Relationship Between Individualized Training Impulse and Aerobic Fitness Measures in Hurling Players Across a Training Period

The current study examined the association between individual internal training load (individualized training impulse, iTRIMP) and aerobic fitness variables in male hurling players. Twenty hurling players (age, 25.5 ± 3.2 years; height, 178.9 ± 3.2 cm; body mass, 78.5 ± 4.5 kg) performed treadmill testing for V[Combining Dot Above]O2max, running economy (RE), and the speed at blood lactate concentrations of 2 mmol·L (S2) and 4 mmol·L (S4) on separate occasions before and after an 8-week training period. The Yo-Yo intermittent recovery (Yo-YoIR1, Yo-YoIR2) test performance were also assessed before and after the training period. Individualized training impulse was calculated using the blood lactate and heart rate profile of each individual player and was further assessed for each training session across the intervention period (n = 990). The results showed that iTRIMP had large to very large association with the percentage improvements in V[Combining Dot Above]O2max (r = 0.77; p = 0.002; 95% confidence interval [CI], 0.38-0.93, very large), RE (r = 0.78; p = 0.002; 95% CI, 0.40-0.93; very large), S2 (r = 0.64; p = 0.004; 95% CI, from 0.25 to 0.85; large), S4 (r = 0.78; p = 0.003; 95% CI, 0.45-0.85; very large), Yo-YoIR1 (r = 0.69; p = 0.003; 95% CI, 0.45-0.92; large), and Yo-YoIR2 (r = 0.60; p = 0.005; 95% CI, 0.45-0.92; large) performance. The study shows that iTRIMP is a means of quantifying training load in team sports and can be used to prescribe training for the maintenance or improvement of aerobic fitness during the competitive season with strong relationships seen between weekly iTRIMP measures and improvements in aerobic fitness measures

Yo-Yo Intermittent Recovery Test Performance in Subelite Gaelic Football Players from under Thirteen to Senior Age Groups

Gaelic football is indigenous to Ireland and has similar locomotion profiles to soccer and Australian Football. Given the increasing attention on long-term player development, investigations into age-related variation in Yo-YoIR1 performance may provide useful information in talent identification, programme design, and player monitoring. Therefore, the aim of this study was to evaluate Yo-YoIR1 performance across Gaelic football age groups. Male participants (n = 355) were recruited from division one, Gaelic football teams. Participants were allocated to one of seven groups according to respective age groups from under 13 (U13), under 14, under 15 (U15), under 16 (U16), minor, under 21 (U21), to senior age groups. Total Yo-YoIR1 distance (m) increased progressively from U13 (885 ± 347 m) to U16 (1595 ± 380 m) equating to a rate of change of 180.2%. In comparison to U13, total distance at minor (1206 ± 327 m) increased by 136.4%. Subsequent increases were observed in U21 (1585 ± 445 m) and senior players (2365 ± 489). Minimum (800-880 m) and maximum (2240-2280 m) total distances were comparable for U15, U16, and U21 players. Differences in total distance (m) for all age groups were statistically significant when compared to U13 players (p\u3c0.002). In comparison to U13 players the magnitude of differences between age groups for total distance were deemed to be large (ES \u3e0.8). Similar trends were observed for maximum velocity and estimated VO2max. The evolution of Yo-YoIR1 performance in Gaelic football players from adolescents to adulthood highlights how maturation may influence sport-related running ability. Changes in Yo-YoIR1 performance should be closely monitored to optimise interventions for individuals transitioning across age groups

Effect of game design, goal type, and player numbers on the physiological and physical demands of hurling-specific small-sided games

The current study examined the effect that game design modification, goal type, and player numbers on the running performance and physiological demands of small-sided hurling games (SSG). Forty-eight hurling players (age, 25.5 ± 3.2 years; height, 178.9 ± 3.2 cm; body mass, 78.5 ± 4.5 kg) performed 4 types of SSG (possession [P], normal play [NP], regular goals [RG] and small goals [SG]) in 4-a-side, 5-a-side, and 6-a-side formats. Heart rate (Polar Electro Oy) and global positioning system technology (VX Sport, 4-Hz, Lower Hutt) were used to analyze the physical and physiological differences between SSG. Total distance (m), high-speed running distance (m) (≥17 km·h), very-high speed running distance (≥22 km·h) (m), peak and mean velocity (km·h) were analyzed as an indicator of the physical demands of play. The 4-a-side SSG independent of game design and goal type resulted in a significantly higher relative exercise intensity compared with 5-a-side (mean change: 6 ± 2%; p = 0.001; d = 1.9 ± 0.2; large) and 6-a-side SSG independent of game design or goal type (mean change: 12 ± 2%; p = 0.001; d = 2.9 ± 0.8; very large). The 4-a-side SG (619 ± 106-m [419-735-m]) resulted in the highest distance when compared with all PP (mean change: 141 ± 9 m; p = 0.05; d = 1.9 ± 0.3; moderate) and RG (mean change: 119 ± 39 m; p = 0.004; d = 2.1 ± 0.8; large). Similar trends were observed for 5-a-side and 6-a-side games with SG resulting in increased total running performance. In conclusion, the current observations reveal that 4-a-side NP, SG, and RG have the highest physiological demands with 4-a-side SG having increased running performance in contrast to other game design and goal-type games. Furthermore, independent of game design and goal type, 4-a-side SSG show increased relative intensity compared with 5-a-side and 6-a-side SSG

The influence of pitch size on running performance and physiological responses during hurling-specific small-sided games

The current study examined how the impact of pitch dimensions influences physiological and running performance during 4-minute small-sided games (SSGs). Twenty-four (n = 24) hurling players were monitored with global positioning system and heart rate monitors during the in-season training period. Total distance (in meters), high-speed running distance (in meters) (≥17 km·h), very high-speed running distance (≥22 km·h) (in meters), total accelerations (n), acceleration distance (in meters), and peak and mean velocity (in kilometers per hour) were calculated. Additionally, SSGs rate of perceived exertion (RPESSG; AU), % maximum heart rate, and individualized training impulse (iTRIMP; AU) were collected. The current results show that the manipulation of SSGs pitch size has an impact on the running performance and physiological responses. The data showed that SSGs played on large pitches (SSG80 × 20 m) had greater running demands than medium (SSG60 × 20 m) or small (SSG40 × 20 m) pitches, with significantly more distance covered in all movement categories. Total distance covered at high speed was 354 ± 111 m on a large pitch, 254 ± 72 m on a medium pitch, and 198 ± 62 m on a small pitch. Large pitch dimensions resulted in greater physiological and perceptual demands on players (higher %HRmax, iTRIMP [AU], and RPESSG [AU]) compared with medium and small pitches. The current data help applied practitioners to understand further how modifying different aspects of SSGs can alter the running and physiological responses of players. Moreover, applied practitioners now have consistent information to design and optimize their training time in mixing the physical, technical, and tactical elements within specific SSGs pitch dimensions

The running performance profile of elite gaelic football match-play

The current study examined (a) the match running performance of Gaelic football and (b) the decrement in match running performance with respect to position. Global positioning satellite system technologies (4-Hz; VX Sport) were used with 3 elite intercounty teams across 3 full seasons with 250 full game data sets collected. Game movements were classified according to game actions and distance covered across speed zone thresholds (total distance [TD], high-speed running distance [HSRD; ≥17 km·h], sprint distance [SD; ≥22 km·h]; accelerations [n]; peak speed [km·h]). The influence of running performance in each quarter on the subsequent quarter was analyzed across all positional roles. The mean (±SD) TD and HSRD covered during the game were 8,889 ± 1,448 m and 1,596 ± 594 m, respectively. Results show a temporal profile for TD with reductions in the second (-4.1%), third (-5.9%) and fourth (-3.8%) quarters, respectively. There was a significant reduction in HSRD in the second (-8.8%), third (-15.9%), and fourth (-19.8%) quarters when compared to the first quarter (p \u3c 0.001). Positional differences were observed for distance-based measures with the middle 3 positions (half-back, midfield, and half-forward) completing the highest running performances. These positions also showed increased decrements in TD and HSRD and SD across quarters. The current data indicate a reduction in exercise intensity over the duration of elite Gaelic football match-play. It is unclear if this reduction is because of fatigue, pacing, contextual factors, or nutritional strategies employed by players

The running performance and estimated energy cost of hurling specific small-sided games

The current study examined the extent to which pitch dimensions can influence the physical and estimated energetic demands of hurling small-sided games. Training data (n = 990) were collected from 24 (age 25.5 ± 3.2 years; height 178.9 ± 3.2 cm; body mass 78.5 ± 4.5 kg) hurling players using 4-Hz global positioning system technology (VX Sport, Lower Hutt, New Zealand). Total distance (m), high-speed running distance (m; ≥ 17 km/h), very high-speed running distance (m; ≥ 22 km/h), total accelerations (n), acceleration distance (m), peak and mean velocity (km/h) were considered. In addition changes in velocity were analysed by assessing the acceleration actions during SSG. This allowed for the assessment of estimated energy expenditure (kJ/kg) and the equivalent distance covered a different metabolic power thresholds. The main findings show that traditional speed-based data increased as pitch dimensions were increased (p = 0.002; d = 4.53 ± 0.46; very large). Furthermore, as relative player area increased there was an increase in estimated energy expenditure (p = 0.004; d = 2. 16 ± 0.20; very large) and average metabolic power metrics (p = 0.002; d = 1.13 ± 0.46; moderate). Distances covered at metabolic power categories (TP) increased with small-sided games pitch dimension (p = 0.002; d = 0.3 ± 0.06; small). The study enables coaches to better understand the physical demands imposed on players during specific hurling small-sided games pitch dimensions, and highlights that traditional speed-based data underestimate the running demands of small-sided games

Are small-sided games an effective training methodology for improving fitness in hurling players? A comparative study of training methodologies

The current investigation compared the effects of specific small-sided games training versus generic continuous aerobic training on team sport related exercise performances. Forty-eight hurling players (age: 25 ± 6.4 years; height: 180.2 ± 20.4 cm; mass: 80.5 ± 3.2 kg; V·O2max role= presentation style= display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative; \u3eV⋅O2maxV·O2max: 58.78 ± 3.05 ml·kg·min−1) completed either traditional continuous aerobic training (n = 24) or team sport-specific small-sided game training (n = 24), consisting of 4 × 4 min with 3-min active recovery periods completed twice per week. The following outcomes were measured at baseline (pre) and after 10 weeks (post): maximum oxygen uptake (ml·kg−1·min−1), running economy (ml·kg−1·min−1), maximal aerobic speed (km·h−1), Yo-Yo intermittent recovery test level 1 (m), Yo-Yo intermittent recovery test level 2 (m), repeated sprint ability (RSA; s), linear sprint speed over 5, 10 and 20 m (s) and counter-movement jump performance (cm). Training load was quantified by heart rate and rating of perceived exertion during all training sessions with no significant difference between groups (P = 0.12). Small-sided game (P = 0.002; d = 1.72; likely beneficial) had a likely beneficial effect for improving running economy (ml·kg−1·min−1) in contrast to the unclear effect for continuous training (P = 0.94; d = 0.21; unclear). Small-sided game (P = 0.04; d = 0.80; likely beneficial) had a likely beneficial effect for changes in RSAb (s) and RSAt (s) with these being in contrast to the likely negative effect for continuous training on similar measures (P = 0.12; d = −2.01; likely negative). Continuous training had a trivial (P = 0.72; d = 0.30; trivial) effect on Yo-Yo intermittent recovery test level 1 (m) performance in contrast to the likely beneficial effect seen for small-sided game (P = 0.002; d = 1.72; likely beneficial). Small-sided game (P = 0.001; d = 1.69; likely beneficial) resulted in a likely beneficial effect for Yo-Yo intermittent recovery test level 2 (m) performance with a likely negative effect for continuous training (P = 0.004; d = −2.40; likely negative). The current study suggests that small-sided games are a time efficient and effective method of improving fitness characteristics within hurling cohorts

Case Study: Transition to a Vegan Diet in an Elite Male Gaelic Football Player

Vegan diets are increasingly of interest to athletes, but require a well-planned approach in order to mitigate the risk of potential adverse effects on nutrient intakes, and consequently performance. This case study reports the process of an elite male Gaelic football player (age 25 years; height, 1.88 m; body mass, 87.8 kg; lean body mass, 73.26 kg; body fat, 11.3%) transitioning from an omnivorous diet to a vegan diet at the beginning of a competitive season. The report encompasses key considerations in the planning and provision of nutrition support in this context, in addition to iterations needed based on challenges presented by the athlete. Analysis of nutrient intake (Nutritics Dietary Analysis Software), body composition (dual X-ray absorptiometry; Lunar iDXA, GE Healthcare), and running performance during match-play (global positioning system-based tracking; STATSports Apex) each indicated that with adequate knowledge and education, and appropriate planning, commitment and iterative feedback, the athlete was able to meet nutrition targets on a vegan diet without compromising key performance indicators compared to the omnivorous diet of the previous season. We anticipate that this case study will assist practitioners to recognize the key considerations to address when working with athletes transitioning to a vegan diet

The integration of internal and external training load metrics in hurling

The current study aimed to assess the relationship between the hurling player’s fitness profile and integrated training load (TL) metrics. Twenty-five hurling players performed treadmill testing for VO2max, the speed at blood lactate concentrations of 2 mmol•L-1 (vLT) and 4 mmol•L-1 (vOBLA) and the heart rate-blood lactate profile for calculation of individual training impulse (iTRIMP). The total distance (TD; m), high speed distance (HSD; m) and sprint distance (SD; m) covered were measured using GPS technology (4-Hz, VX Sport, Lower Hutt, New Zealand) which allowed for the measurement of the external TL. The external TL was divided by the internal TL to form integration ratios. Pearson correlation analyses allowed for the assessment of the relationships between fitness measures and the ratios to performance during simulated match play. External measures of the TL alone showed limited correlations with fitness measures. Integrated TL ratios showed significant relationships with fitness measures in players. TD:iTRIMP was correlated with aerobic fitness measures VO2max (r = 0.524; p = 0.006; 95% CI: 0.224 to 0.754; large) and vOBLA (r = 0.559; p = 0.003; 95% CI: 0.254 to 0.854; large). HSD:iTRIMP also correlated with aerobic markers for fitness vLT (r = 0.502; p = 0.009; 95% CI: 0.204 to 0.801; large); vOBLA (r = 0.407; p = 0.039; 95% CI: 0.024 to 0.644; moderate). Interestingly SD:iTRIMP also showed significant correlations with vLT (r = 0.611; p = 0.001; 95% CI: 0.324 to 0.754; large). The current study showed that TL ratios can provide practitioners with a measure of fitness as external performance alone showed limited relationships with aerobic fitness measures

Quantifying The Training and Match-Play External and Internal Load of Elite Gaelic Football Players

The current investigation quantified the training and match-play load of elite Gaelic football players across a two-season period using global positioning system technology (GPS), rating of perceived exertion (RPE) and sessional rating of perceived exertion (sRPE). Total weekly workload variables were collected across GPS, RPE, and sRPE across thirty-six elite Gaelic footballers (mean ± SD, age: 26 ± 5 years; height: 177 ± 8 cm; mass: 81 ± 7 kg) from one elite squad during a two-season observational period. External training load variables included: Total distance (m), High speed running (m; ≥ 17.1 km·h −1 ), Sprint distance (m; 22 km·h −1 ), Accelerations (n), Average metabolic power (W·kg−1 ), High-power distance (m; ≥ 25 W·kg−1 ). Internal load variables included: sRPE and RPE. Repeated measures ANOVA were used to understand the differences in loading patterns across phases, position, and week types when significant main effects were observed a Tukey’s post hoc test was applied and standardized effect sizes were calculated to understand the practical meaning of these differences. When total weekly loading across phases was considered total load was significantly greater in club 1 and provincial 1 with these phases showing the highest loading for players when compared to all other phases (p ≤ 0.001; ES: 2.95–7.22; very large). Furthermore, in-season 1 was greater for total loading when compared to in-season 2 and both championship phases (p ≤ 0.05; ES: 0.47–0.54; small). Total distance in training was greater during preseason 1 when compared to all other phases of the season (p ≤ 0.001; ES: 2.95–7.22; very large). During the in-season period, training based total distance was higher during provincial 1 when compared to other phases with similar trends across all measures (p ≤ 0.005). Finally, a positional profile for load measures was observed, with weekly context (match or non-match) having an impact on the internal and external loading players experienced across phases. The current data provide useful information for practitioners on the training periodization currently present within the elite Gaelic football training process. Specifically, the data provide positional profiles of loading across weekly and segmented phased of an elite Gaelic football season. These data can increase understanding as to the periods of increased and decreased loading across different phases of an elite Gaelic football season, while providing a framework for future analysis concerning Gaelic football periodization