Relationships Between Sprint, Jumping and Strength Abilities, and 800 M Performance in Male Athletes of National and International Levels

Bachero‐Mena, Beatriz; Pareja‐Blanco, Fernando; Rodríguez-Rosell, David; Yáñez-García, Juan Manuel; Mora-Custodio, Ricardo; González-Badillo, Juan José

doi:10.1515/hukin-2017-0076

Cited by 29 publications

(24 citation statements)

References 26 publications

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“…Regarding the sprint variables, a significant improvement of performance in 200 m throughout the season can be observed. This result shows that the distance of 200 m is probably more related to the performance in 800 m than other shorter distances as 20 m. Similarly, significant correlations between 800 and 300 m running times (Deason et al, 1991 ), and between 800 and 200 m have been found (Bachero-Mena et al, 2017 ). Therefore, strength and sprint-related variables seem to be relevant in the 800 m performance.…”

Section: Discussionmentioning

confidence: 67%

“…However, these events are shorter than the 800 m. In accordance with our findings, Hudgins et al ( 2013 ) observed significant correlations between jumping ability and 800 m race time in competitive runners. Likewise, significant correlations between CMJ, JS, and SQ with performance in 800 m in high-level athletes have been found (Bachero-Mena et al, 2017 ). Contrary to our study, Balsalobre-Fernández et al ( 2015 ) did not find significant improvements in strength parameters during an athletics season in middle and long-distance athletes.…”

Section: Discussionmentioning

confidence: 95%

“…The same occurred with the worst running competition, which was followed by the worst CMJ performances of the season. Recently, Bachero-Mena et al ( 2017 ) have found significant correlations between running performance in 800 m event and sprint times (20 and 200 m), squat strength and loaded and unloaded jumps height in 800 m high-level athletes. Despite the extensive published data confirming the strong correlation between strength manifestations and endurance performance (Mikkola et al, 2007 ; Taipale et al, 2010 , 2014 ), there are limited data on the long-term changes in strength variables associated with long-term middle-distance training.…”

Section: Introductionmentioning

confidence: 98%

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Enhanced Strength and Sprint Levels, and Changes in Blood Parameters during a Complete Athletics Season in 800 m High-Level Athletes

2017

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The purpose of this study was to analyze changes in sprint, strength, hematological, and hormonal parameters in high-level 800 m athletes during a complete athletics season. Thirteen male athletes of national and international level in 800 m (personal best ranging from 1:43 to 1:58 min:ss) participated in this study. A total of 5 tests were conducted during a complete athletics season. Athletes performed sprint tests (20 and 200 m), countermovement jump (CMJ), jump squat (JS), and full squat (SQ) tests. Blood samples (red and white blood profile) and hormones were collected in test 1 (T1), test 3 (T3), and test 5 (T5). A general increase in the performance of the strength and sprint parameters analyzed (CMJ, JS, SQ, 20 m, and 200 m) during the season was observed, with a significant time effect in CMJ (P < 0.01), SQ (P < 0.01), and 200 m (P < 0.05). This improvement was accompanied by a significant enhancement of the 800 m performance from T3 to T5 (P < 0.01). Significant changes in some hematological variables: hematocrit (Hct) (P < 0.01), mean corpuscular volume (MCV) (P < 0.001), mean corpuscular hemoglobin content (MCHC) (P < 0.001), white blood cells count (WBC) (P < 0.05), neutrophils (P < 0.05), monocytes (P < 0.05), and mean platelet volume (MPV) (P < 0.05) were observed throughout the season. The hormonal response and creatin kinase (CK) did not show significant variations during the season, except for insulin-like growth factor I (IGF-1) (P < 0.05). In conclusion, our results suggest the importance of strength levels in middle-distance athletes. On the other hand, variations in some hematological parameters and a depression of the immune system occurred during the season. Therefore, monitoring of the mechanical, hematological and hormonal response in athletes may help coaches and athletes to optimize the regulation of training contents and may be useful to diagnose states of overreaching or overtraining in athletes throughout the season.

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Section: Discussionmentioning

confidence: 67%

Section: Discussionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 98%

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Enhanced Strength and Sprint Levels, and Changes in Blood Parameters during a Complete Athletics Season in 800 m High-Level Athletes

2017

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“…At the very least, the addition of MSS allows for enhanced potential analysis (see Figures 1A,B ), and is a technically and methodologically easy addition to most study designs. However, very rarely, are any maximal speed/power and/or biomechanics based metrics reported or considered (despite considerable evidence showing them to be important performance determinants of MSS Weyand et al, 2000 , 2010 ; Morin et al, 2011 ; Rabita et al, 2015 ; Nagahara et al, 2019 ) as well as determinants of middle-distance race performance (Nummela et al, 1996 ; Bachero-Mena et al, 2017 ; Sandford et al, 2019a ).…”

Section: Middle-distance Running—the Event Group With Largest Diversimentioning

confidence: 99%

“Question Your Categories”: the Misunderstood Complexity of Middle-Distance Running Profiles With Implications for Research Methods and Application

Sandford

Stellingwerff

2019

Front. Sports Act. Living

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Middle-distance running provides unique complexity where very different physiological and structural/mechanical profiles may achieve similar elite performances. Training and improving the key determinants of performance and applying interventions to athletes within the middle-distance event group are probably much more divergent than many practitioners and researchers appreciate. The addition of maximal sprint speed and other anaerobic and biomechanical based parameters, alongside more commonly captured aerobic characteristics, shows promise to enhance our understanding and analysis within the complexities of middle-distance sport science. For coaches, athlete diversity presents daily training programming challenges in order to best individualize a given stimulus according to the athletes profile and avoid “non-responder” outcomes. It is from this decision making part of the coaching process, that we target this mini-review. First we ask researchers to “question their categories” concerning middle-distance event groupings. Historically broad classifications have been used [from 800 m (~1.5 min) all the way to 5,000 m (~13–15 min)]. Here within we show compelling rationale from physiological and event demand perspectives for narrowing middle-distance to 800 and 1,500 m alone (1.5–5 min duration), considering the diversity of bioenergetics and mechanical constraints within these events. Additionally, we provide elite athlete data showing the large diversity of 800 and 1,500 m athlete profiles, a critical element that is often overlooked in middle-distance research design. Finally, we offer practical recommendations on how researchers, practitioners, and coaches can advance training study designs, scientific interventions, and analysis on middle-distance athletes/participants to provide information for individualized decision making trackside and more favorable and informative study outcomes.

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“…In sport and everyday activities, one of the most important attributes of skeletal muscle is the ability to generate power, a product of strength and speed of movement [14]. Research has shown a strong relationship between strength, 20 m sprinting, and jumping performance in athletes and field sports athletes [15,16]. Another study [17] reported that a strong correlation exists between half-squat maximum strength, 30 m sprint performance, and jump height in soccer players.…”

Section: Introductionmentioning

confidence: 99%

Relationships between Resisted Sprint Performance and Different Strength and Power Measures in Rugby Players

Zabaloy

Carlos‐Vivas

Freitas

et al. 2020

Sports

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This study aimed to investigate the relationship between a specific isometric-strength sprint test (SIST) and unresisted maximum velocity (Vmax), sprint times across different loading conditions, and the velocity loss (Vloss) loads required to achieve each intended Vloss condition during resisted sprint training (RST) in rugby players. Additionally, the investigation examined the relationship between strength in the back-squat one-repetition maximum (1RM-SQ) as well as isometric squat (ISQT), jumps, and sprint performance variables. Twenty (n = 20) male amateur rugby players performed, on two separate occasions, a structural multiple-joint assessment of jumps, strength, and sprint performance. Interestingly, SIST revealed moderate correlations (r = 0.453 to 0.681; p < 0.05) between 1RM-SQ and ISQT. The SISTrel (relative to body mass), but not SIST, used in the present study showed moderate correlations (r = 0.508 to 0.675; p < 0.05) with the loads needed to reach 10%, 30%, and 50% of Vloss during RST. The SISTrel that measures resultant force application in a more sprint-related position explains much of the individual response of each athlete during sprinting towing a sled and can also be used to prescribe and quantify loads in the RST in a more objective and individual manner.

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Relationships Between Sprint, Jumping and Strength Abilities, and 800 M Performance in Male Athletes of National and International Levels

Cited by 29 publications

References 26 publications

Enhanced Strength and Sprint Levels, and Changes in Blood Parameters during a Complete Athletics Season in 800 m High-Level Athletes

Enhanced Strength and Sprint Levels, and Changes in Blood Parameters during a Complete Athletics Season in 800 m High-Level Athletes

“Question Your Categories”: the Misunderstood Complexity of Middle-Distance Running Profiles With Implications for Research Methods and Application

Relationships between Resisted Sprint Performance and Different Strength and Power Measures in Rugby Players

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