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赛季澳大利亚足球超级联赛（A-League）的每场赛事环境数据。研究人员回溯整理了每场赛事的气温与湿球黑球温度（Wet Bulb Globe Temperature，WBGT）两项环境指标。其中，气温即大众熟知且易于获取的环境空气温度；湿球黑球温度为一类体感温度指标，综合了相对湿度、风速与太阳辐射的影响，可更细致地反映观测到的热应激水平。
过往研究已对湿球黑球温度的应用场景、优缺点进行了充分阐述1-3。尽管该指标应用广泛，但黑球温度（辐射热获取量）与自然湿球温度（蒸发散热能力）的测量方式仍受诟病，认为其无法准确反映人体体温调节状态，进而在诸多场景中低估了热应激水平1,4。同时需说明，湿球黑球温度属于热应激指数，并未针对低温环境完成有效性验证。因此，为分析低温环境对伤病发生的影响，本研究同时纳入气温指标开展分析。
尽管目前已有更先进、更复杂的热应激指标4,5，但湿球黑球温度仍被广泛使用，尤其在各体育联合会的高温赛事政策中。具体而言，国际足球联合会（FIFA）出台的高温赛事政策也采用了该指标，其建议在湿球黑球温度达到32℃时设置饮水暂停时段6。
针对德国足球甲级联赛赛事，气象数据来源于Meteostat.net7。该开源服务可针对任意给定坐标提供逐小时气象数据，其数据通过对距目标地理点位最近的四座气象站的观测值进行距离与海拔差加权插值得到。该平台可提供以下数据：气温、相对湿度、露点温度、风速、气压、总降水量与当前天气状况。基于上述数据，可通过多种方法估算湿球黑球温度2，本研究采用Liljegren等人于2008年提出的估算方法3，该方法已在不同环境场景下完成有效性验证，且被证实为现有各类估算方法中准确度最优的方案8。实现此类计算所需的R代码已公开并被过往研究采用9。
研究假设风速最小值为1m/s，因为参赛球员移动产生的气流速度至少可达该水平。太阳辐射则通过赛事举办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，本研究选取每场赛事的开球时刻与开球后1小时两个时间点的数据进行平均。若赛事并非整点开赛，而是在半点或15分、30分时刻开赛，则以上一个整点作为首个时间点，下一个整点作为第二个时间点。
针对澳大利亚足球超级联赛赛事，环境数据由UBIMET.com11提供。该商业气象服务平台借助人工智能与多源气象站、雷达及卫星数据，可针对指定地面点位估算气象数据。其提供了上下半场开球时刻的气温、相对湿度、太阳辐射与湿球黑球温度实测值，本研究对这两个时间点的数据取平均，得到每场赛事的单一项环境指标值。
为验证基于Meteostat.net数据估算的湿球黑球温度结果，本研究采用德国足球甲级联赛所用的湿球黑球温度估算方法，对澳大利亚足球超级联赛的气象数据重新进行估算。作为内部验证，将估算结果与UBIMET.com提供的湿球黑球温度实测值进行对比，二者呈现极强的线性相关性（相关系数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/