Analyzing a shot's xG and angle
The user shared a detail in Chinese about Diaz's goal, mentioning that it had an expected goal (xG) of only 0.03 with a narrow shot angle of 1.8°. This is likely about a notable goal from Luis Díaz. They didn't ask a specific question, but it seems they may want an explanation or analysis. I can clarify what xG and shot angle metrics mean, discuss factors affecting xG, and provide some intuitive examples.Explaining shot angle and xG
I need to structure my final answer clearly, possibly using bullet points. I'll clarify concepts like xG and shot angles, discussing factors such as finishing skill, luck, goalkeeper positioning, and more. For visualizing the angle, I can mention computing it using geometric principles between the goalposts while acknowledging the width of 7.32m. An angle of 1.8° is very narrow compared to typical angles of 20-35° in the box. I can also touch on the implications of a 0.03 xG, which indicates only a 3% chance of scoring.Discussing goalkeeper coverage and xG
I should comment on goalkeeper coverage near the post. My answer will include a bullet list explaining what xG of 0.03 means, the significance of a 1.8° angle, why it's improbable to score from that position, and what factors lower xG. I can also touch on what might have contributed to the goal and how training could help replicate similar situations. It would be helpful to ask if the user wants more details or a visual. Lastly, I’ll avoid making claims beyond my knowledge cutoff and stick to general insights.Understanding angle and xG metrics
So, an angle of 1.8° across the 7.32m width indicates the shooter is very close to the goal line, making the goal mouth seem extremely narrow. I could compute the subtended angle by positioning the goal center at (0,0) and the posts at (-w/2,0) and (w/2,0), but that might involve too much math. A 0.03 xG is typical for tight-angle shots from outside the 6-yard box or wide near the goal. It’s important to note that xG doesn’t fully account for exceptional strikes, but some modern models consider shot speed and placement.
要点解释如下：
- 0.03 xG是什么意思：约3%进球概率（大约每33次类似位置/情境的射门进1次）。属于极低质量机会，模型认为大多数情况下不会进。
- 射门角度1.8°：从射门点看，两个门柱在视野中仅相隔1.8°，几乎“看不见门”。作个对比：点球的门柱夹角约为36.8°（7.32m宽、11m距离），比1.8°大约20倍。
- 为什么模型给低分：极小射门角度；可能有较差身体朝向/非优势脚/防守压力/来球高度或速度不理想等因素；门将通常能封住近角。
- 它为何还能进：高质量触球与落点（如刁钻的远角/上沿）、出脚速度与旋转、门将站位瞬间被牵制；这些是“射后”因素。预期进球是射门前估计，无法捕捉这脚“神仙操作”的所有质量；若看“射后xG/PSxG”，该球可能会高很多。
- 结论：属于低概率的高难度世界波/零角度破门，更多体现个人瞬间天赋与执行，难以复制，作为单次事件并不与xG矛盾。
如果你想直观算“射门角度”，可用这个小函数（假设球门中心在(0,0)，门宽7.32m，射门点为(x,y)，y为到球门线的前后距离，单位米）：
import math
GOAL_W = 7.32
def shot_angle_deg(x, y):
# 门柱坐标
p1 = (-GOAL_W/2, 0.0)
p2 = ( GOAL_W/2, 0.0)
# 向量
v1 = (p1[0]-x, p1[1]-y)
v2 = (p2[0]-x, p2[1]-y)
# 夹角
dot = v1[0]*v2[0] + v1[1]*v2[1]
n1 = math.hypot(*v1)
n2 = math.hypot(*v2)
cos_theta = max(-1.0, min(1.0, dot/(n1*n2)))
return math.degrees(math.acos(cos_theta))
# 示例：点球(0,11)角度约36.8°
print(shot_angle_deg(0.0, 11.0))
需要我帮你把具体射门落点、门将站位用图示/数据再拆一次吗？