (Hodun et al., 2016). GPS in female sport is not as common as in men’s sport and as a result limited data is available. As there is a difference biologically between male and female and their capabilities including speed and intensity in training, it is very important that there is female-specific data as it will be more inclined to be correct towards the needs of women (Hodun et al., 2016).

GPS is used to monitor athletes in competition to training for ultimate performance. (Liebermann et al., 2002). This technology is also used to avoid injury such as hamstring strains; this can be done by monitoring acceleration times. Players who are exposed to rapid high-speed and intensity running increases the chances of injury (Malone et al., 2017). GPS devices are used to monitor many important aspects of the game that can help coaches monitor the athlete in training load and performance which could lead to overtraining and severe fatigue which can lead to possible injury (Rossi et al., 2017). Tracking GPS data can help detect fatigue in training and matches and also identify the different activities performed by different positions. Coaches can analyse the data to help detect the most intense and non-intense periods in a game. The GPS is also used to test athletes of their physical capacity including game-specific tasks and tactical skills. It is important to test the validity and reliability of the GPS units being used as it is an important factor to creating and adaptation of training loads.

Valid & Reliability of GPS

GPS and its reliability is a controversial matter. A study by (Duffield et al., 2010) has stated that GPS has inter-unit reliability and is accurate for recording the distance covered. In this study, the accuracy level is less than 5% for measuring distance when comparing 1 Hz and 5 Hz units. A study by Edgecomb & Norton, (2006) showed that 1hz GPS devices are useful for quantifying slow and medium running speeds and straight line walking with 59 trials experimented with 4.8% error. It is shown that 5 Hz is more reliable at higher speeds than 1 Hz. A study by Harley et al., (2011) stated that more research is required to determine if an increase of Hertz will increase the reliability for field sports to quantify sprint performance and fast accelerations over shorter distances. Duffield et al., (2010) also focused on GPS readings on the demands of team sport and the reliability of the GPS. The results of this study were similar to the previous research that showed that there is a decrease in the validity and reliability of GPS readings fewer than 20 m. It is also mentioned in these studies that newer models of GPS devices have resulted in better readings than the older versions.

(Gray et al., 2010) examined the effect of movement intensity and path linearity on GPS. A participant wore eight 1 Hz GPS systems while completing five trials over 200 meters of linear and nonlinear course. Locomotives including walking, jogging, running and sprinting were collected. The results from the linear course showed that from seven GPS receivers (one receiver had faults), found the mean (± SD) and percent bias of the GPS distance value on the course. The results showed (walking) 20.8 ± 2.4 m (2.8%) (jogging) 201.8 ± 2.8m (0.8%), (running) 203.1 ± 2.2m (1.5%) and (sprinting) 205.8 ± 4m (2.5%) for all locomotives. Walking and sprinting differed from jogging and running (p < 0.05). The non linear course results, (walking) 198.9 ± 3.5 m (-0.5%), (jogging) 188.3 ± 2 m (-5.8%), (running) 184.6 ± 2.9 m (-7.7%) and (sprinting) 180.4 ± 5.7 m (9.8%) Edgecomb & Norton, (2006) stated that 1 Hz GPS systems moderate values regarding intra-reliability for long distances ranging from 128 m to 1386 m. Likewise, intra-reliability was also found in 5 Hz when studied. In a study by Jennings, D., Cormack, S., Coutts, A. J., Boyd, L., & Aughey, (2010) it was discovered that 5 Hz is poor measurement over short distances such as 10-20 m while walking, jogging, striding and sprinting but found reliable over 40-m sprints. A similar study by Portas et al., (2010) using 5 Hz GPS units in linear and multi-directional movement was carried out and it was found that distances over 600-8800 m the 5 Hz system were accurate. A study by Casamichana et al., (2011) examined 10 Hz over 15 and 30 m sprint. It was found that a standard error mean (SEM) of 15 m sprint was 10.9% and the SEM of 5.1% over 30 m. A study by (Rampinini, E., Alberti, G., Fiorenza, M., Riggio, M., Sassi, R., Borges, T. O., & Coutts, 2015)  showed that 10 Hz GPS units are accurate in high-speed running at a moderate distance of 70 m but at higher speeds, lower value of accuracy was found.

Metrics and Locomotives

GPS has been used in female team sports such as soccer (Gabbett, 2008; Vescovi, 2012; Malone et al., 2017) and field hockey (Gabbett, 2010; Vescovi, 2013; Vescovi and Frayne, 2015; Hodun et al., 2016). These studies on female sport focus on match performance, fatigue and training intensity (Hodun et al., 2016). Currently there is no similar GPS research available in camogie. GPS can be used to detect and track several locomotives (Total distance covered, acceleration, deceleration, sprinting distance and maximum speed). The GPS can also record speed zones. The data collected is very valuable to the coaches. This information lets the coaches observe the physiological workload of the athlete which leads to more knowledge on athlete recovery times (Johnston et al., 2014).

Total Distance (TD)

Total distance (TD) is the amount of distance covered by the athlete in a session or game. It can also be described as a global external physical load. The TD can be a marker for running performance expectations. TD is the first variable which the GPS unit recorded (Cummins et al., 2013). Additional metrics allow TD to be broken into a number of intensities like walking jogging running, sprinting and high-intensity running. A study by Gabbett, (2008) found that elite female soccer players cover on average 9 – 12 km per game. This mostly consists of low-intensity activities such as walking and jogging. The attackers covered 9609 ± 359 m, midfielders covered 10672 ± 1338 m and the defenders covered 9621 ± 1202 m. From this data, it is clear to see that the midfielders covered more distance than the other positions. Attackers spent the most distance walking at 35.7% but exceeded the most time sprinting at 12.3% of the overall distance. All positions spent most of the time jogging in the game, attackers 39.7%, and midfielders 43.5% with defenders covering the most distance in jogging phase at 45.4%. In comparison Gabbett, (2010) found that female field hockey players cover an average of 6.6 km (range: 3.4-9.5 km) over the course of a 70-minute match. Attackers covered 6154 ± 271 m; midfielders covered 6931 ± 1882 m and defenders covering 6643 ± 1618 m. It is clear to see that the female soccer players covered more distance than the female hockey players. This could be a result in difference in game time (Soccer 90 minutes and field hockey 70 minutes) and field size (a soccer pitch is larger than a hockey pitch). Although there was more distance covered in the soccer study, the percentages in the jogging phase were similar in both studies. In the soccer study attackers 39.7%, midfielders 43.5% and defenders 45.4%. Field hockey attackers 49.1 ± 5 % and midfielders 49.3 ± 2.6 % covered similar jogging TD. However defenders covered the most distance 54.8 ± 3.5 % (Gabbett, 2010). Defenders will be covering more distance in games as they have to cover the space and be aware of the ball as well as marking their opponent to prevent scoring.

Relative distance is a segment of the TD traveled by the player per minute. This variable is considered more accurate as it gives more detail on match intensity in a shorter period of time in game time (m.min-1) (Cummins et al., 2013) therefore it is more accurate when comparing different sport. A study by Vescovi, (2012) who focused on female soccer, has reported a significant difference (p < 0.001) between ages of the athletes and the work rate and intensity in the TD covered. Under 15 players cover 86 ± 3 m.min-1, under 16 cover 100 ± 1 m.min-1 and under 17 cover 100 ± 3 m.min-1. A range of 100 to 120 m.min-1 is considered to be a target work rate for women soccer (Hodun et al., 2016). A study by Ramos et al., (2017) have compared the locomotive activity of under 17, under 20 and senior top class Brazilian female teams. It was found that the senior team covered more overall distance than the U17 and U20.

Speed zone

Speed zones are the specific speeds in which the athletes are reaching in locomotive movements. The internal load and intensity can be quantified by the coaches as TD can be divided in each speed-zone.  The variables include walking, jogging, running and sprinting. Comparison between studies can be difficult as each study may have a different speed zones measurement as there is not a concise regulation to speed zones.

A study by Gabbett, (2010) focusing on GPS analysis of elite women’s field hockey training and competition used 5 zones. The value of speed zones is broken down into meters per second m.s-1, zone one low intensity (0-1 m.s-1), zone 2 moderate intensity (1-3 m.s-1) and zone 3 (3-5 m.s-1), and high intensity zone 4 (5-7 m.s-1) zone 5 (>7 m.s-1). As mentioned the defenders cover the most distance in the low to moderate intensity activities as shown in zone 1 and zone 2 841 ± 229 m and 3618 ± 821 m. In zone 3 and 4 the midfielders cover the most distance 2181 ± 558 m and 571 ± 244 m. In zone 4 the midfielders cover the most distance 571 ± 244 m followed by the strikers cover 423 ± 195 m. In zone 5 the strikers cover 46 ± 57 m, the midfielders cover 77 ± 69 m and the defenders cover 52 ± 62 m. It is clear to see that most of the midfielder’s and defenders cover more distance at higher speed than the attackers. This could be a result in multiple invasions at high speed from the defender position. The zone with the most distanced covered is zone two with an average of 10,057 m covered. The least time spent in a zone is zone 5 with an average of 175 m. This shows that the athletes are reaching high-velocity speeds very little throughout the game. The total absolute number of high intensity activity was greater in midfielders 102 efforts, than attackers 92 efforts and lastly defenders 79 efforts. This leads to an understanding in importance in individualising conditioning programs to meet the specific needs and demands of the different positions. In another study by Collins et al., (2017) on the match play demands of hurling the speed zones are broken into km.hr-1 (more commonly used in papers). It also consists of 5 speed zones. Zone 1 (passive) 1 – 6.9 km.hr-1, zone 2 (slow) 7-11.9 km.hr-1 , zone 3 (medium) 12-16.9 km.hr-1, zone 4 (fast) 17-12.9 km.hr-1  and zone 5 (maximal) ≥22 km.hr-1 . The results show similar results as the study above with the least time covered in zone 4 815 ± 274 m and 5 319 ± 129 m. The speed in which the athlete is reaching as an important factor as determents the external load per training or competition.

Sprint distance

Sprint distance is described as the amount of distance covered while the athlete is at their highest running speed which is called sprinting. Sprinting is a very important attribute of any field sport as described in a study by Vescovi, (2013) focused youth female hockey players reach 90% of maximal sprint speed during match play. As the athletes are expected to reach sprint speed multiple times throughout game time it is important that the coaches have knowledge of the athlete’s high intensity running distances to prepare them to complete this avoid injury and fatigue. Vescovi, (2012) studied 71 elite female soccer players sprint profiles. The athletes who played a full game were monitored during 12 matches in one season. A sprint was classified as ≤ 18 km.h-1. Attackers covered 15.5 ± 9.6 m in 2.3 ± 1.5 s, midfielders covered 14.3 ± 9.1 m in 2.2 ± 1.4 s and defenders covered 15.3 ± 9.4 m in 2.3 ± 1.5 s. Results show that on average players sprint is 15.1 ± 9.4 m duration is on average 2.3 s with an average maximal speed of 21.8 ± 2.3 km.h-1 (zone 3 in this study). The mean duration between sprints was 2.5 minutes. Similar, a study on time-motion analysis on female soccer players by Gabbett, (2008) also investigated female soccer sprint duration. A sprint is defined by the maximal effort with great leg extension and heals lift, as there is no speed zone foe the sprint it is hard to compare results as they will differ with no standardisation. Results show attackers 2.5 ± 1.5 s; midfielders cover 2.3 ± 1.6 s and defenders 2.4 ± 1.5 s. There is no data to show the m covered in the times above. In female hockey there is limited data for example a study by Gabbett, (2010) they used high-intensity movements speed zones of 5-7 m.s-1 and >7 m.s-1.  This is not specific speed zone as it is unknown what range of speed the athlete may be reaching the amount of m covered as the speed zone is >7 m.s-1.

Differences demands between positions

Different positions will have different demands (Carling et al., 2008). In a study by Gabbett,( 2008) (soccer) and Gabbett, (2010) (hockey) showed that midfielders (10672 ± 1338 m and 6931 ± 1882 m) covered more distance than both attackers (9609 ± 359 m and 6154 ± 271 m) and defenders (9621 ± 1202 m and 6643 ± 1618 m) in both studies. Defenders covered 54.8 ± 3.5 % of TD at low intensity (Gabbett, 2010). In a study by Collins et al., (2017) work rate of elite hurling the work rate of elite hurlers (as there is no female research available on the decrease of halves) discovered that there is a significant decrease in high intensity activities between the first quarter 330 ± 120 m and forth quarter 255 ±108 m. The players covered more distance in the first half of the game than the second half. This may be because of a drop of game intensity and fatigue.

Vescovi and Frayne, (2015) studied the motion characteristics of female college hockey. All positions had similar results in a number of sprints, accelerations, and decelerations. In regards to position, the defenders played more time than the attackers in the full game (p = 0.019, d = 0.93). This may be a result of defenders covered more distance at low intensity running than attackers (P = 0.37, d = 0.91) and less high-intensity running than midfielders (p = 0.037, d = 0.91). Defenders also covered less relevant distance than the other positions (P = 0.019, d = 1.04 to 1.06). There was a tendency of forwards to have less distance at low metabolic power and the midfielders to have covered more distance at high and elevated metabolic power. A study by Vescovi, (2012) (soccer) found defenders (n = 2306) and midfielders (n = 1504) had more sprint attempts than attackers (n = 1209). Midfielders 14.3 m, 2.2 ± 1.4 s had shorter sprint distance, duration and maximal speed compared to forwards 15.5 ± 9.4 m, 2.3 ± 1.5 s but defenders 15.3 ± 9.4 m, 2.3 ± 1.5 s showed similar results. This may be a result in forwards chasing the ball to invade for a score.

Currently, there is limited GPS research available in female sport. There is no research available on the demands in camogie in relation to GPS. Camogie is a dynamic sport with many demands involved with this game. Coaches require information which describes the match play demands in order to prepare players effectively. Therefore the aim of this study was to investigate the demands on an inter-county camogie team in competition.


Bradley, P. S. (2009) ‘High-intensity running in English FA Premier League soccer matches’.

Carling, C. et al. (2008) ‘The role of motion analysis in elite soccer: Contemporary performance measurement techniques and work rate data’, Sports Medicine, 38(10), pp. 839–862. doi: 10.2165/00007256-200838100-00004.

Casamichana, D. et al. (2011) ‘RELIABILITY AND ACCURACY OF 10 HZ GPS DEVICES FOR SHORT-DISTANCE EXERCISE, JSSM-2011, Vol.10, Issue 1, 233 – 234’, (May), pp. 28–30. Available at: http://ww.w.jssm.org/vol10/n1/33/v10n1-33text.php.

Collins, K. et al. (2017) ‘The Work-Rate of Elite Hurling Match-Play’, Journal of Strength and Conditioning Research, p. 1. doi: 10.1519/JSC.0000000000001822.

Cummins, C. et al. (2013) ‘Global positioning systems (GPS) and microtechnology sensors in team sports: A systematic review’, Sports Medicine, 43(10), pp. 1025–1042. doi: 10.1007/s40279-013-0069-2.

Duffield, R. et al. (2010) ‘Accuracy and reliability of GPS devices for measurement of movement patterns in confined spaces for court-based sports’, Journal of Science and Medicine in Sport, 13(5), pp. 523–525. doi: 10.1016/j.jsams.2009.07.003.

Edgecomb., N. (2006) ‘Comparison of global positioning and computer’.


Gabbett, T. J. (2010) ‘GPS analysis of elite women’s field hockey training and competition.’, Journal of strength and conditioning research / National Strength & Conditioning Association, 24(5), pp. 1321–1324. doi: 10.1519/JSC.0b013e3181ceebbb.

Gaelic Athletic Association (2016) ‘GAELIC ATHLETIC ASSOCIATION Official Guide -Part 1’, (April), pp. 1–229.

Gray, A. J. et al. (2010) ‘Validity and reliability of GPS for measuring distance travelled in field-based team sports’, Journal of Sports Sciences, pp. 1319–1325. doi: 10.1080/02640414.2010.504783.

Harley, J. A. et al. (2011) ‘The Interchangeability of Global Positioning System and Semiautomated Video-Based Performance Data During Elite Soccer Match Play’, Journal of Strength and Conditioning Research, 25(8), pp. 2334–2336. doi: 10.1519/JSC.0b013e3181f0a88f.

Hodun, M. et al. (2016) ‘Global Positioning System Analysis of Running Performance in Female Field Sports’, Strength and Conditioning Journal, 38(2), pp. 49–56. doi: 10.1519/SSC.0000000000000200.

Jennings, D., Cormack, S., Coutts, A. J., Boyd, L., & Aughey, R. J. (2010) ‘The validity and reliability of GPS units in team sport specific running patterns’, International journal of sports physiology and performance, pp. 328–341. doi: 10.1249/MSS.0b013e3181ef9d6b.10.

Johnston, R. J. et al. (2014) ‘Validity and Interunit Reliability of 10 Hz and 15 Hz GPS Units for Assessing Athlete Movement Demands’, Journal of Strength and Conditioning Research, pp. 1649–1655. doi: 10.1519/JSC.0000000000000323.

Liebermann, D. G. et al. (2002) ‘Advances in the application of information technology to sport performance’, J. Sports Sci., pp. 755–769.

Maddison, R. and Ni Mhurchu, C. (2009) ‘Global positioning system: a new opportunity in physical activity measurement’, International Journal of Behavioral Nutrition and Physical Activity, 6(1), p. 73. doi: 10.1186/1479-5868-6-73.

Malone, S. et al. (2017) ‘High-speed running and sprinting as an injury risk factor in soccer: Can well-developed physical qualities reduce the risk?’, Journal of Science and Medicine in Sport. doi: 10.1016/j.jsams.2017.05.016.

Portas, M. D. et al. (2010) ‘The validity and reliability of 1-Hz and 5-Hz Global Positioning Systems for linear, multidirectional, and soccer-specific activities’, International Journal of Sports Physiology and Performance, 5(4), pp. 448–458. doi: 10.1123/ijspp.5.4.448.

Ramos, G. p. et al. (2017) ‘Activity profiles in U17, U20 and senior women’s Brazilian National soccer teams during international competitions’, Journal of Strength and Conditioning Research, p. 1. doi: 10.1519/JSC.0000000000002170.

Rampinini, E., Alberti, G., Fiorenza, M., Riggio, M., Sassi, R., Borges, T. O., & Coutts, A. J. (2015) ‘Accuracy of GPS Devices for Measuring High’.

Reilly, T. and Collins, K. (2008) ‘Science and the Gaelic sports: Gaelic football and hurling’, European Journal of Sport Science, 8(5), pp. 231–240. doi: 10.1080/17461390802251851.

Rossi, A. et al. (2017) ‘Effective injury prediction in professional soccer with GPS data and machine learning’, (May). Available at: http://arxiv.org/abs/1705.08079.

Shovlin, A. et al. (2017) ‘The Positional Anthropometric and Performance Profile of Elite Gaelic Football Players.’, Journal of Strength and Conditioning Research, p. 1. doi: 10.1519/JSC.0000000000002071.

Vescovi, J. D. (2012) ‘Sprint profile of professional female soccer players during competitive matches: Female Athletes in Motion (FAiM) study’, Journal of Sports Sciences, 30(12), pp. 1259–1265. doi: 10.1080/02640414.2012.701760.

Vescovi, J. D. (2013) ‘Impact of Maximum Speed on Sprint Performance During High’.

Vescovi, J. D. and Frayne, D. H. (2015) ‘Motion characteristics of Division I college field hockey: Female Athletes in Motion (FAiM) study’, International Journal of Sports Physiology and Performance, 10(4), pp. 476–481. doi: 10.1123/ijspp.2014-0324.

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