Rifle Nodes: How You’ve Been Wasting Your Time and Money on Load Development

Shooters using large sample sizes have been saying that many of our detail-oriented efforts at the reloading bench are pointless, so I set out to find out for myself
Tyler Freel Avatar
savage m110 carbon predator in .223
Finding nodes or optimal charge weights has been standard practice for decades: what if we've been wasting our time?

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Finding a rifle’s nodes is just one of many commonly-practiced load development procedures that handloaders follow in the pursuit of creating the most consistent, accurate ammo possible. The meticulous reloader will select quality powder, bullets, brass, primers, and other components, then methodically test different variables — primarily different charge weights and seating depths — to find what works best in each individual gun. For the 24 years or so that I’ve loaded my own ammo, everything I’ve read, watched, and done has focused on finding just the right combination of charge weight and seating depth to identify the sweet spot where velocities settle into a repeatable groove and groups tighten down to nothing. I’ve burned countless pounds of gunpowder, and managed to make some good ammo by following these procedures. But what if all that, including finding a rifle’s nodes, is just nonsense — an illusion created by small sample sizes?

Getting Out of the Matrix

As I tell people what I’m going to share with you, I feel like I’m describing Neo in the movie The Matrix. I was existing happily in my religious-like beliefs about rifle accuracy and reloading when, on a wolf hunt in Alberta, I heard about a podcast episode that Hornady had published called Ep. 50 Your Groups are Too Small. In the episode, Hornady Senior Ballistician Jayden Quinlan and Project Engineer Miles Neville presented some ideas that challenge many of the commonly-used methods for load development and gauging a rifle’s accuracy — all based on thousands and thousands of rounds of test shooting they’d done. Eventually I listened to it, and it made sense. I listened to it again, and it started changing the way I thought about and defined rifle accuracy. More importantly, I recognized the importance of using significant sample sizes — and how I’d been misled by small sample sizes in my own testing and load development. 

I listened to the follow-up episode (episode 52), then another, and another — realizing that much of what I thought about load development and the methods I used were all based on small and, ultimately, invalid sample sizes. Sometimes I’d strike gold with a great-shooting load, but now I know that I could have just picked a random charge weight and probably seen the same results. I felt pretty small at the thought of how much gunpowder and time I’d wasted on load testing that was essentially pointless.

We shooters and hunters often tend to stick with what we know works, or what we believe works, regardless of any evidence to the contrary. To complicate this matter, experienced reloaders who follow these practices and use good components and equipment usually do produce great-shooting ammo. However, Neville posed the valid question: “If a hundred different people develop loads a hundred different ways, and they all end up with comparable results, is it really the method that matters?” 

Like Neo in the movie, once I learned that everything I thought I knew about load development might be a myth, I couldn’t turn back. Rather than remaining comfortable in my ignorance, I had to dive further into the rabbit hole to see if there might be a more efficient way to reload ammo, and a more effective way to quantify and measure rifle accuracy.

Rifle Nodes: What Is a Node?

Many commonly-used terms in the shooting community aren’t widely understood or used in a consistent context, so it’s important to define what we are talking about. The technical term “node” refers to the points on a wave at which the amplitude or displacement is the smallest. In terms of a vibrating object like a rifle barrel, it’s the point at which the vibrating barrel moves the least. A rifle barrel does have nodes as it vibrates during and after a shot is fired, but when someone refers to “finding their rifle’s nodes,” they’re referring to finding the charge weight and velocity that causes the bullet to exit at or near that node or dead spot in the barrel’s movement as it vibrates back and forth. That’s one dominant idea, but I’ve heard a variety of theoretical explanations of the relationship between a barrel’s vibrations, bullet exit timing, and charge weight.

Whether you want to call it a node, sweet spot, or optimal charge weight, shooters have developed many methods for homing in on the best-shooting combination for their rifles. One of the most common methods is to run a velocity ladder test. There are many different ways these are conducted, but they usually involve incrementally increasing charge weights — usually one to three rounds per charge weight — that start low, then end up near or at book maximum. These can be valuable for getting a rough idea of what velocity each charge weight should produce, or tell you when you’ve hit your pressure limit, but many reloaders use ladder tests to find “nodes” or flat spots — consecutive charges with relatively little change in velocity. In theory, the middle of this “node” should produce consistent, forgiving velocity, even if your charge weight varies by a couple tenths of a grain.

Another popular method for finding that sweet spot is called the OCW or “optimal charge weight” test. This primarily uses accuracy and point of impact to determine the best load. The OCW test prescribes loading three rounds per charge weight in a ladder test fashion, but shooting each charge weight at a separate aiming point. You’ll then calculate your mean point of impact for each charge weight and, like a velocity ladder test, look for the tightest correlation of results. Your three consecutive charge weights that produce the closest points of impact highlight your “node.” 

At face value, a lot of this stuff makes sense. It seems logical that a given rifle would prefer certain charge weights of certain powders, depending on the bullet. But maybe it only seems logical because that’s what we’ve always believed and confirmed with small samples. After all, there’s people that believe the earth is flat because we would be flung off a spinning, round earth. What if you pick a bullet for your rifle, and either it shoots well with a given powder, or not? It would change everything about how we approach load development — for the better.

Node testing rifles: Savage 110 carbon predator, ruger american gen 2, and Remington 710
Test rifles from top to bottom: Savage 110 Carbon Predator in .223, Ruger American Gen 2 in 6.5 CM, and the Remington 710 in .30/06.

Find the Nodes, Then Test Them

As compelling as the tremendous amount of data compiled by the guys at Hornady is, I needed to see it for myself. They found that when using the small sample sizes (that everyone uses for these tests), a shooter will see consistencies in accuracy and velocity that are really just random noise within the outer limits of the system. The problem? They’re not repeatable. When they increased their sample sizes, they saw all of these imaginary nodes disappear. 

When I brought up the subject with Shooting Editor John B. Snow, he said that all his data had supported the idea that chasing nodes doesn’t gain you anything. He and other high-level shooters at team events will even tailor their loads to target matching velocities to simplify drop and windage calculations between shooting partners — that’s what he did in his Nightforce ELR Match prep last year.

I wanted to test this as thoroughly as I could, so I decided to use three rifles in three different calibers (.223 Rem., 6.5 Creedmoor, and .30/06) with varying degrees of accuracy and components, and treat them as if I was trying to develop a load. I picked a powder and bullet, then ran both velocity ladder and OCW tests to find my nodes. Then, I loaded 30-shot samples at each “node,” a sample at the “antinode” or worst-looking spot, and a fourth 30-shot sample to fill any big gaps in the charge weight spectrum. Any statistics textbook will tell you that 30 samples is a minimum good number for sample size, and though I expected some variability with that, they would certainly be more accurate than 3-, 5-, or 10-shot groups.

Test Rifles

I selected three different rifles and calibers with different capabilities for this test. I wanted to see what a match-grade barrel would do, sure, but I also wanted to see if this matters for mid-priced rifles and budget-grade rifles. After all, I’ve heard many arguments that budget rifles can shoot just as well as more expensive guns, it just takes developing the load it likes. I selected components and powders that were caliber-appropriate that I had in stock, but not with any particular strategy.

RifleSuppressorCaliberBulletPowderPrimerCase
Savage M110 Carbon PredatorBanish Speed K.223 RemingtonHornady 68-grain BTHP MatchHodgdon BenchmarkRemington SR BenchrestIMI
Ruger American Gen 2Banish Backcountry6.5 CreedmoorHornady 143-grain ELD-XHodgdon H4350Winchester Large RifleHornady
Remington 710N/A.30/06 SpringfieldHornady 150-grain InterbondIMR 4350CCI Large RifleFederal

Finding the Nodes

The first test I conducted was a basic 10-shot velocity ladder, using one shot per charge weight. I used Hodgdon’s Reloading Data Center to find safe load ranges with my components, and incrementally increased charge weights by 0.3 grains with the 6.5 Creedmoor and .30/06, and 0.2 grains with the .223. I noted spots with the smallest incremental changes in velocity and compared them to the additional three velocities from the OCW test (which I conducted next) to find my suspected nodes. These velocity “flat spots” seemed consistent between the 1-shot and 3-shot tests. I called this charge weight my “velocity node.”

After the velocity ladder test, I cleaned the barrels, re-fouled with 5 shots apiece, and conducted an OCW test, giving the barrels plenty of time to cool between groups. As mentioned above, I recorded velocities in my OCW test, but for this node, I correlated my points of impact to find my OCW node or “accuracy node.” Below is a table detailing the nodes I found, the “antinode” or least consistent charge weight, and the fourth charge weight that I tested. Velocities are the ones recorded during this testing session.

RifleCharge Weight RangeVelocity NodeOCW NodeAntinode
Savage .223 Rem.21.7 to 23.5 grains23.1 grains / 2,736 fps22.3 grains / 2,598 fps22.3 grains / 2,535 fps
Ruger 6.5 CM39.1 to 41.8 grains41.5 grains / 2,611 fps40.6 grains/ 2,529 fps39.7 grains / 2,468 fps
Remington .30/0654.8 to 57.5 grains56.9 grains / 2,751 fps56.6 grains / 2730 fps55.1 grains / 2,652 fps

Next, I would increase the sample size to see how these nodes would hold up to more scrutiny. I did note that the velocity and OCW nodes I found for the .30/06 were only 0.3 grains apart, but both of the other rifles showed significantly different nodes in each test. I found the OCW node and velocity “antinode” to perfectly line up at 22.3 grains of powder in the .223.

Testing the Nodes

To test both nodes and the other two charge weights, I loaded 30 rounds of each, plus 5 fouling shots. I fired these test batches over the course of two different days, and a temperature difference of around 15 to 20 degrees between days. I tested the velocity node and antinode the first day at about 5 degrees, then the OCW node and fourth charge weight on the second day at about 20 degrees. I fired each 30-shot aggregate in the same format: 5 3-shot groups, then 3 5-shot groups, letting barrels cool between groups. I did this to see and show the variability in group sizes with small samples, and I used group analysis software to correlate points of aim to show extreme spread of the group and calculate mean radius (the average distance by which shots missed the center of the group). I recorded each shot’s velocity in the test, and came away with 30-shot samples for reasonably accurate velocity average and standard deviation figures.

If these nodes are real, or any optimal charge weight exists, one of these test samples should show significantly better — or even just different results than the others. The Hornady crew claimed to have found no significant change in group size with varying charge weights — except that group sizes seemed to decrease slightly as charge weight decreased. What would my data say? After over 600 rounds fired, recorded, and tabulated, here’s what I found:

.223 Rem. OCW test
For my OCW tests, I fired three shots of each charge weight at an aiming point, then calculated mean POI for each group.

Savage M110 Carbon Predator: .223

This was the most accurate rifle in the test, one that I’ve used to evaluate .223 and 5.56mm ammo, and it will reliably print 20- and 30-shot groups at an inch or less at 100 yards with several types of ammo. 

Determining the Nodes

  • Velocity Node: I determined that 23.1 grains was the most promising velocity node. It was the middle ground of the three consecutive charge weights with the smallest change in velocity (35.2 fps total change over .4 grains of powder between 22.9 and 23.3 grains)
  • OCW Node: Based on accuracy, I pegged the OCW node at 22.3 grains because charge weights of 22.1, 22.3, and 22.5 grains had the closest consecutive mean points of impact (a .22-inch spread)
  • Velocity Antinode: Interestingly, the antinode appeared at 22.3 grains, same as the OCW node. It had the greatest change in velocity across three consecutive charge weights (189.1 fps total change over .4 grains of powder between 22.1 and 22.5 grains)
  • Additional Data Points: Because my OCW node and Velocity antinode were the same, I elected to test both minimum and maximum charge weights (21.9 and 23.5 grains) to fill in the blanks.

Large Sample Results

This rifle produced good extreme spread and mean radius numbers in this test too, but I was surprised by the relatively poor velocity SD numbers. From book min to book max for charge weight, you can see that average velocity increased with charge weight in a linear fashion as one would expect, but velocity SD, group size or extreme spread, and mean radius show almost no change from big changes in charge weight. The lowest charge weight produced the tightest accuracy, and it slowly increased along with charge weight, with the book maximum producing the largest group size and mean radius.

Read Next: What Is Mean Radius, and Why Should We Care?

I did notice that at my “velocity node,” the velocity SD was noticeably more consistent than the other samples — something that might make me think that it truly is a repeatable node. To double check, I loaded another 30-shot sample at that charge weight, repeated the test, and the SD fell right in line with the other samples. The SD from the repeat of that sample was actually worse then the calculated “antinode” which should be a less forgiving charge weight according to node theory. In other words, none of my nodes held up. Temperature was about 20 degrees warmer when the repeat sample was fired, accounting for a slight bump in velocity

Charge WeightVelocity NodeVelocity AntinodeOCW NodeAverage Velocity (30 shots)Standard Deviation (Velocity)Extreme Spread (Group Size)Mean Radius
21.9258235.60.9040.262
22.3XX264230.21.1040.319
23.1X2778.1123.91.0890.275
23.52848.132.11.3710.333
23.1 (2nd sample)X2802.736.61.160.244

Ruger American Gen 2: 6.5 Creedmoor

Basically brand new, this rifle showed itself to be a good shooter, and provided some great data. I selected H4350, an ideal 6.5 Creedmoor powder, so I wasn’t surprised when the common go-to charge weight of 41.5 grains showed promise as a velocity node. 

Determining the Nodes

  • Velocity Node: I determined that 41.5 grains was the most promising velocity node. It was the middle ground of the three consecutive charge weights with the smallest change in velocity (24.8 fps total change over .7 grains of powder between 41.2 and 41.8 grains)
  • OCW Node: Based on accuracy, I found the OCW node at 40.6 grains because charge weights of 40.3, 40.6, and 40.9 grains had the closest consecutive mean points of impact (a .21-inch spread)
  • Velocity Antinode: The antinode appeared at 39.7 grains. It had the greatest change in velocity across three consecutive charge weights (94.5 fps total change over .7 grains of powder between 39.4 and 40 grains)
  • Additional Data Points: I selected my fourth charge weight at 39.1 grains to get a representative sample from the lower fourth of the safe load range — this one being a minimum load.

Large Sample Results

Not far off the 41.5-grain velocity node, 40.6 was a promising OCW node. Like the .223 though, the test samples in this 6.5 Creed showed almost identical results for accuracy and velocity SD from book min to max. Again, the minimum charge weight produced the tightest dispersion and, this time, the best velocity consistency. None of the loads were outside the expected error range of the sample size. 

Charge WeightVelocity NodeVelocity AntinodeOCW NodeAverage VelocityStandard Deviation (Velocity)Extreme Spread (Group size)Mean Radius
39.1248511.41.1080.285
39.7X249818.41.6950.369
40.6X257214.91.4570.332
41.5X262519.71.1140.355

Remington 710: .30/06

I chose this rifle — my first hunting rifle — to represent the budget category for this test. I killed my first moose, bears, caribou, and Dall sheep with this gun, and it’s the rifle I learned how to handload with. Part of my purpose for testing this rifle was to see if a generally less-precise rifle would show the same correlations. It’s certainly a noisier system, with greater variability. If there’s a rifle that a carefully-selected charge weight would benefit, it’s this one, right? 

Determining the Nodes

  • Velocity Node: I determined that 56.9 grains was the most promising velocity node. It was the middle ground of the three consecutive charge weights with the smallest change in velocity (8.2 fps total change over .7 grains of powder between 56.6 and 57.2 grains)
  • OCW Node: Based on accuracy, I found the OCW node at 55.6 grains because charge weights of 55.3, 55.6, and 55.9 grains had the closest consecutive mean points of impact (a .59-inch spread)
  • Velocity Antinode: The antinode appeared at 55.1 grains. It showed the greatest change in velocity across three consecutive charge weights (66 fps total change over .7 grains of powder between 54.8 and 55.4 grains)
  • Additional Data Points: I selected my fourth charge weight at 55.9 grains to fill in a gap between minimum-level loads and the nodes on the upper end of the spectrum.

Large Sample Results

Amazingly, or not amazingly, the Remington produced incredibly consistent results. They were consistently bad, but consistent. Across all four samples, the velocity SD and group size barely changed, and the mean radius of all samples was nearly identical. 

I did note that my “velocity node” showed a slightly lower average velocity than the OCW node. It wasn’t entirely odd — 0.3 grains is a very small change in charge weight, and it was 15 degrees or so warmer when I shot the 56.6-grain sample. Down to only 15 bullets, I loaded another 15-shot sample of the 56.9-grain “velocity node” load and re-shot (on that day, it was approximately 20 to 25 degrees warmer than the original firing). 

Again, accounting for the ambient temperature difference, velocity, group size, and mean radius fell right in line with previous samples. Because of the smaller sample size, velocity SD was on par to end up in the 17- to 25 feet-per-second range as well. Could it be a true node? Maybe, but considering that again, the most accurate sample was the lowest charge weight tested and the “antinode,” I highly doubt it.

Charge WeightVelocity NodeVelocity AntinodeOCW NodeAverage VelocityStandard Deviation (Velocity)Extreme Spread (Group size)Mean Radius
55.1X266922.83.750.904
55.9271125.83.2150.986
56.6X275820.23.6361.07
56.9X275417.84.2441.126
56.9 (2nd sample — 15 shots)X277113.93.3121.113

Shoot More to Shoot Less

Moving to larger sample sizes has truly changed the way I think about load development and rifle accuracy. It’s like I’m seeing the real world for the first time — an incredibly liberating feeling. My test wasn’t nearly as extensive as the ones that Neville and Quinlan have done, and if I had the time and resources to shoot 50- or 100-shot groups at every tenth of a grain, I would. Does this testing unequivocally prove that ladder tests don’t work, or that crafting your handloads to match your nodes isn’t a real thing? No, but there are still people wearing masks in their cars, alone, because someone told them it would keep them safe. Santa isn’t real either, guys. 

It might seem that simply loading a 20-round batch of a first load sample is crazy and inefficient, but the results are the results. You’re going to get a representative group size and velocity SD for the entire range of charge weights. If it’s bad, change your powder or bullet. If it’s good, load another sample to verify or target a different velocity. They’re all going to shoot about the same — except that lower charge weights trend towards producing slightly tighter groups. You’ll either have your load development done or scrap that powder within 20 or 30 shots, where it might take you 50, 60, or 100 shots of chasing your tail with small-sample charge weight tests. 

6.5 creedmoor groups
Here you can see the variability of small-sample 3- and 5-shot groups. All shots are within a consistent range of dispersion — the wide ones aren’t errors or flyers.

Final Thoughts on Rifle Nodes and Load Development

In the process of accepting the validity of large sample sizes, I’ve had to eat some humble pie. Rifles I’d sworn to be dead-nuts shooters are actually just OK, and being honest with myself means knowing that I spent a lot of time and money spinning my wheels, chasing the mirage of an optimal charge weight. The rifles are all still the same guns, but now I have a more realistic and effective way to quantify their accuracy and a no-nonsense, more efficient way to load ammo for them.

The theory of vibration nodes timed with bullet exit seems logical when an accomplished shooter and reloader is confidently lecturing you on the subject. But if this were true, your perfect node load would go out the window with any major change in temperature that altered your velocity. Ultimately, it just doesn’t hold up to large sample testing, not even a little bit. 

I did not experiment with changes in seating depth in this test. One of the things that Neville and Quinlan observed in their testing was that changes in seating depth, like charge weight, didn’t result in any meaningful changes in accuracy. I used to experiment with seating depth and load bullets as long as they’d fit in the magazine, but a couple years back, I started loading everything to the cartridge overall length that the reloading data suggested. I have noticed no difference in accuracy. An easy proof of this would be to shoot a 30 shot sample at your “ideal” seating depth and another at a different seating depth (at least a .030-inch change). They will look different with 3-, 5-, or 10-shot samples, but will that hold up with 30?

This should be great news for everyone from hunters to match shooters, but I expect many seasoned reloaders to be skeptical. Even if you’re not convinced yet, take your favorite rifle, your favorite, painstakingly-developed load, and shoot a 30-shot sample. Compare it to a 30-shot sample of a random or book-minimum charge weight. Be honest with yourself, and let the data do the rest. Worst case, you’re down 60 rounds and got some extra practice at the bench. Unlike The Matrix, the best case is peeling back the curtain to a world where you’re not needlessly and unwittingly slaving away to procedures that don’t matter. That’s a pill everyone should swallow.