Environmental temperatures in the Australian and German professional football leagues.

This is environmental data for each match of the German Bundesliga (seasons 2014-21) and Australian A-League (seasons 2016-20). Environmental conditions in the form of temperature and WBGT were collated retrospectively for each match. Whereas temperature refers to the commonly known and easily accessible ambient air temperature, WBGT is a feels-like temperature adding the influence of relative humidity, wind, and solar radiation, for a more detailed interpretation of the observed heat stress. The use, advantages, and disadvantages of WBGT have been described extensively in previous research.1-3 Despite its widespread use, the black globe temperature (radiative heat gain) and natural wet-bulb temperature (evaporative heat loss) measurements are criticized as not representing human thermoregulation, thereby underestimating heat stress in many settings.1,4 It should also be mentioned, that WBGT is a heat stress index and is not validated for colder conditions. Therefore, to interpret the effects of colder environments on injury occurrence temperature was also used in our analyses. Although more modern and sophisticated thermal indexes exist 4,5, WBGT remains widely used, especially in sports federation heat policies. Specifically, this index is also used in the heat policy introduced by FIFA, which recommends the use of drinking breaks at 32 °C WBGT6. For Bundesliga matches, weather data was obtained from Meteostat.net.7 This is an open-source service, providing hourly meteorological data for any given coordinates. Data is obtained as a weighted interpolation depending on the distance and elevation difference from the four closest weather stations to a geological location. They provide the following data: temperature, relative humidity, dew point, wind speed, air pressure, total precipitation, and the current weather condition. Based on this, WBGT can be estimated in a variety of ways according to previous research.2 We used the estimation developed by Liljegren et al. (2008).3 This is validated and reliable in different environmental settings and is described as the best estimate for WBGT from different methods.8 The R code needed to implement these calculations has been provided and used in previous research.9 Wind speed was assumed to be a minimum of 1 m/s, as moving players generate airflow of at least equivalent to that. Solar radiation was estimated using the solar angle at the time and location of the match10. As Meteostat.net provides hourly data, two time points (the kick-off time and one hour later) were used per match and averaged. If the match did not start at a full hour, but at 15 or 30 minutes past the hour, the previous full hour was used as a starting point and the following hour as a second time point. For A-League matches, environmental conditions were provided by UBIMET.com.11 This commercial provider uses artificial intelligence and data input from multiple weather stations, radar, and satellite data, to estimate meteorological data at given ground locations. They provide temperature, relative humidity, solar radiation, and WBGT measurements for the starting times of the first and second half, which were then averaged to create one value per match. To validate the WBGT data based on Meteostat.net data, the WBGT estimation method used for the Bundesliga data was also performed with the A-League data. As internal validation, results were then compared to the WBGT reported from UBIMET.com. There was a very good linear association (correlation coefficient r = 0.93). 1. Brocherie F, Millet G. Is the Wet-Bulb Globe Temperature (WBGT) Index Relevant for Exercise in the Heat? . Sports Med. 2015;45:1619-1621. 2. Lemke B, Kjellstrom T. Calculating Workplace WBGT from Meteorological Data: A Tool for Climate Change Assessment. Ind Health. 2012;50:267-278. 3. Liljegren J, Carhart RA, Lawday P, Tschopp S, Sharp R. Modelling the Wet Bulb Globe Temperature Using Standard Meteorological Measurements. J Occup Environ Hyg. 2008;5(10):645-655. 4. Blazejczyk K, Epstein Y, Jendritzky G, Staiger H, Tinz B. Comparison of UTCI to selected thermal indicies. Int J Biometeorol. 2012;56:515-535. doi:https://doi.org/10.1007/s00484-011-0453-2 5. Jendritzky G, de Dear R, Havenith G. UTCI - Why another thermal index? Int J Biometeorol. 2012;56:421-428. doi:https://doi.org/10.1007/s00484-011-0513-7 6. Brown H, Chalmers S, Topham T, et al. Efficacy of the FIFA cooling break heat policy during an intermittent treadmill football simulation in hot conditions in trained males. Br J Sports Med. 2024;doi:10.1136/bjsports-2024-108131 7. Meteostat.net. The Weather’s Record Keeper. https://meteostat.net/en/ 8. Patel T, Mullen SP, Santee WR. Comparison of Methods for Estimating Wet-Bulb Globe Temperature Index From Standard Meteorological Measurements. Military Medicine. 2013;178(8):926-933. 9. HeatStress. Casanueva, A; 2019. https://zenodo.org/records/3264930 10. Duffie J, Beckman W. Solar Engineering of Thermal Processes. 4th ed. John Wiley & Sons, Inc.; 2013. 11. UBIMET GmbH. UBIMET WEATHER MATTERS. https://www.ubimet.com/en/

本数据集涵盖2014-2021赛季德国足球甲级联赛（Bundesliga）以及2016-2020赛季澳大利亚足球甲级联赛（A-League）的每一场赛事环境数据。所有赛事的环境条件数据均以气温与湿球黑球温度（Wet Bulb Globe Temperature，WBGT）的形式呈现，为回溯整理所得。其中，气温指大众熟知且易于获取的环境空气温度；而WBGT作为体感温度指数，纳入了相对湿度、风速与太阳辐射的影响，可更细致地评估观测到的热应激水平。WBGT的应用场景、优势与不足已在既往研究中得到广泛阐述1-3。尽管该指数应用广泛，但黑球温度（辐射热获取）与自然湿球温度（蒸发散热）的测量方法遭到批评，认为其无法准确反映人体体温调节过程，因此在诸多场景下会低估热应激程度1,4。同时需说明，WBGT作为热应激指数，并未在寒冷环境中完成验证。因此，为分析寒冷环境对伤病发生的影响，本研究在分析中同时纳入了气温数据。尽管目前已有更先进、复杂的热指数4,5，但WBGT仍被广泛使用，尤其在各体育联合会的热应激管理政策中。具体而言，国际足球联合会（FIFA）推出的热应激政策也采用了该指数，其建议在WBGT达到32℃时安排补水暂停6。
德国足球甲级联赛的气象数据取自Meteostat.net7。该平台为开源服务，可针对任意给定坐标提供逐小时气象数据。其数据通过对距离目标地理位置最近的四个气象站的观测值进行加权插值计算得到，权重取决于各气象站与目标点的距离及海拔差。该平台提供以下数据：气温、相对湿度、露点温度、风速、气压、总降水量以及当前天气状况。基于这些数据，可通过既往研究中的多种方法估算WBGT2。本研究采用了Liljegren等人（2008）提出的估算方法3，该方法在不同环境场景下均经过验证且可靠性良好，被认为是现有各类WBGT估算方法中的最优方案8。实现该计算所需的R代码已在既往研究中公开并使用9。考虑到运动员移动时产生的气流速度至少可达1m/s，因此将风速的最小值设定为1m/s。太阳辐射则通过赛事举办的时间与地点对应的太阳高度角进行估算10。由于Meteostat.net提供逐小时数据，每场赛事选取两个时间点（开赛时刻及开赛1小时后）的数据并取平均值。若赛事并非整点开赛，而是在半点或15分或30分时刻开赛，则以上一个整点作为第一个时间点，下一个整点作为第二个时间点。
澳大利亚足球甲级联赛的环境数据由UBIMET.com11提供。该商业服务商通过人工智能结合多座气象站、雷达及卫星数据，针对指定地面位置估算气象数据。该平台提供上下半场开赛时刻的气温、相对湿度、太阳辐射及WBGT测量值，随后将这两个值取平均，得到单场赛事的环境数据值。为验证基于Meteostat.net数据得到的WBGT数据，本研究将德甲所用的WBGT估算方法同样应用于澳甲赛事数据。作为内部验证，将计算结果与UBIMET.com报告的WBGT值进行对比，二者呈现极佳的线性相关性（相关系数r=0.93）。
1. Brocherie F, Millet G. 湿球黑球温度（WBGT）指数是否适用于高温运动？. 运动医学（Sports Med）. 2015;45:1619-1621.
2. Lemke B, Kjellstrom T. 基于气象数据计算工作场所WBGT：一款用于气候变化评估的工具. 工业健康（Ind Health）. 2012;50:267-278.
3. Liljegren J, Carhart RA, Lawday P, Tschopp S, Sharp R. 基于标准气象测量值建模湿球黑球温度. 职业与环境卫生杂志（J Occup Environ Hyg）. 2008;5(10):645-655.
4. Blazejczyk K, Epstein Y, Jendritzky G, Staiger H, Tinz B. UTCI与选定热指数的对比. 国际生物气象学杂志（Int J Biometeorol）. 2012;56:515-535. doi:https://doi.org/10.1007/s00484-011-0453-2
5. Jendritzky G, de Dear R, Havenith G. UTCI——为何需要新的热指数？. 国际生物气象学杂志（Int J Biometeorol）. 2012;56:421-428. doi:https://doi.org/10.1007/s00484-011-0513-7
6. Brown H, Chalmers S, Topham T, et al. 高温环境下间歇式跑步机足球模拟训练中FIFA补水暂停热政策的有效性. 英国运动医学杂志（Br J Sports Med）. 2024;doi:10.1136/bjsports-2024-108131
7. Meteostat.net. 天气记录者. https://meteostat.net/en/
8. Patel T, Mullen SP, Santee WR. 基于标准气象测量值估算湿球黑球温度指数的方法对比. 军事医学（Military Medicine）. 2013;178(8):926-933.
9. HeatStress. Casanueva, A; 2019. https://zenodo.org/records/3264930
10. Duffie J, Beckman W. 热过程太阳能工程（第4版）. John Wiley & Sons, Inc.; 2013.
11. UBIMET GmbH. UBIMET WEATHER MATTERS. https://www.ubimet.com/en/