The physiological regulation of resting heart rate (RHR) involves multiple mechanisms, including myocardial morphology, plasma volume, autonomic nervous activity, age, and body position. Athletes undergoing high-intensity training or a congested competition schedule often exhibit elevated RHR, with an increase in heart rate during sleep also being observed (43). Standardized measurement of RHR typically requires subjects to lie supine for 10 min or to be taken immediately upon awakening in the morning, with nocturnal RHR being regarded as an ideal indicator for assessing training load intensity due to the exclusion of circadian rhythm interference (44).

However, the effectiveness of RHR as a tool for monitoring training load has yet to reach a consensus in existing research. Some studies have indicated that following intense competitions or training, athletes may develop overtraining syndrome (OTS), which is associated with a significant increase in RHR (40). Nevertheless, other literature suggests that there is no statistically significant difference in RHR between normal training and overtraining states (45). This perspective was elucidated in a systematic review, which found that short-term high-intensity interventions (<2 weeks) can cause a moderate increase in RHR (effect size ES = 0.45), whereas long-term interventions (>2 weeks) show no significant change in RHR (ES = 0.12) (45). These findings suggest that the dynamic changes in RHR are more sensitive to short-term fluctuations in training load but have limited indicative value for long-term training adaptation states.

In rugby, RHR monitoring can serve as an auxiliary indicator of acute fatigue accumulation during short-term high-intensity training or in periods of dense competition schedules. For instance, an increase in RHR can be used as a basis for adjusting athletes' load fatigue responses when there is a sudden increase in weekly training load (17). However, when incorporated into a longitudinal monitoring system throughout an entire season or used to monitor non-functional overreaching and OTS, its sensitivity and specificity are significantly limited (44). Therefore, in training, RHR should be used in conjunction with other monitoring indicators (such as HRV, blood markers) to enhance the accuracy of fatigue assessment.

During training, heart rate (HR)—related metrics such as exercise heart rate (HRex), heart rate reserve (HRres), maximum heart rate (HRmax), and percentage of maximum heart rate (%HRpeak) are widely utilized (42, 46). HRex serves as a crucial indicator for assessing training adaptation and fatigue status. Buchheit's research (42) has demonstrated a strong correlation between HRex and the increase in oxygen uptake (VO2), with changes in HRex reflecting athletes' adaptation to training.

To effectively manage training intensity in elite rugby players, heart rate (HR)—related metrics such as exercise heart rate (HRex) and maximum heart rate (HRmax) are widely utilized (47). HRex serves as a crucial indicator for assessing training adaptation and fatigue status. Monitoring the overall load in rugby players has shown that adult players' average heart rate during training or matches typically ranges from 75%–86% of their HRmax (17). This intensity level was defined as sub-maximal training. Importantly, these findings align with observations from other team sports, such as football, where similar heart rate responses have been documented during training and competition (48). This consistency further supports the practicality of using HRex as a reliable indicator for controlling training intensity.

In training practice, the setting and monitoring of exercise intensity are usually based on the %HRpeak method. However, heart rate is subject to interference from various factors, such as submaximal heart rate, which can vary by up to 6.5% daily (12). Therefore, when classifying low-, moderate-, and high-intensity training, other load monitoring indicators (such as blood lactate concentration) need to be integrated. Studies have shown that there is a significant correlation between high-intensity training time and changes in aerobic performance. In appropriate load training, a decrease in heart rate is usually associated with an improvement in aerobic capacity (49). However, in team sports, a decrease in players' heart rate during preseason training does not reflect fatigue but may be related to changes in plasma volume caused by training or the environment (50) Therefore, it is necessary to quantify training load and assess the physiological load of training by using a combination of multiple indicators (10, 41, 50).

Training impulse (TRIMP) is a heart rate-based method for quantifying training load, calculated by training duration × training intensity based on average heart rate, which can assess athletes' physiological stress levels (51). To accurately assess the load of interval training, the TRIMP algorithm has continued to evolve and has been combined with values such as lactate threshold and ventilatory threshold to optimize the assessment method. Several studies have used different TRIMP methods to assess the internal load in rugby training and matches and have confirmed that this method can establish a training dose-response relationship between training load and changes in maximum oxygen uptake (VO2max) (52).

In addition, the individualized TRIMP (iTRIMP) method is calculated based on individual lactate threshold. iTRIMP calculates the relationship between each person's HR changes and blood lactate concentration, monitors heart rate in real-time during training or matches, and weights it according to the relationship previously established by the athlete. This breaks through the limitations of the universal division of traditional heart rate zones and achieves precise quantification of individual-specific responses (17). Studies have shown that iTRIMP can accurately reflect the speed changes of professional youth football players at a lactate concentration of 2 mmol·L⁻¹ (12). In rugby training monitoring, iTRIMP also shows good applicability, especially in different training modes such as simulated matches, physical conditioning, technical and tactical training, speed training, and strength training, with high application value (53).

Heart rate recovery (HRR) refers to the rate of decline in heart rate after exercise stops and is an indicator for assessing athletes' autonomic nervous function and training status (12). Borressen and Lambert's (54) study found that when athletes maintain the same load training, HRR remains stable; increasing the training load slows down HRR, while reducing it can accelerate HRR recovery. HRR is usually calculated between 30 s and 2 min, with the most commonly used method being the difference between immediately after exercise and 60 s later. Studies have found that the higher the exercise intensity and the higher the peak heart rate, the faster the initial recovery speed (12). However, as exercise intensity increases, the heart rate recovery speed slows down, which may be related to the sustained activation of the sympathetic nerve. The impact of exercise duration on HRR is less than that of exercise intensity. Under the same internal training load, the HRR recovery speed of high-intensity short-duration training is slower than that of low-intensity long-duration training (55), indicating that high-intensity training leads to elevated heart rates and longer recovery times, and the body has not fully adapted yet.

Scott (47) conducted a two-week experiment on rugby players, testing HRR at 1 and 2 min after exercise. The daily fluctuation range under different exercise intensities and durations was ±4.6 and ±4.1 beats, respectively, showing good consistency. Borresen (54) further pointed out that to ensure accurate assessment of HRR, testing should be conducted after high-intensity training, with exercise intensity reaching 86%–93% of maximum heart rate. Although HRR can provide more precise monitoring effects after high-intensity training, for athletes who have accumulated a certain degree of fatigue, high-intensity training may increase the risk of injury or exacerbate fatigue. Therefore, the timing of testing needs to be carefully selected in practical applications (56).

Blood lactate (BLA) is one of the main indicators for assessing the training intensity of athletes, peaking about 3 min after exercise ends, and is therefore commonly tested immediately after training. Studies in rugby have shown that the peak BLA for male athletes is 2.9–20.2 mmol·L⁻¹, while for female athletes it is 3.4–14.6 mmol·L⁻¹ (62). Moreover, the clearance rate of BLA after exercise can reflect the body's recovery capacity; a faster clearance rate indicates better training status and aerobic capacity, while a slower rate suggests possible accumulation of fatigue or overtraining (63).

BLA concentration, often measured alongside heart rate and oxygen uptake, provides a comprehensive assessment of athletes' aerobic and anaerobic capabilities. In rugby, high-intensity activities like sprints rely primarily on anaerobic metabolism and cannot be sustained by aerobic metabolism alone (1). For example, Granatelli (64) reported BLA concentrations of 8.7 (1.7) mmol·L⁻¹ 2 min after halftime and 11.2 (1.4) mmol·L⁻¹ 2 min after an international match. Similarly, Couderc (65) found a BLA concentration of 11.7 ± 3.7 mmol·L⁻¹ following a sevens rugby match, aligning with Granatelli's findings (11.2 ± 1.4 mmol·L⁻¹) (64).

Post-match, the peak BLA concentration for sevens rugby players was approximately 16.3 (2.4) mmol·L⁻¹, whereas for fifteens rugby matches, the BLA concentration ranged from 4.8–7.2 mmol·L⁻¹ (62, 66). These data indicate that glycolysis plays a significant role in the energy supply of rugby players, and athletes need to possess a high capacity for acid tolerance to cope with high-intensity activities in successive matches (67) (Table 5).

Blood biochemical monitoring, as a core means of assessing athletes' functional status, can precisely quantify the relationship between training intensity, match load, and recovery process through periodic sampling (68). The standardized blood sampling procedure requires subjects to be in a fasting state and complete sampling between 8:00 and 9:00 in the morning (41).

When assessing the physiological function of rugby players, CK, aspartate aminotransferase (ASAT), and alanine aminotransferase (ALAT) are key indicators for evaluating muscle damage. CK is widely distributed in skeletal muscle, myocardium, and brain tissue, directly participating in muscle contraction and energy metabolism, with its level changes highly correlated with the degree of muscle fatigue. ASAT and ALAT also significantly increase after training or matches, and these indicators are highly sensitive to high-load training. Their concentration changes can not only monitor the liver function status of athletes but also assess muscle recovery (24, 67).

CK, a key enzyme in skeletal muscle energy metabolism, significantly increases following eccentric exercise and external impacts (68, 72). In rugby, CK levels rise sharply 30 min post-match, peak at 12–36 h (a 265.5% increase from baseline), and remain elevated at 72 h (21, 50, 69). However, some studies suggest that the reported 12–16 h “peak” may be due to a lack of measurements beyond 24 h, and recommend extending sampling times for more accurate assessments (70). Forwards, who experience more physical contact, show a significantly higher CK increase than backs (24 h: 285.1% vs. 167.9%; 48 h: 144.6% vs. 88.9%) (71). This highlights the specific distribution of sport-specific load fatigue. While long-term CK assessments (beyond 4 days) aid in understanding recovery, individual differences should be noted (70).

In addition, the resting CK levels of rugby players are significantly higher than those in other contact sports (such as football and basketball), and this difference may stem from adaptive changes to cumulative fatigue caused by frequent collisions over the long term (72). Therefore, particular attention should be paid to technical training, including collisions, in training to avoid injuries and overtraining (73).

Changes in blood components such as C-reactive protein, hemoglobin, white blood cells, and neutrophils can be systematically monitored during high-intensity matches and training to scientifically assess athletes' recovery status and health levels (17, 72). Studies have shown that hemoglobin concentration often changes during training, especially after high-intensity exercise (67). In the early stages of training, changes in hemoglobin concentration are mainly due to an increase in plasma volume, leading to hemodilution. However, as high-intensity training continues, erythropoiesis is inhibited (6, 68). This biphasic change may reduce blood oxygen-carrying efficiency, thereby affecting athletic performance.

White blood cell (WBC) and its subpopulation analysis reveal the dynamic balance mechanism of immune function. The increase in total WBC count after matches or high-intensity training is mainly due to a significant increase in neutrophils (PMN), accounting for 70% of the increase in WBC (72). This change is usually associated with muscle fatigue, inflammatory response, and recovery process induced by exercise. However, despite the increase in WBC and neutrophil counts, their functional capacity may not be enhanced synchronously. Studies have shown that in continuous rugby exercise without adequate recovery, although an increase in cell numbers is observed, the function of neutrophils (such as degranulation) significantly decreases (−65%) (7). Monitoring the changes in WBC and neutrophil counts can effectively assess whether athletes have overtraining or other health issues.

C-reactive protein (CRP) levels are compared immediately after matches to baseline levels, showing an increase of up to 9.8% (74). Further studies indicate that CRP rises to 64.1% and 121.6% of baseline at 16 and 24 h post-match, respectively, peaking at 201.0% of baseline within 24–48 h and returning to baseline within 72 h (21). CRP appears more sensitive than creatine kinase (CK) in reflecting muscle fatigue and recovery related to collisions (23). Additionally, a decrease in plasma glutamine levels and an increase in glutamate levels reduce the glutamine-to-glutamate ratio. A ratio below 3.58 suggests increased training load (75). This decline in glutamine may be linked to increased gluconeogenesis due to glycogen depletion, which promotes greater amino acid uptake (76). However, limited research connects glutamine reduction to impaired immune function (73), so further studies are needed to confirm the utility of the glutamine-to-glutamate ratio as a fatigue marker.

Interleukin-6 (IL-6), an inflammatory cytokine, has been extensively studied as a marker of fatigue and overtraining. IL-6 levels significantly increase following exercise, particularly after high-intensity and prolonged activities, with its elevation being closely associated with muscle damage and inflammatory responses (72). Research indicates that the rise in IL-6 not only reflects the extent of muscle damage but may also play a role in modulating immune responses and facilitating the recovery process (72). Therefore, monitoring IL-6 levels can provide valuable insights into athletes' training loads and recovery status.

Hormonal indicators play a crucial role in assessing athletes' endocrine status, their adaptation to training load, and their recovery status. Testosterone (T) and cortisol (C) serve as critical biomarkers for evaluating training adaptation and recovery. T mediates anabolic processes including protein synthesis and glycogen replenishment (77). Post-exercise T responses indicate load appropriateness: unchanged levels suggest insufficient stimulus; 10%–20% decreases reflect optimal adaptation; while sustained drops >25% signal excessive load requiring intervention (78). These hormonal patterns enable precise training load management to prevent overtraining.

C levels are closely tied to training load, increasing during both endurance and resistance training (8). It reflects both physiological stress from high-intensity exercise and psychological stress from competitive environments (79). Before rugby matches, excitement, anxiety, and stress can alter cortisol and testosterone levels. During training, decreased testosterone and increased cortisol often indicate an imbalance between anabolic and catabolic processes (80). Post-match, cortisol may rise by 30.0%–52.5%, and testosterone may drop by about 43%, reducing the testosterone-to-cortisol (T/C) ratio significantly. This ratio continues to decline for up to 36 h and remains elevated for up to five days (17, 23, 72), aligning with findings in elite rugby (81). A significant increase in the T/C ratio suggests the body's response to high training loads by boosting testosterone to aid muscle repair and synthesis (72).

In Dubois's study (23), the focus was on the changes in insulin-like growth factor (IGF-1). The ratios of these indicators (such as the T/C ratio and IGF-1/C ratio) provide insights into fatigue and recovery in rugby players. IGF-1 shows high sensitivity to training and match loads (50). The accumulation of long-term training load correlates positively with IGF-1 levels, reflecting the recovery and regeneration processes following muscle fatigue. Changes in the IGF-1/C ratio and T/C ratio can serve as indicators of training status and help monitor non-functional overreaching (68, 82).

Saliva, as a non-invasive biological sample, offers several advantages such as ease of collection, safety, and cost-effectiveness. Its protein content is lower compared to serum (80). Salivary secretory immunoglobulin A (S-IgA) is one of the key indicators for assessing the immune system health of athletes. Studies have shown that in rugby players, S-IgA secretion rates decrease from an average of 401.3 µg/min pre-match to 298.3 µg/min post-match, with variations observed among players in different positions (50, 83, 84). Monitoring changes in S-IgA can help assess the immune function of rugby players during high-intensity training or matches, thereby revealing the impact of exercise intensity on the immune system (Table 5).

The concentrations of cortisol and testosterone in saliva accurately reflect the adrenal cortex's adaptive response to exercise intensity. As exercise intensity and duration increase, the rise in cortisol levels becomes more pronounced (84). Monitoring before and 30 min after matches shows an increase in cortisol levels, peaking 30 min post-match (85). It is important to note that pre-match cortisol levels also reflect the athlete's psychological state, influenced by cognitive expectations and perceived anxiety, often used to regulate pre-match excitement (70). Therefore, the significant post-match increase in cortisol may be influenced by psychological factors and differences in exercise type and duration.

Regarding the assessment of muscle fatigue, there is currently debate over the changes in enzyme indicators such as CK, aspartate aminotransferase (AST), and lactate dehydrogenase (LDH) in saliva before and after matches. González (69) found no significant differences in CK and LDH concentrations before and after matches, despite high RPE according to the Borg scale. In contrast, Barranco (86) observed significant changes in these enzyme indicators 30 min and 12 h post-match, with levels remaining elevated up to 24 h afterward (80). This discrepancy may be due to differences in the timing of sample collection, indicating a delay in the transfer of these enzymes from blood to saliva.

Therefore, it is essential to consider the cumulative effects of exercise load and the timing of sample collection. Changes in salivary enzyme indicators typically become apparent only after a certain period of load accumulation. For instance, significant changes in salivary AST levels were observed only after four weeks of aerobic exercise intervention (87). This suggests that changes in salivary enzyme indicators are time-dependent.

Studies in football have shown that salivary CK and LDH levels increase 30 min post-match, while AST levels remain unchanged, possibly due to lower sensitivity of AST in saliva (86). In rugby research, male players exhibited higher CK and LDH levels before and after matches, with LDH being the only enzyme showing no gender differences (69, 83), indicating potential gender differences in enzyme responses. Further research has shown that physiological responses to exercise also vary by gender. For example, females exhibit higher heart rates and RPE levels post-exercise, while males show more pronounced declines in strength, suggesting that females may have better fatigue resistance when facing the same load (88). Additionally, studies have indicated that females have a lower incidence of muscle damage and a more gradual increase in serum CK levels after injury (89), highlighting the need to consider gender differences when assessing salivary enzyme indicators.

Urine markers serve as crucial tools for assessing athletes' health and metabolic status, operating within the domain of metabolomics. By examining fluctuations in metabolites, these markers uncover the fundamental sources of endogenous substances and energy supply within the body during exercise. Monitoring the dynamic changes in metabolic biomarkers post-exercise aids in elucidating the patterns of potential biological indicators associated with exercise (90) (Table 5).

The cortisol/corticosterone (C/Cn) ratio and adrenaline/noradrenaline (A/NA) ratio, reflecting HPA and SAM axis activity, are key indicators of athletes' stress and recovery (91, 92). These hormones show significant changes in endurance sports like swimming and running (93). High-intensity training increases C, Cn, and the C/Cn ratio by +27%, +13%, and +22%, respectively, while A and NA levels drop by −30% and −25% (91, 93). These markers return to baseline after a two-week recovery. NA is mainly affected by physical stress, while A is more influenced by psychological stress (94). Monitoring training load should include both physiological and psychological aspects, with regular use of the Session-RPE test to prevent overtraining (31, 91).

Despite temporary disturbances in homeostasis during high-intensity training, levels of C, Cn, and the A/NA ratio return to baseline after a brief adjustment period, coinciding with performance improvement. This recovery period facilitates performance enhancement through supercompensation, further underscoring the importance of adequate recovery in preventing overtraining. Overall, levels of C, Cn, A, and NA and their ratios, particularly the C/Cn ratio, in urine serve as effective biomarkers for monitoring changes in training load, fatigue, and performance. Changes in the SAM and HPA axes reflect athletes' physiological adaptation to long-term training, offering a multi-faceted basis for monitoring the training of elite athletes.

Urine metabolites and physicochemical parameters can indicate exercise-induced bodily changes. In rugby players, post-match urine creatinine levels rise significantly, reflecting muscle metabolic function (93). Urine specific gravity (SG), a measure of urine concentration and hydration status, also increases. The World Anti-Doping Agency (WADA) suggests using SG to assess overhydration (SG > 1.030) and dehydration (SG < 1.003). Additionally, other parameters of urine samples, such as urine color and osmolality, also have certain reference value for understanding athletes' hydration status (41).

In rugby, there is a significant decrease in urine pH from pre-match to post-match (P = 0.002), dropping from 6.33 ± 0.6–5.67 ± 0.36 (95, 96). This change indicates that high-intensity exercise may lead to the accumulation of acidic metabolic products in the body, thereby affecting the acid-base balance of urine.

In their study on rugby union, Lindsay (96) observed that, after correction for urine specific gravity, levels of neopterin increased 1.75-fold and total neopterin increased 2.3-fold. These markers exhibited a significant post-game increase, returning to baseline within 17 h. Their temporal changes suggest that neopterin and total neopterin can serve as novel indicators for detecting acute inflammatory responses, particularly in the context of physical exercise (96). It is important to note that individual athletes exhibited substantial variability in their responses to game-related stress, underscoring the critical importance of personalized monitoring.

Similar to hormonal changes, urinary myoglobin effectively quantifies exercise load, with post-match levels (17.5 ± 12.6 ng/ml) significantly exceeding pre-match values (6.2 ± 5.7 ng/ml; p < 0.05, η² = 0.353) and normalizing within 17 h (6.8 ± 6.9 ng/ml) (95). As a sensitive muscle fatigue marker, its plasma/urine concentrations correlate with collision frequency—professional rugby matches elevate levels from <5 ng/ml pre-match, with greater increases after consecutive games (96, 97). Variability between matches depends on competition level, sampling timing, and individual differences (69, 96, 97), necessitating pH adjustment and standardized analysis timing for reliable measurements.