Phyllis Weikert, UM Field Hockey coach, 1973

(portrait from 1984 Department of Kinesiology annual report)

The influence of recreational ball hockey play on cardiovascular risk factors in sedentary males

Introduction: The prevalence of coronary artery disease (CAD) is ever increasing in western industrialized societies. An individuals overall risk for CAD may be quantified by integrating a number of factors including, but not limited to, cardiorespiratory fitness, body composition, blood lipid profile and blood pressure. It might be expected that interventions aimed at improving any or all of these independent factors might improve an individual 's overall risk. To this end, the influence of standard endurance type exercise on cardiorespiratory fitness, body composition, blood lipids and blood pressure, and by extension the reduction of coronary risk factors, is well documented. On the other hand, interval training (IT) has been shown to provide an extremely powerful stimulus for improving indices of cardiorespiratory function but the influence of this training type on coronary risk factors is unknown. Moreover, the vast majority of studies investigating the effects of IT on fitness have used laboratory type training protocols. As a result of this, the influence of participation in interval-type recreational sports on cardiorespiratory fitness and coronary risk factors is unknown. Aims: The aim of the present study was to evaluate the effectiveness of recreational ball hockey, a sport associated with interval-type activity patterns, on indices of aerobic function and coronary risk factors in sedentary men in the approximate age range of 30 - 60 years. Individual risk factors were compiled into an overall coronary risk factor score using the Framingham Point Scale (FPS). Methods: Twenty-four sedentary males (age range 30 - 60) participated in the study. Subject activity level was assessed apriori using questionnaire responses. All subjects (experimental and control) were assessed to have been inactive and sedentary prior to participation in the study. The experimental group (43 ± 3 years; 90 ± 3 kg) (n = 11) participated in one season of recreational ball hockey (our surrogate for IT). Member of this group played a total of 16 games during an 11 week span. During this time, the control group (43 ± 2 years; 89 ± 2 kg) (n = 11) performed no training and continued with their sedentary lifestyle. Prior to and following the ball hockey season, experimental and control subjects were tested for the following variables: 1) cardiorespiratory fitness (as V02 Max) 2) blood lipid profile 3) body composition 5) waist to hip ratio 6) blood glucose levels and 7) blood pressure. Subject V02 Max was assessed using the Rockport submaximal walking test on an indoor track. To assess body composition we determined body mass ratio (BMI), % body fat, % lean body mass and waist to hip ratio. The blood lipid profile included high density lipoprotein, low density lipoprotein and total cholesterol levels; in addition, the ratio of total cholesterol to high density was calculated. Blood triglycerides were also assessed. All data were analyzed using independent t - tests and all data are expressed as mean ± standard error. Statistical significance was accepted at p :S 0.05. Results: Pre-test values for all variables were similar between the experimental and control group. Moreover, although the intervention used in this study was associated with changes in some variables for subjects in the experimental group, subjects in the control group did not exhibit any changes over the same time period. BODY COMPOSITION: The % body fat of experimental subjects decreased by 4.6 ± 0.5%, from 28.1 ± 2.6 to 26.9 ± 2.5 % while that of the control group was unchanged at 22.7 ± 1.4 and 22.2 ± 1.3 %. However, lean body mass of experimental and control subjects did not change at 64.3 ± 1.3 versus 66.1 ± 1.3 kg and 65.5 ± 0.8 versus 64.7 ± 0.8 kg, respectively. In terms of body mass index and waist to hip ratio, neither the experimental nor the control group showed any significant change. Respective values for the waist to hip ratio and body mass index (pre and post) were as follows: 1 ± 0.1 vs 0.9 ± 0.1 (experimental) and 0.9 ± 0.1 versus 0.9 ± 0.1 (controls) while for BMI they were 29 ± 1.4 versus 29 ± 1.2 (experimental) and 26 ± 0.7 vs. 26 ± 0.7 (controls). CARDIORESPIRATORY FITNESS: In the experimental group, predicted values for absolute V02 Max increased by 10 ± 3% (i.e. 3.3 ± 0.1 to 3.6 ± 0.1 liters min -1 while that of control subjects did not change (3.4 ± 0.2 and 3.4 ± 0.2 liters min-I). In terms of relative values for V02 Max, the experimental group increased by 11 ± 2% (37 ± 1.4 to 41 ± 1.4 ml kg-l min-I) while that of control subjects did not change (41 ± 1.4 and 40 ± 1.4 ml kg-l min-I). BLOOD LIPIDS: Compared to pre-test values, post-test values for HDL were decreased by 14 ± 5 % in the experiment group (from 52.4 ± 4.4 to 45.2 ± 4.3 mg dl-l) while HDL data for the control group was unchanged (49.7 ± 3.6 and 48.3 ± 4.1 mg dl-l, respectively. On the other hand, LDL levels did not change for either the experimental or control group (110.2 ± 10.4 versus 112.3 ± 7.1 mg dl-1 and 106.1 ± 11.3 versus 127 ± 15.1 mg dl-1, respectively). Further, total cholesterol did not change in either the experimental or control group (181.3 ± 8.7 mg dl-1 versus 178.7± 4.9 mg dl-l) and 190.7 ± 12.2 versus 197.1 ± 16.1 mg dl-1, respectively). Similarly, the ratio of TC/HDL did not change for either the experimental or control group (3.8 ± 0.4 versus 4.5 ± 0.5 and 4 ± 0.4 versus 4.2 ± 0.4, respectively). Blood triglyceride levels were also not altered in either the experimental or control group (100.3 ± 19.6 versus 114.8 ± 15.3 mg dl-1 and 140 ± 23.5 versus 137.3 ± 17.9 mg dl-l, respectively). BLOOD GLUCOSE: Fasted blood glucose levels did not change in either the experimental or control group. Pre- and post-values for experimental and control groups were 92.5 ± 4.8 versus 93.3 ± 4.3 mg dl-l and 92.3 ± 11.3 versus 93.2 ± 2.6 mg dl-1 , respectively. BLOOD PRESSURE: No aspect of blood pressure was altered in either the experimental or control group. For example, pre- and post-test systolic blood pressures were 131 ± 2 versus 129 ± 2 mmHg (experimental) and 123 ± 2 and 125 ± 2 mmHg (controls), respectively. Pre- and post-test diastolic blood pressures were 84 ± 2 and 83 ± 2 mmHg (experimental) and 81 ± 1 versus 82 ± 1 mmHg, respectively. Similarly, calculated pulse pressure was not altered in the experimental or control as pre- and post-test values were 47 ± 1 versus 47 ± 2 mmlHg and 42 ± 2 versus 43 ± 2 mmHg, respectively. FRAMINGHAM POINT SCORE: The concerted changes reported above produced an increased risk in the Framingham Point Score for the subjects in the experimental group. For example, the pre- and post-test FPS increased from 1.4 ± 0.9 to 2.7 ± 0.7. On the other hand, pre- and post-test scores for the control group were 1.8 ± 1 versus 1.8 ± 0.9. Conclusions: Our data confirms previous studies showing that interval-type exercise is a useful intervention for increasing aerobic fitness. Moreover, the increase in V02 Max we found in response to limited participation in ball hockey (i.e. 16 games) suggests that recreational sport may help reduce this aspect of coronary risk in previously sedentary individual. On the other hand, our results showing little or no positive change in body composition, blood lipids or blood pressures suggest that one season of recreational sport in not in of itself a powerful enough stimulus to reduce the overall risk of coronary artery disease. In light of this, it is recommended that, in addition to participation in recreational sport, the performance of regular physical activity is used as an adjunct to provide a more powerful overall stimulus for decreasing coronary risk factors. LIMITATIONS: The increase in the FPS we found for the experimental group, indicative of an increased risk for coronary disease, was largely due to the large decrease in HDL we observed after compared to above one season of ball hockey. In light of the fact that cardiorespiratory fitness was increased and % body fat was decreased, as well as the fact that other parameters such as blood pressure showed positive (but non statistically significant) trends, the possibility that the decrease in HDL showed by our data was anomalous should be considered. FUTURE DIRECTIONS: The results of this study suggesting that recreational sport may be a potentially useful intervention in the reduction of CAD require to be corroborated by future studies specifically employing 1) more rigorous assessment of fitness and fitness change and 2) more prolonged or frequent participants.

Field fitness testing and training patterns for women in three masters sports

This study involved 33 women, aged 44-71 years involved in either masters swimming, field hockey or lawn bowls. Subjects undertook a 12-week competitive training program and participated in one fitness test session, to trial field-based tests of aerobic fitness, muscle power, body fat and flexibility. The field-based fitness testing proved practical. Athlete fitness was affected by age, competitiveness, training intensity and volume.

Global positioning system data analysis: velocity ranges and a new definition of sprinting for field sport athletes

Global positioning system (GPS) technology has improved the speed, accuracy, and ease of time-motion analyses of field sport athletes. The large volume of numerical data generated by GPS technology is usually summarized by reporting the distance traveled and time spent in various locomotor categories (e.g., walking, jogging, and running). There are a variety of definitions used in the literature to represent these categories, which makes it nearly impossible to compare findings among studies.

The purpose of this work was to propose standard definitions (velocity ranges) that were determined by an objective analysis of time-motion data. In addition, we discuss the limitations of the existing definition of a sprint and present a new definition of sprinting for field sport athletes.

Twenty-five GPS data files collected from 5 different sports (men’s and women’s field hockey, men’s and women’s soccer, and Australian Rules Football) were analyzed to identify the average velocity distribution. A curve fitting process was then used to determine the optimal placement of 4 Gaussian curves representing the typical locomotor categories. 

The complete hockey player /

Includes index.

Physical performance profile of sub-elite juvenile Gaelic Games players and the prevalence of a Relative Age Effect (RAE)

Gaelic Games are the indigenous sports played in Ireland, the most popular being Gaelic football and hurling. The games are contact sports and the physical demands are thought to be similar to those of Australian Rules football, rugby union, rugby league, field hockey, and lacrosse (Delahunt et al., 2011). The difference in chronological age between children in a single age group is known as relative age and its consequences as the RAE, whereby younger players are disadvantaged (Del Campo et al., 2010). The purpose of this study was to describe the physical and performance profile of sub-elite juvenile Gaelic Games players and to establish if a RAE is present in this cohort and any influence physiological moderator variables may have on this. Following receipt of ethical approval (EHSREC11-45), six sub-elite county development squads (Under-14/15/16 age groups, male, n=115) volunteered to partake in the study. Anthropometric data including skin folds and girths were collected. A number of field tests of physical performance including 5 and 20m speed, vertical and broad jump distance, and an estimate of VO2max were carried out. Descriptive data are presented as Mean SD. Juvenile sub-elite Gaelic Games players aged 14.53 0.82 y were 172.87 7.63 cm tall, had a mass of 64.74 11.06 kg, a BMI of 21.57 2.82 kg.m-2 and 9.22 4.78 % body fat. Flexibility, measured by sit and reach was 33.62 6.86 cm and lower limb power measured by vertical and broad jump were 42.19 5.73 and 191.16 25.26 cm, respectively. Participant time to complete 5m, 20m and an agility test (T-Test) was 1.12 0.07, 3.31 0.30 and 9.31 0.55 s respectively. Participant’s estimated VO2max was 48.23 5.05 ml.kg.min-1. Chi-Square analysis of birth month by quartile (Q1 = January-March) revealed that a RAE was present in this cohort, whereby an over-representation of players born in Q1 compared with Q2, Q3 and Q4 was evident (2 = 14.078, df = 3, p = 0.003). Kruskal-Wallis analysis of the data revealed no significant difference in any of the performance parameters based on quartile of birth (Alpha level = 0.05).This study provides a physical performance profile of juvenile sub-elite Gaelic Games players, comparable with those of other sports such as soccer and rugby. This novel data can inform us of the physical requirements of the sport. The evidence of a RAE is similar to that observed in other contact sports such as soccer and rugby league (Carling et al, 2009; Till et al, 2010). Although a RAE exists in this cohort, this cannot be explained by any physical/physiological moderator variables. Carling C et al. (2009). Scandinavian Journal of Medicine and Science in Sport 19, 3-9. Delahunt E et al. (2011). Journal of Athletic Training 46, 241-5. Del Campo DG et al. (2010). Journal of Sport Science and Medicine 9, 190-198. Delorme N et al. (2010). European Journal of Sport Science 10, 91-96. Till K et al. (2010). Scandinavian Journal of Medicine and Science in Sports 20, 320-329.

Recognising team activities from noisy data

Recently, vision-based systems have been deployed in professional sports to track the ball and players to enhance analysis of matches. Due to their unobtrusive nature, vision-based approaches are preferred to wearable sensors (e.g. GPS or RFID sensors) as it does not require players or balls to be instrumented prior to matches. Unfortunately, in continuous team sports where players need to be tracked continuously over long-periods of time (e.g. 35 minutes in field-hockey or 45 minutes in soccer), current vision-based tracking approaches are not reliable enough to provide fully automatic solutions. As such, human intervention is required to fix-up missed or false detections. However, in instances where a human can not intervene due to the sheer amount of data being generated - this data can not be used due to the missing/noisy data. In this paper, we investigate two representations based on raw player detections (and not tracking) which are immune to missed and false detections. Specifically, we show that both team occupancy maps and centroids can be used to detect team activities, while the occupancy maps can be used to retrieve specific team activities. An evaluation on over 8 hours of field hockey data captured at a recent international tournament demonstrates the validity of the proposed approach.

Representing and discovering adversarial team behaviors using player roles

In this paper, we describe a method to represent and discover adversarial group behavior in a continuous domain. In comparison to other types of behavior, adversarial behavior is heavily structured as the location of a player (or agent) is dependent both on their teammates and adversaries, in addition to the tactics or strategies of the team. We present a method which can exploit this relationship through the use of a spatiotemporal basis model. As players constantly change roles during a match, we show that employing a "role-based" representation instead of one based on player "identity" can best exploit the playing structure. As vision-based systems currently do not provide perfect detection/tracking (e.g. missed or false detections), we show that our compact representation can effectively "denoise" erroneous detections as well as enabe temporal analysis, which was previously prohibitive due to the dimensionality of the signal. To evaluate our approach, we used a fully instrumented field-hockey pitch with 8 fixed high-definition (HD) cameras and evaluated our approach on approximately 200,000 frames of data from a state-of-the-art real-time player detector and compare it to manually labelled data.

Representing team behaviours from noisy data using player role

Due to their unobtrusive nature, vision-based approaches to tracking sports players have been preferred over wearable sensors as they do not require the players to be instrumented for each match. Unfortunately however, due to the heavy occlusion between players, variation in resolution and pose, in addition to fluctuating illumination conditions, tracking players continuously is still an unsolved vision problem. For tasks like clustering and retrieval, having noisy data (i.e. missing and false player detections) is problematic as it generates discontinuities in the input data stream. One method of circumventing this issue is to use an occupancy map, where the field is discretised into a series of zones and a count of player detections in each zone is obtained. A series of frames can then be concatenated to represent a set-play or example of team behaviour. A problem with this approach though is that the compressibility is low (i.e. the variability in the feature space is incredibly high). In this paper, we propose the use of a bilinear spatiotemporal basis model using a role representation to clean-up the noisy detections which operates in a low-dimensional space. To evaluate our approach, we used a fully instrumented field-hockey pitch with 8 fixed high-definition (HD) cameras and evaluated our approach on approximately 200,000 frames of data from a state-of-the-art real-time player detector and compare it to manually labeled data.

A modified TRIMP to quantify the in-season training load of team sport players

Thatcher, Rhys, et al., 'A modified TRIMP to quantify the in-season training load of team sport players', Journal of Sport Sciences, (2007) 25(6) pp.629-634 RAE2008