Mystics & Statistics

French Estimate of Russian Killed in Ukraine

Seems like everyone in and out of NATO has their own estimate of Russian losses. The current French estimate, according to their foreign minister, is 150,000 Russian soldiers killed and a total of 500,000 casualties. See: France’s Shocking Estimation: 150,000 Russian Soldiers Dead in Ukraine War (msn.com)

First reality check: Wounded-to-killed ratios. 500,000 – 150,000 = 350,000 wounded. Wounded-to-killed ratio of 2.33-to-1. The Soviet Army mostly on the attack in the southern salient of the Battle of Kursk from 12-18 July 1943 had a wounded-to-killed ratio of 2.68-to-1 (see Kursk: The Battle of Prokhorovka, page 1374, this is also in Chapter 15 of War by Numbers).

Are they saying the Russian medical care is worse now than in 1943, before they had penicillin, or in many cases no painkillers other than Vodka? They also had in 1943 a shortage of trained doctors, the rear hospitals were not brought forward that spring to be near the front, and they had a poor medical evacuation system.

Anyhow, another estimate to ignore. What data are these estimates actually based upon?

It looks like 1420 may have quit broadcasting

One of my favorite channels on YouTube to watch has been a site called “1420.” I did mention it yesterday during the question and answer period of my podcast on The Battle for Kyiv

It is a series of street interviews done in Moscow, St. Petersburg and at other locales across Russia asking people some irreverent questions and sometimes very pointed political questions. It is useful to get a feel of the opinions and range of opinions among the Russians. Hard to do so otherwise with limited independent polling and rather stacked elections.

They appear to have quit adding new interviews. Don’t know why. Their newest street interview is now one month old and they are now listed under “Archives of 1420”. See: Archives of 1420 by Daniil Orain – YouTube

My past references to this site on my blog are here:

  1. 1420 | Mystics & Statistics (dupuyinstitute.org)
  2. 1420 – second posting | Mystics & Statistics (dupuyinstitute.org)
  3. 1420 – third posting | Mystics & Statistics (dupuyinstitute.org)
  4. 1420 – fourth posting | Mystics & Statistics (dupuyinstitute.org)
  5. 1420 – fifth posting | Mystics & Statistics (dupuyinstitute.org)
  6. CBC on 1420 | Mystics & Statistics (dupuyinstitute.org)
  7. 1420 – sixth posting | Mystics & Statistics (dupuyinstitute.org)
  8. Presidential Elections – 2024 | Mystics & Statistics (dupuyinstitute.org)

Analysis of Force Ratios using the Campaign Data Base (CaDB) – fourth and final continuation

This is the fourth and final continuation of our previous four 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) and Analysis of Force Ratios using the Campaign Data Base (CaDB) – third 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)

All of this analysis of the CaDB was for a reason, it was to determine if odds (force ratios) play out difference at higher level of operations (meaning army level). Are they different at the operational level vice the tactical level of warfare. The answer appears to be no. I do not know of anyone who has actually specifically explored this issue before, so I am not sure there is an existing or countervailing opinions out there.

Of course, my real interesting in looking at this (which I did last year) was because of the war in Ukraine and the upcoming Ukranian spring/summer offensive in 2023. I did brief this at the Second HAAC (October 2023) and in Norway (November 2023). The question I had was does a minor advantage in force ratios or combat power ratios lead to a bigger advantage at the operational level of combat. The answer appears to be no, as this was reinforced by limited movement of the front line in Russo-Ukrainian War since the fall of 2022. 

My final slide in the briefing was “Does this relate to the fighting in Ukraine?” I then asked two questions:

  1. What are the odds?
    1. What is the strength of the deployed Ukrainian Army?
    2. What is the strength of the Russian Army deployed in Ukraine?
  2. What other advantages does the Ukrainian attacker have?
    1. Artillery
    2. Air Support? (Drones?)
    3. Observations/Intelligence
    4. Morale
    5. Training

Now, as it appears that Russia will be on the offensive this spring/summer, then I may need to restructure this slide and also add another point “artillery ammunition supply.”

 

I am probably going to do some more blog posts on this subject, looking at other levels of combat.

 

Podcast on The Battle for Kyiv

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.

Analysis of Force Ratios using the Campaign Data Base (CaDB) – third continuation

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:

Force Ratio    Notes

0.58                 HUSKY – US Invasion of Sicily (39 days)

1.05                 HUSKY – UK Invasion of Sicily (39 days)

1.15                 Ardennes Allied Counteroffensive South II (15 days)

1.22                SHINGLE – Allied Landing at Anzio (10 days)

1.23                The West Bank 1967 (3 days)

1.34                 Ardennes Allied Counteroffensive South I (9 days)

1.38                 Graziani’s Advance (6 days)

1.44                 Moselle-Metz (6 days)

1.50                 Ardennes Allied Counteroffensive North (15 days)

 

1.75 to 1.98     3 cases

2.02 to 2.32     4 cases

2.51 to 2.92     6 cases

3.63 to 4.94     5 cases

6.04 to 10.00   2 cases

 

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). 

Force Ratio   Notes

0.78                The Cauldron: Battle of Gazala (21 days)

0.80                The Sinai, 1967 (5 days)

0.93                Golan Heights, 1967 (2 days)

1.01                BUFFALO: Anzio Breakout (9 days)

1.50                KADESH: Israeli Attack in the Sinai (8 days)

1.57                PO Valley Breakthrough (UK) (22 days)

1.67                Battle of Normandy, US Army (31 days)

 

1.82 to 1.93    2 cases

2.10 to 2.49    3 cases

2.52 to 2.92    2 cases

3.47 to 4.54    5 cases

6.58 to 7.01    2 cases

 

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.

Dueling Defense Budgets

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.

Analysis of Force Ratios using the Campaign Data Base (CaDB) – second continuation

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):

  • Outcome I is limited action
  • Outcome II is limited attack
  • Outcome III is failed attack
  • Outcome IV is attack advances
  • Outcome V is defender penetrated
  • Outcome VI is defender enveloped
  • Outcome VII is other.

These definitions are used to create the following table:

Outcome             I        II      III        IV       V       VI       VII

Cases                15        9     10        29      21      8          2

Force Ratios   1.88   3.35   1.80    2.69    2.75   1.86   8.50

Loss Ratios    3.77   1.56   1.66    1.51    0.64   0.05   0.01

 

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:

  1. Failed attacks tend to be lower average odds than successful ones (i.e. 1.80 versus 2.69 and 2.75).
  2. Attackers suffer higher losses than defenders until they are penetrated (1.61 and 1.51 versus 0.64)
  3. These are the same patterns as for division-level combat.

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).

Analysis for Force Ratios using the Campaign Data Base (CaDB) – continued

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:

Force Ratio      Attacker wins   Defender wins *   Draws **   Notes

0.30                    1                                                                  Suomussalmi

0.52 to 0.73        6                         2

0.77 to 1.00        7                         5

1.01 to 1.25      14                         3                            1

1.27 to 1.50        8                         3                            1

1.55 to 1.75        9                         3

1.78 to 2.00       11                        5

2.02 to 2.50       10                        6                             2

2.51 to 2.92         8                                                       1 ****

3.01 to 4.00         8                      4 ***                       1 ****    Loos (3.97) – defender wins

4.02 to 4.94         8

5.79 to 7.33         5

10.00 to 11.21     2

 

 

Notes:

* Removed from this seven engagements coded as “limited action” and “limited attack.” Their ratios were 0.58, 1.51, 2.90, 2.90, 3.58, 6.55, 12.38

** Removed from this 15 engagements coded as “limited action” and “limited attack.”

*** Three World War one engagements (Festubert at 3.01, Chemin des Dames at 3.33 and Loos at 3.97) and First Cassino (US) at 3.12.

**** Gothic Line Stalemate I at 2.58 and Gothic Line Statement II (US) at 3.08

 

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.

Schedule for HADSS 2024

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:

HADSS_programme v2

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).

Analysis for Force Ratios using the Campaign Data Base (CaDB)

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:

                                                   Attacker   Defender   Draw 

Av. Attacker Strength               208,835    156,821     171,312

Av. Defender Strength                91,486    100,729       96,582

       Ratio                                   2.28           1.56           1.77

 

Av. Attacker Losses                    34,630      69,098       15,232

Av. Defender Losses                   52,466      64,271       12,632

      Ratio                                     0.66           1.08           1.21

 

Av. Attacker % per day              0.73           0.98           0.32

Av. Defender % per day             2.59           0.98           0.39

      Ratio                                      0.28          1.00            0.82

 

Starting Strength Ratio              2.42          2.24            1.79

Casualty Ratio                            1.04          2.51            1.22

 

Contemplate for a moment what this data is telling you. A few observations:

  1. There is a difference in force ratios between winning and losing engagements (2.28-to-1 vice 1.56-to-1).
  2. There is a difference in casualties between winning and losing engagements (0.66-to-1 vice 1.08-to-1).
  3. The data for these army-level operations does not look significant different than for a division-level operation. This is significant.

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).