Excellence in Historical Research and Analysis
Excellence in Historical Research and Analysis
I will be doing a Podcast on 2 PM (EST), 7 PM (UK time), on The Battle for Kyiv: The Battle for Kyiv by Christopher A Lawrence Tickets, Tue 7 May 2024 at 19:00 | Eventbrite
It is free to attend.
I will be speaking for about 40 minutes and then there will be 20 minutes of questions. I suspect I will talk extemporaneous about the process and need to write to write a book while the conflict is going on and what are some of the sources available.
This is a continuation of our previous three posts: Analysis for Force Ratios using the Campaign Data Base (CaDB) | Mystics & Statistics (dupuyinstitute.org) and Analysis for Force Ratios using the Campaign Data Base (CaDB) – continued | Mystics & Statistics (dupuyinstitute.org) and Analysis of Force Ratios using the Campaign Data Base (CaDB) – second continuation | Mystics & Statistics (dupuyinstitute.org). It is a part of a briefing on forces ratios I will be giving at HADSS in UK: Schedule for HADSS 2024 | Mystics & Statistics (dupuyinstitute.org) and at HAAC near DC: Next Revised Schedule for the Third Historical Analysis Annual Conference (HAAC), 8 – 10 October 2024 | Mystics & Statistics (dupuyinstitute.org)
This is a continuation of Section IV of the briefing titled “What is necessary to have a good chance of generating a breakthrough?”
Having put together a table in the last post of force ratios and exchange ratios by outcome, I decided to take a moment to look at each of these cases. Each of these 94 cases is a fully mapped out campaign, many that you have heard of.
First looking at the 29 cases that were coded outcome IV (attacker advances). The average force ratios were 2.69-to-1 and the average exchange ratios were 1.51-to-1:
What I was really looking for is to see if there is any pattern in these low odds cases. Do they represent particularly odd or unusual cases? They really don’t. It does help to look at the cases though.
I then looked at those 21 cases that were coded as outcome five (defender penetrated). The average force ratios were 2.75-to-1 and the average exchange ratios were 0.64-to-1. There did not seem to be any unusual pattern, although there are a number of Arab-Israeli cases in these low odd penetrations. That is because human factors matter (morale, training, experience, leadership, motivation, etc.). In fact, they matter a lot (and are not considered in most U.S. DOD combat models).
By the way, if someone is looking for some 3-to-1 rule in this data, good luck. Warfare is more complex than that.
One more post to come on this series of force ratios for army-level operations. Debating what I should discuss next.
The cold hard reality is that in the long run $$$ = combat power. This is a obvious little relationship that is often ignored. This was demonstrated in spades when Japan attacked a country in 1941 that had an economy more than ten times their size. Good luck with that one. It was also ignored by the leader of Germany, who somehow or the other believed that superior willpower go overcome the overwhelming coalition arrayed against them. He could not. In the long run, warfare is decided by the golden rule: he who has the gold – rules. So, let us take a moment and look at the defense budget of Russia vs Ukraine.
Russia defense budget in 2023, according to Wikipedia, was $86.4B. Source was the Stockholm International Peace Research Institute (SIPRI), from back in the days when Sweden was neutral. Now maybe this should be adjusted by PPP (Purchasing Power Parity) to account for lower labor costs, lower food costs, etc. The PPP multiplier for the GDP is 2.66. Meaning that their real value of the budget is somewhere between 86.4 to 229.8. Hard to say how much of military expenditures should be under PPP, especially when one is talking about all the high-tech equipment that makes up a modern army. The 2024 budget is higher, that is discussed below. Their 2023 budget only make of 4.1% of the GDP, so there is room to grow. Russia is receiving no significant outside aid to support this war (they have to pay for the material from Iran, China and North Korea).
Ukraine on the other hand is receiving lots of outside aid. At least $110B a year. This includes over $50 billion from the EU & UK, and at least $61B from the U.S. Much of this is spent in their home countries for equipment, so is not directly comparable to the PPP adjusted Russian figures. On the other hand, in 2024 Ukraine is spending $66.2 billion of its own money on the war (source: Ministry of Finance of Ukraine). This is 18% of their GDP. Sort of gives you some idea of what Russia might be capable of if the political will was there (so I guess willpower does matter). One of course, has to ask, why is the political will not there? What is the dynamics where Ukraine has spent 18% of their national income on the war while Russia, which initiated this war, is only spending 4%. What is the Kremlin afraid of? Their own people?
Anyhow, $66B that Ukraine is spending also needs to be adjusted by PPP. Their multiplier is 2.73. So that $66B turns into $180.2. So 180 vs 230. 1-to-1.28 ratio of expenditures. But to that Ukraine adds a least $111B in Western money. So, 181 + 111 vs 230 or a 1.27-to-1. This is of course assuming that PPP is a fully valid measurement and none of the western aid is influenced by PPP. Neither of these are quite the case. If it was a simple nominal expense comparison it would be 66 + 111 vs 86 or a ratio of 2.06-to-1.
From a practical point of view, it appears that Ukraine with western aid is outspending Russian by at least 50%. Of course, I am comparing here Ukrainian 2024 figures to Russian 2023 figures. In the long run, that means that Ukraine will win. More than likely, it will force Russia to increase it defenses expenditures by at least 50%, up to 6% or more of GDP. This is sustainable.
Now, the linked article below shows that Russia’s 2024 defense expenditure is 40% (or 39% in another article) of their national budget, which 391.2 x .4 = 156.48. They say it is a 70% increase from 2023 (86.4 x 1.7 = 146.88). Anyhow, they are having to increase their budget significantly. See: Putin approves big military spending hikes for Russia’s budget | Reuters
So, 146.88 x 2.66 (PPP multiplier) = 391. So 181 + 111 vs 391 is a 1-to1.34 ratio based upon PPP for both Russia and Ukraine. Or… 66 + 111 vs 147 is a 1.20-to-1 ratio in favor of Ukraine based upon nominal costs. So it does appear that for 2024 the two sides expenditures appear to be roughly equal. This would imply that a rough stalemate is going to be the outcome in 2024.
Now, this is a rough back-of-the-envelope calculation banged out this morning. Something more rigorous could be developed by someone. I am not sure it would tell a different story.
This is a continuation of our previous two posts: Analysis for Force Ratios using the Campaign Data Base (CaDB) | Mystics & Statistics (dupuyinstitute.org) and Analysis for Force Ratios using the Campaign Data Base (CaDB) – continued | Mystics & Statistics (dupuyinstitute.org). It is a part of a briefing on forces ratios I will be giving at HADSS in UK: Schedule for HADSS 2024 | Mystics & Statistics (dupuyinstitute.org) and at HAAC near DC: Next Revised Schedule for the Third Historical Analysis Annual Conference (HAAC), 8 – 10 October 2024 | Mystics & Statistics (dupuyinstitute.org)
Section IV of the briefing is titled “What is necessary to have a good chance of generating a breakthrough?”
We coded some (94), but not all, of the 196 Army-level operations as to outcome. The outcomes are defined as (see War by Numbers for a more detailed description):
These definitions are used to create the following table:
Now, I put seven of those numbers in bold. They are worth looking at.
For those 10 operations that were coded as “failed attack”, the average force ratio is 1.80-to-1 while the average loss exchange ratio is 1.66-to-1 (i,e. the attacker lost more than the defender).
For those 29 operations that were coded as “attack advances”, the average force ratio is 2.69-to-1 while the average loss exchange ratio is 1.51-to-1.
For those 21 operations that were coded as “defender penetrated”, the average force ratio is 2.75-to-1 while the average loss exchange ratio is 0.64-to-1 (meaning the defender lost almost twice as many people as the attacker. Note that casualties included kill, wounded, missing and captured).
One notices that the loss exchange ratio gets even more favorable in mop-up operations (defender enveloped). These are often the operation after “defender penetrated.”
A few other observations:
This last point is significant. Are operations with bodies of 60 thousand plus people the same as operations with 10-20 thousand people? At least in the patterns of force ratios required, loss exchange ratios, etc., they are very similar.
More to come (my briefings are long). The obvious next work step would be to finish coding the outcome of the other 102 operations in the CaDB. This is several man-weeks of effort. Not going to take that on now (I am trying to finish up another book).
This is the continuation of our previous post: Analysis for Force Ratios using the Campaign Data Base (CaDB) | Mystics & Statistics (dupuyinstitute.org)
In that post was a table showing the force and losses differences between battles won by the attacker, the defenders and those that are drawn. Below is a follow-up table, showing the force ratios for all the campaigns:
These are slides 19 and 20 of my briefing. Now, I do not make conclusions on this slide in this briefing or even observations, but…. there are a few that could be made looking at this table. First, a three-to-one rule doesn’t really apply. Second, the defender never wins above four-to-one. Third, clearly there are a lot of factors included in these campaigns beyond simple manpower counts, and…. fourth…. you tell me?
The next slide of my briefing goes into the Section III of the briefing: “Influence of Human Factors on Combat.” This is all drawn from War by Numbers… so… read the book. I will skip that and my next post will pick up at Section IV of the briefing “What is necessary to have a good chance of generating a breakthrough.” Probably do that post next Tuesday.
The Historical Analysis for Defence and Security Symposium (HADSS) is scheduled for 8-11 July at the University of York. The provisional schedule for the conference is here:
Description of the conference is here Historical Analysis for Defence and Security Symposium | ICMS – International Centre for Mathematical Sciences and here: Weighing the Fog of War (wordpress.com).
York seems like a really cool city. I will be at the conference (and presenting).
We have not made much use of our Campaign Data Base. (See: The History of the DuWar Data Bases | Mystics & Statistics (dupuyinstitute.org)). We used it as part of the Enemy Prisoner of War (EPW) studies back in 2000-2001 and have not made use it in the last two decades. But, for a presentation I did last year on force ratios, I blew the dust off of it because I wanted to see if force ratios were different for army-level operations than for division-level engagements. I mean, in the ETO data we have (116 cases), in the force ratios ranging between 1.15-to-1 to 1.88-to1 the attacker won 79% of the time (so much for needing 3-to-1). See: The 3-to-1 rule and the War in Ukraine | Mystics & Statistics (dupuyinstitute.org). So the question became, is the pattern we see at army-level different than division-level?
The Campaign Data Base consists of 196 campaigns from 1905 to 1991. They from two days in length to 155 days in length. Only three were over 60 days in length. The problem is that the database is not complete. We assembled it, used it once and have not used it again. There are some holes. For example, we only had the starting strength ratios calculated for 163 cases, we only had the total casualty ratios calculated for 162 and only had the winner calculated for 156 cases. In most cases the missing data is available but has not been assembled. The database just needs a little tender loving care.
The average attacker strength (99 cases) was 188,909. The average defender strength (96 cases) was 95,497. This comes out to a 1.98-to-1 ratio.
The average attacker losses (176 cases) was 36,076. The average defender losses (172 case) was 47,004. This comes out to a 1-to-1.30 ratio.
The average attacker percent losses per day (163 cases) was 0.69%. The average defender percent losses per day (162 cases) was 1.85%. This comes out to a 1-to-2.68 ratio.
The starting strength ratio (163 cases) was 2.24 (2.24-to-1). The total casualty ratio was (164 cases) 1.35-to-1.
Now, the holes in the database become an issue. This are holes that can be filled given time (read: budget). We have 97 cases where the attacker is coded as the winner, and 38 cases where the defender wins. We have draws in 21 other cases. The rest (40 cases) are currently not coded.
Anyhow, this all produces the following table:
Contemplate for a moment what this data is telling you. A few observations:
I will stop here for a moment. This is from slides 12 – 18 for my force ratios briefing. There is more to come (because my briefings, like some of my books, are never short).
This is the third provisional schedule for the third Historical Analysis Annual Conference (HAAC). We currently have 29 presentations scheduled by 20 speakers and two group discussions planned. We are looking for more presentations. Have slots still open for seven more presentations (although I can add more slots). Each slot is an hour long, so plan for a 45-minute presentation and 15 minutes of discussion.
The conference is at 1934 Old Gallows Road, Suite 350, Vienna, VA 22182. This is basically across the street by Tysons Corner Shopping mall and the Marriot Hotel on Route 7. It is right off the Route 7 exit from 495 (the Beltway). It is at the corner of Route 7 (Leesburg Pike) and Old Gallows Road. It is in the building above the restaurant called Rangos. Parking is in the parking garage next door to it.
Conference description is here: The Second Historical Analysis Annual Conference (HAAC), 17-19 October 2023 in Tysons Corner, VA | Mystics & Statistics (dupuyinstitute.org)
Costs, Hotels and Call for Presentations (these are all 2023 postings but nothing has changed): Cost of the Second Historical Analysis Annual Conference (HAAC), 17 -19 October 2023 | Mystics & Statistics (dupuyinstitute.org) and Hotels for the Second Historical Analysis Annual Conference (HAAC), 17-19 October 2023 | Mystics & Statistics (dupuyinstitute.org) and Call for Presentations for the Second Historical Analysis Annual Conference (HAAC), 17-19 October 2023 | Mystics & Statistics (dupuyinstitute.org).
The cost of the conference is $150 for entire conference or $60 a day. This the same as the last two years. Please pay through PayPal (www.paypal.com) to SRichTDI@aol.com. The conference is priced to cover the costs of the conference facility. We are also set up to take credit card payments by phone. Call The Dupuy Institute during working hours at (703) 289-0007.
We are set up for virtual presentations and virtual attendees. We do record the presentations but most have not been published yet.
The presentations from all three days of the first HAAC are here: Presentations from the first HAAC – all three days | Mystics & Statistics (dupuyinstitute.org).
Friday, October 11: Tour of a Civil War Battlefield – Antietam: bloodiest day of the U.S. Civil War (and in the Western Hemisphere?). – we will arrange transport there and back ($20 charge for tour).
The House passed the aid bill for Ukraine. This was the hold up. It will now go to the Senate, which will approve and then to the President who will sign it. I assume it will be a done deal next week.
The final vote was 311-112 (7 not voting and five unfilled seats). So ,72% voted for it. Of those 210 were Democrats and 112 were Republicans. The House current sits 217 Republicans and 213 Democrats. So, this ends up being a bi-partisan foreign aid bill.
So, 99% of the House Democrats and 52% of the House Republicans voted for it. Note that the foreign aid bill advanced yesterday with 165 Democratic votes and 151 Republican votes. That is 70% of the House Republicans advancing the bill.
The total bill was for $95.3 Billion, or which $61 billion was for Ukraine. Around $16 B was aid to Israel and over $9 B was humanitarian assistance for Gaza. Another $8 B was for the Indo-Pacific region.
Related post: Size of aid bill versus Russian defense budget | Mystics & Statistics (dupuyinstitute.org)
There is a 3-to-1 rule that some people quote from somewhere. We have discussed this before: Trevor Dupuy and the 3-1 Rule | Mystics & Statistics (dupuyinstitute.org) and The 3-to-1 Rule in Histories | Mystics & Statistics (dupuyinstitute.org) and The 3-to-1 Rule in Recent History Books | Mystics & Statistics (dupuyinstitute.org).
Trevor Dupuy’s argument was always that it took a combat power advantage to advance (attack successfully). This combat power calculations considers weapons, terrain, posture, air support, human factors, etc. Because of the current artillery shell shortages for the Ukrainian Army, logistics may also be a factor.
This combat power advantage often happens at 1.5-to-1 or 2-to-1. Usually is happens by around 2-to-1 (my conclusions – see War by Numbers). For example, here is my chart of force ratios for division-level combat in the European Theater of Operation (ETO) in 1944 from page 10 of War by Numbers:
Notice that the attacker succeeds at force ratios between 1.15-to-1 to 1.88-to-1 in 79% of the 48 cases of division-level combat. It gets better from there. The book also has force ratios from other theaters and campaigns. Some of this has been discussed here before: More Combat Results Tables from War by Numbers | Mystics & Statistics (dupuyinstitute.org) and Force Ratios at Kharkov and Kursk, 1943 | Mystics & Statistics (dupuyinstitute.org) and Force Ratios in the Arab-Israeli Wars (1956-1973) | Mystics & Statistics (dupuyinstitute.org).
A rigidly defined 3-to-1 rule tends to create an officer corps of McLellan’s. This rule-of-thumb is doing more damage than good as constructed.
What got my attention is that some people are trying to apply some 3-to-1 rule in Ukraine, and then come to the conclusion that one or the other side cannot advance because they don’t have a 3-to-1 force ratio. Yet, people have been advancing. In fall of 2022 Ukraine re-took Kherson and surrounding areas (see: 2022 Kherson counteroffensive – Wikipedia) and achieved a breakthrough at Balakliya that took back a significant portion of Donetsk province (see: Battle of Balakliia – Wikipedia) and conducted a successful offensive around Kharkiv (see: 2022 Kharkiv counteroffensive – Wikipedia). In 2023 Russia did advance on Bakhmut and took it (see: Battle of Bakhmut – Wikipedia) and in 2023/2024 Russia did advance on Avdiivka and took it (see: Battle of Avdiivka (2023–2024) – Wikipedia). I think in three for those five cases the attacker did not have anything approaching a 3-to-1 advantage. Of course, I have no reliable manpower statistics for either side in any of these five battles, so this is sort of a guess, as is most of the analysis and expert opinions on this war.
I do not know how many troops Ukraine currently has. I am guessing at least 300,000 deployed. Some people throw out figures in the 600-700,000 range. I have no idea if that are total mobilized estimates or total deployed estimates. The same with Russia, where figures of 600-700,000 are also thrown out, but not sure that is what is actually deployed in Ukraine. I am guessing some number closer to 300,000. Don’t really know, and don’t know who does for certain (see the “Force Involved’ section of this post: The Russo-Ukrainian War – Day 699 | Mystics & Statistics (dupuyinstitute.org)).
Anyhow, I gather the two sides are somewhere near parity in force size. They can certainly concentrate forces to get a local advantage. With current modern intelligence gathering capabilities, concentrating forces is often seen while it is happening and opposing side can respond promptly. So not sure where anyone can get their 3-to-1 advantage.
I did do a test recently, comparing the force ratios in a database over 700 division-level combat engagements to the force-ratios in over 100 Army-level operations. The question was whether force ratios and the success from those force ratios was different at division-level vice army-level. My tentative conclusions were that force ratios for army level campaigns had the “Same patterns as for division-level combat.”
Now, I have not written this effort up. I did brief it last year at the Second HAAC and did brief it in Norway. I will be briefing it again on Thursday, July 11 at HADSS in York (see: Historical Analysis for Defence and Security Symposiums (HADSS), 8 – 11 July in York, England | Mystics & Statistics (dupuyinstitute.org)) and for one last time at the Third HAAC (see: Revised Schedule for the Third Historical Analysis Annual Conference (HAAC), 8-10 October 2024 | Mystics & Statistics (dupuyinstitute.org)). After that, I may write it up, either as a blog post or as a chapter in a book called More War By Numbers, which will probably be delayed until 2026 (see: Current book release schedule | Mystics & Statistics (dupuyinstitute.org), which I probably need to update).
Anyhow, the point is, anyone doing analysis for the situation in Ukraine based upon some 3-to-1 rule probably needs to reconsider their analysis.