Although circadian clocks have been studied extensively in controlled laboratory settings, examining the function and misalignment of these biological clocks in natural settings has been more challenging. Here, we examined data from Major League Baseball (MLB) where players frequently travel long distances in the east–west direction. By using 20 years of MLB data, we found the effect of jet lag to be context dependent and remarkably specific. Overall, our findings demonstrate how circadian misalignment can impact specific features of human performance in natural settings.

Laboratory studies have demonstrated that circadian clocks align physiology and behavior to 24-h environmental cycles. Examination of athletic performance has been used to discern the functions of these clocks in humans outside of controlled settings. Here, we examined the effects of jet lag, that is, travel that shifts the alignment of 24-h environmental cycles relative to the endogenous circadian clock, on specific performance metrics in Major League Baseball. Accounting for potential differences in home and away performance, travel direction, and team confounding variables, we observed that jet-lag effects were largely evident after eastward travel with very limited effects after westward travel, consistent with the >24-h period length of the human circadian clock. Surprisingly, we found that jet lag impaired major parameters of home-team offensive performance, for example, slugging percentage, but did not similarly affect away-team offensive performance. On the other hand, jet lag impacted both home and away defensive performance. Remarkably, the vast majority of these effects for both home and away teams could be explained by a single measure, home runs allowed. Rather than uniform effects, these results reveal surprisingly specific effects of circadian misalignment on athletic performance under natural conditions.

Although we know much about circadian clock function from highly controlled laboratory studies, less is known about the specific functions of these clocks under natural conditions, especially in humans. In constant laboratory conditions, clocks drive a wide range of behavioral and physiological rhythms, which are approximately, but not exactly, 24 h (1). In addition, these near-24-h rhythms can be synchronized to and aligned with the 24-h environment via light. Rapid long-distance east–west travel can desynchronize internal clocks from the external 24-h environment, resulting in symptoms collectively known as “jet lag” (2, 3). These include poor sleep, fatigue, gastrointestinal disturbance, and impaired motor performance. To discern the role of circadian alignment under natural conditions in humans, researchers have examined the effects of jet lag on athletic performance and have found effects on broad aggregate performance parameters such as winning percentage or total points scored (4⇓⇓⇓⇓⇓⇓–11). It has been widely assumed that jet lag impacts a broad range of parameters under a wide variety of conditions. Here, we mined 20 seasons of Major League Baseball (MLB) data to examine the precise aspects of human performance that underlie the effects of jet lag. Specifically, we asked whether jet lag differentially affects the home and away teams and whether it affects all or only specific features of performance, and if so, which ones?

Results

To ensure sufficient statistical power and robust conclusions, we analyzed 20 y of data from MLB (1992–2011), encompassing 46,535 games analyzed for effects of jet lag on performance. From the perspective of both the home and away teams, we found 4,919 instances of teams having at least 2 h of jet lag (Tables S1 and S2). Jet lag was determined by the number of time zones crossed and the number of days since travel, following the general rule of thumb that human circadian clocks resynchronize toward their destination time at a rate of ∼1 h/d (12, 13). Given the relatively small number of games involving jet lag of 3 h (Table S1) and the fact that the International Classification of Sleep Disorders diagnosis of Jet Lag Disorder requires travel across at least two time zones (14), we defined jet lag as those games where a team had at least a 2-h jet lag, that is, teams that traveled across at least two time zones, accounting for adaptation to the new time zone (Methods). Teams that were shifted 1 h or less after adaptation were not considered to be jet lagged. Combining the 2- and 3-h jet-lag groups allowed us to maximize the size of the jet-lag group and thus the power to detect jet-lag effects.

Importantly, we also accounted for potential confounding variables, such as home-field advantage and team effects. Because home teams were less often jet lagged, i.e., upon return travel home (Table S1), differences attributed to jet lag could be due to home-field advantage, i.e., the general advantage a team displays at home. In our analysis, we analyzed home- and away-team jet-lag effects separately. In addition, it is possible that high-performing teams may not be randomly distributed between the jet-lag and non–jet-lag groups and thus, differences between the two groups may instead be due to the differential composition of team quality between those groups. By controlling for the home team, this approach also controls for potential park effects. Thus, we controlled for many potential confounding factors when analyzing game data; see Methods (and below) for further details.

We also considered jet-lag effects as a function of eastward or westward direction of travel. Because the human endogenous circadian period is longer than 24 h (15, 16), it is generally thought to be easier to adjust to westward travel that delays sunrise/sunset, than eastward travel (17). Nonetheless, westward travel has been found to be more deleterious in some cases (7, 10, 11). This latter effect has been attributed to the teams traveling west performing further from their optimal time-of-day than their host teams that are not typically jet lagged do, enhancing jet-lag effects.

We performed a multivariate linear regression analysis, including home- and away-team jet-lag variables considering travel direction (greater than or equal to two or more time zones with one time zone/day adjustment) and home- and away-team variables, to determine whether away- or home-team jet lag contributed to performance independent of each other and team (Table 1, and see Methods). A detailed description of the model used is provided in Methods. In general, the effects of eastward travel on winning percentage exceeded those of westward travel, which were consistent with the >24-h endogenous period. However, only eastward travel by the home team reached statistical significance (home eastward travel, P < 0.05). It is well established that the home team has a systematic advantage over the away or visiting team. In terms of winning percentage over the time period of our analysis, the home team won 53.9% of its games, corresponding to an advantage of +3.9%. In fact, the home-team eastward travel effect (−3.5%, P < 0.05) was comparable in magnitude to this home-field advantage (+3.9%). Thus, if the home team traveled two time zones east, and the away team was visiting from the same time zone, the home-field advantage was essentially nullified. On the other hand, the effect of traveling west was smaller and did not reach statistical significance (−2.0%, P = 0.11), suggesting direction selectivity. Interestingly, for the away team, the effects of traveling east on winning percentage were also larger than those traveling west, although eastward effects did not reach statistical significance (−2.1%, P = 0.075). The direction-selective effects, at least for the home team, suggest that they are due to circadian misalignment and not due to a general effect of travel.

Table 1. Effect of travel direction on the impact of jet lag on home and away winning and aggregate offensive performance

To determine the basis of these effects, we examined the effects of jet lag on major parameters of home- and away-team offense, such as runs scored and batting average. Surprisingly, we found that home- and away-team offenses were differentially impacted by jet lag on one of these parameters, slugging percentage (total bases/at-bats). Like winning percentage, these home-team effects were direction selective, evident after eastward (P < 0.05) but not westward travel (P = 0.327), suggesting a circadian etiology. On the other hand, neither eastward (P = 0.412) nor westward travel (P = 0.3215) impacted away-team slugging percentage. Although the effects did not reach statistical significance, a similar pattern was also evident for runs scored. It is noteworthy that these effects were detected even though there are both fewer eastward travel and home-team jet-lag games and thus, less statistical power.

We then examined additional more specific offensive metrics to identify the underlying basis of these changes to major offensive parameters. Where aspects of offensive performance were detectably impacted by jet lag, these were nearly universally evident by traveling eastward rather than westward travel (Table 2). Home-team eastward travel, but not westward travel, significantly reduced doubles, triples, and stolen bases, and increased double plays (P < 0.05 at a Benjamini–Hochberg false discovery rate <0.2). The only parameter impacted by westward travel was a very minor parameter, stolen base attempts, and this did not quite translate into a statistically significant effect on stolen bases.

Table 2. Effect of travel direction on the impact of jet lag on home offensive performance

In terms of impact on slugging percentage (total bases/at-bats), the effect on doubles largely explains most of the effect. A reduction of 0.146 doubles per game translates into a reduction of 0.292 total bases per game. As the home team averages about 33 at-bats/game, this results in a reduction of 0.008 in slugging percentage, which is most of the observed reduction of 0.010. Thus, doubles can explain much of the aggregate effects of jet lag.

Consistent with the specificity of jet-lag effects on the home-team offense, we did not observe effects of east or west travel on away-team offensive performance on these metrics (Table 3). In fact, the only effects we observed on away-team offensive performance were on relatively minor parameters of sacrifice hits and sacrifice flies, although the latter passed our P-value threshold it did not pass our false discovery rate (FDR) threshold. In the case of sacrifice hits, it was dependent on westward travel and in the case of sacrifice flies, eastward travel. Nonetheless, these away- and home-team westward travel effects in single and relatively minor parameters are dwarfed by the multiple parameters impacted after home-team eastward travel. Thus, jet lag selectively impacts the home-team offensive performance, especially on metrics related to aggressive base running.

Table 3. Effect of travel direction on the impact of jet lag on away offensive performance

We then examined the effect of jet lag on major defensive performance metrics (Table 4). Eastward, but not westward, travel also strongly affected defensive performance metrics of slugging percentage allowed (for both home and away teams, P < 0.05), fielding-independent pitching (FIP; both home and away) and runs allowed for the away team. FIP attempts to isolate the effects on pitching weighting factors by their impact on earned runs allowed (Methods). Runs allowed for the home team were also nearly significant (+0.197, P = 0.056). For both home and away teams, these effects were comparable to or exceeded the home-field advantage effect for runs scored/allowed (home vs. away +0.135). Notably, batting average on balls in play (BABIP), an indicator of fielding, was not affected by jet lag, suggesting effects may be pitching-specific. Thus, a jet-lagged team upon return home displays both impaired offensive and defensive performance, whereas a jet-lagged team on the road exhibits impaired defensive performance with relatively minor effects on offensive performance.

Table 4. Effect of travel direction on the impact of jet lag on home and away aggregate defensive performance

To determine what was responsible for the poor defensive performance, we examined specific metrics and found highly significant effects of eastward, but not westward, travel on home runs allowed for both home and away teams (Tables 5 and 6). The finding of the same metric affected in both home and away teams demonstrates independent replicability. In addition, no other specific metrics were detectably affected. To address how important this specific effect is to explaining the aggregate effects, we determined the effects of the change in home runs due to jet lag on slugging percentage and runs allowed. As a home run results in four total bases, an increase of 0.107 and 0.073 home runs per game (for home and away eastward jet lag, respectively) would result in an increase of 0.428 and 0.292 total bases per game or an increase of 0.012 and 0.009 in slugging percentage that approximates the 0.010 and 0.009 that we observed. Thus, essentially all of the effect on slugging percentage can be explained by the change in home runs. Given the average number of runners on base when a home run is hit, a home run results in about 1.594 runs on average for the period 1992–2011. Therefore, an increase of 0.107 and 0.073 home runs per game would result in an increase of 0.171 and 0.116 runs per game that are the majority (87% and 72%, respectively) of the 0.197 and 0.162 runs per game effects that we observed. Not only are the effects of jet lag on pitching comparable to the effect of home-field advantage, those effects are largely explained by a single measure: home runs allowed.

Table 5. Effect of travel direction on the impact of jet lag on home defensive performance

Table 6. Effect of travel direction on the impact of jet lag on away aggregate defensive performance

Although eastward travel was generally more detrimental to the defense, one prominent metric that was disrupted by westward, but not eastward, travel was walks allowed by the away team (+0.128 for westward travel, P < 0.05 vs. +0.017 for eastward travel, P = 0.393; Table 6). This effect only affected the away team but not the home team (−0.074, P = 0.858; Table 5). A westward-specific effect on on-base percentage allowed by the visitor, to which walks contribute, was also observed (+0.002, P = 0.021) The only defensive metric affected by westward home-team travel was triples allowed (+0.033, P < 0.01). Unlike effects observed after eastward travel of the home or away team, neither of these westward travel effects was sufficiently large to impact FIP or runs allowed. Thus, there appear to be unique effects of westward travel relative to eastward travel on performance separate from the larger effects of eastward travel.