Statistics can "lie", or fool you, especially when sample size is not large enough for the robustness of the specific stats test you chose. The computer will spit out results, regardless if the data is appropriate.
In the above ANOVA's, there is something I don't like, which is the no significant difference between the Control and Hot. I think there is a difference.
So I did a Box & Whisker plot (image below), which in my opinion, is usually better than ANOVA's and other tests of variance for these types of data.
The reason Box & Whisker plots are better for observing sameness or difference for examples like this, is that they are simply the data stacked smallest to largest, and divided into quarters (quartiles) of 25% each. The middle Box is the 25% to 75% group (the 50% middle Inter Quartile Range, or IQR). Without knowing any fancy statistics methods, your eye can intuitively see the general comparison of how similar or different these are.
The median (the exact middle of the data count), is shown with the horizontal line through the box, and the mean is shown marked with an X. These two often overwrite each other, so I deleted the mean text in each box. The median is often the better indicator of the central bulk of the values when sample sizes are small. When you see the median not in the center of the box, that shows a skewing of more values to that side of the box.
The whiskers are the ES (extreme spread), unless one or more of the values is way, way outside the distribution, in which case its shown as an
outlier.
Outliers are more than 1.5 x the height of the box away from the upper or lower edge of the box.
The data values are shown for the Whisker extremes, the Outlier, the bottom and top of the Box (high and low values of the IRQ).
In this case, the Control group has one crazy outlier. That value is so large that in a small sample size it can mess up the more complicated stats tests. That may be one reason why in the ANOVA, that the Control and Hot were not significantly different. From the B&W plot, its clear to me that they are in fact quite different from each other and in the spread of their distribution. Therefore IMO, I think the ANOVA is a misleading statistical test for this sample size of data.
The Hot ammo has the narrowest distribution which, all else being equal, is likely to shoot less vertical in a match than the two other ammo temperatures. The Cold is not bad either. The Control looks like the poorest performance for MV distribution.
(Other comment: It looks like some of those rounds might be supersonic, in which case they would go through the transonic zone, which might affect how they print on a target at 50 m/yards).