Mystics & Statistics

U.S. Navy Compared to Russian Navy

An elevated port side view of the forward section of a Soviet Oscar Class SSGN nuclear-powered attack submarine. (Soviet Military Power, 1986)

One person commented on this blog about the danger posed by Russian submarines. Probably a good time to look at what the threat is.

I did start my career in the U.S. defense industry working with submarine sonars and spectrum analyzers. This was back in the bad old days, when there were hundreds of subs out there. In our new found more peaceful world, there are a lot less.

Russian has around 56 submarines, according to Wikipedia. How many of these are fully operational is not something I know. Of those, 11 of them are boomers or ballistic missile submarines. These are submarines that carry nuclear missiles and would not be part of any fleet-on-fleet battle. They also list 6 “special-purpose submarines,” two are old converted attack submarines. The group of subs that threaten our control of the seas are 8 cruise missile submarines (SSGN) and 15 nuclear-powered attack submarines (SSNs). There are also 22 smaller diesel-power attack submarines. This is 45 or less operational subs to threaten our carrier fleets.

The biggest danger from Russian fleet is their 8 cruise missile submarines. These really are a threat to our carriers.

The United States has around 66 submarines. Of those, 14 are boomers.

 

Comparative Ship Count:

…………………………U.S……Size…………………….Russia…….Size

Aircraft Carriers………11…….100,000-106,300………..1….,…….58,600 tonnes

LHA/LHD……………….9……..41,150-45,693 tons (these are carriers !!!)

Battlecruisers………….0……………………………………2…………28,000 tons

Cruisers……………….22……..9,800 tons………………..3………….12,500 tons

Destroyers…………….69……..8,315-9,800…………….11…………7,570 – 7,940 tons

LCS…………………….20…….3,104-3,900 (“Littoral Combat Ships”)

Frigates…………………0…………………………………..10………….1,930 – 5,400 tons

Large Corvettes………………………………………………6………….2,200 tons

Corvettes……………………………………………………..76………..500 – 1050 tons

 

LPD…………………….11……25,300 (“Landing Platform Dock”)

LSD…………………….12…..15,939-16,100 (“Landing Ship Dock”)

LST (Landing Ship Tank)…………………………………..20…………..4,080 – 6,600 tons

Special-purpose………7…..895-23,000…………………18…………..500 – 23,780

Patrol Ships…………………………………………………..2…………..1,500

MCM……………………11……….1,312 tons (mine countermeasures)

PC………………………13………….331 tons (coastal patrol)

 

Large SSBN…………………………………………………..1………….48,000 tons

SSBNs………………..14……..18,750 tonnes……………10…………13,700 – 24,000 tons

SSGN…………………..4………18,750 tonnes…………….8………….19,400 tons

SSN……………………48…….6,927-12,139 tonnes…….15…………7,250 – 13,800 tons

SSK…………………….0……………………………………..22…………2,700 – 3,950 tons

Special purpose subs…………………………………………6………….600 – 18,200 tons

 

I did not bother to list landing craft (Russia has 37 of 555 tons or less), patrol boats (Russian has 37 of 139 tons or less), mine countermeasure vessels (Russian has 6 of 1,100 tons or less), auxiliaries (cargo ships, ice breakers, logistic vessels, salvage vessels, tugs, tankers, oilers, transports, etc.), LCCs (amphibious command ships), submarine tenders, maritime prepositioning ships (T-AK), the USS Pueblo, and the USS Constitution.

What is a ton:

Short ton (U.S.) = 2,000 pounds

Metric Tonne = 2,204.6 pounds

Long ton (UK) = 2,240 pounds

 

Normandy 1944: German Military Organization, Combat Power and Organizational Effectiveness

Niklas Zetterling’s revised and update version of his excellent book Normandy 1944 is being re-issued. According to Amazon.com it will be available January 10, 2020. The link is here: Normandy 1944

It is set up to “look inside” so you can get some idea what is in there. It is of course, not another war story but a two part discussion on “Campaign Analysis” and “German Combat Formations.”

The “look inside” feature did not include an ability to search the text, so I was not able to check the really important stuff, like how many times Trevor Dupuy and I are mentioned in the book. I am graciously acknowledged in the introduction (as is Richard Anderson). Now, I did write an appendix for the original book. Always the gentleman, Niklas did ask my permission to remove it from this edition.

The book does include a discussion of the relative combat efficiency of the German forces compared to British and U.S. units, always a sensitive subject. We have never invested a lot of time in analyzing Normandy. Most of our analysis of this subject is from Italy 1943-44, Ardennes (Battle of the Bulge) 1944-45 and Kharkov and Kursk 1943 (and shown in War by Numbers). So this is a nice independent look at the subject using additional data from a different campaign by a different scholar.

Time and the TNDM

[The article below is reprinted from December 1996 edition of The International TNDM Newsletter. It was referenced in the recent series of posts addressing the battalion-level validation of Trevor Dupuy’s Tactical Numerical Deterministic Model (TNDM).]

Time and the TNDM
by Christopher A. Lawrence

Combat models are designed to operate within their design parameters, but sometimes we forget what those are. A model can only be expected to perform well in those areas for which it was designed in and those areas where it has been tested (meaning validated). Since most of the combat models used in the US Department of Defense have not been validated, this leaves open the question as to what their parameters might be. In the cue of the TNDM, if the model is not giving a reasonable result, then you must ask, is it because the model is being operated outside of its parameters? The parameters of the model are pretty well defined by the 149 engagements of the QJM Database to which it was validated.

One of the areas where there is a problem with the TNDM is that while the analyst is capable of running a battle over any time period, the model was fundamentally validated to run 1 to 3 days engagements. This means that there should be a reduced confidence in the results of any engagement of less than 24 hours or over three days. The actual number of days used for each engagement in the original QJM data base is shown below:

By comparison, the 75 battalion level engagements that we are using to validate the TNDM for battalion-level engagements occur over the following time periods:

Three of the engagements used in the battalion-level validation are from the QJM database.

We did run sample engagements of 24 hours, 12 hours, 6 hours and 3 hours. The results of the 12-hour run was literally 1/2 the casualties and 1/2 of the advance for the 24-hour run. The same straight dividing effect was true for the 3- and 6-hour runs. For increments less than 24 hours the model just divided the results by the number of hours. As Dave Bongard pointed out to me, there are various lighting choices, including daylight and night, and these could vary the results some if used. But the impact for daylight would be 1.1 additional casualties and the reduction for night is .7 or .8.

The problem is that briefer battles will result in higher casualties per hour than extended battles. Also, in any extended battle, there are intense periods and un-intense periods, with the model giving the average result of those periods. For battles of less than 24 hours, there tends to be only intense periods. Therefore, it should be expected that battles lasting 3 hours should have more than 1/6 the losses of a 24 hours battle. This will be tested during the battalion-level validation.

For battles in excess of one day, there is a table in the TNDM that reduces the overall casualties and advance rate over time to account for fatigue.

U.S. Population Growth for 2019

The U.S. population grew 1.5 million in 2018 up to 328 million. This is around 0.5% growth rate. Over a third of that growth was immigrants.

Immigration in 2019 was 595,000 people, down from around 1 million in 2016. Guessing this refers to legal immigrants.

This is from an AP article: With births down, U.S. had slowest growth rate in the century

This is all related to our various discussions on demographics:

Demographics of the United States

For those following this subject for political interest, the projected votes swings by state after the 2020 census will be:

“Blue” states (tend to vote Democratic):

California – 1 representative and electoral college vote

Colorado: +1

Oregon: +1

Illinois: -1

Minnesota: -1

New York: -1

Rhode Island: -1

Total =  -3

 

Swing states:

Florida: +2

Michigan: -1

Ohio: -1

Pennsylvania: -1

Total: =  -1

 

“Red” states (tend to vote Republican):

Texas: +3

Arizona: +1

Montana: +1

North Carolina: +1

Alabama: -1

West Virginia: -1

Total =  +4

 

Anyhow, we tend to avoid “politics” on this blog, but these changes are worth noting.

How Attrition is Calculated in the QJM vs the TNDM

French soldiers on the attack, during the First World War. [Wikipedia]

[The article below is reprinted from December 1996 edition of The International TNDM Newsletter. It was referenced in the recent series of posts addressing the battalion-level validation of Trevor Dupuy’s Tactical Numerical Deterministic Model (TNDM).]

How Attrition is Calculated in the QJM vs the TNDM
by Christopher A. Lawrence

There are two different attrition calculations in the Quantified Judgement Model (QJM), one for post-1900 battles and one for pre-1900 battles. For post-1900 battles, the QJM methodology detailed in Trevor Dupuy’s Numbers, Predictions and War: Using History to Evaluate Combat Factors and Predict the Outcome of Battles (Indianapolis; New York: The Bobbs-Merrill Co., 1979) was basically:

(Standard rate in percent*) x (factor based on force size) x (factor based upon mission) x (opposition factor based on force ratios) x (day/night) x (special conditions**) = percent losses.

* Different for attacker (2.8%) and defender (1.5%)
** WWI and certain forces in WWII and Korea

For the attacker the highest this percent can be in one day is 13.44% not counting the special conditions, and the highest it can be for the defender is 5.76%.

The current Tactical Numerical Deterministic Model (TNDM) methodology is:

(Standard personnel loss factor*) x (number of people) x (factor based upon posture/mission) x (combat effectiveness value (CEV) of opponent. up to 1.5) x (factor for surprise) x (opposition factor based on force ratios) x (factor based on force size) x (factor based on terrain) x (factor based upon weather) x (factor based upon season) x (factor based upon rate of advance) x (factor based upon amphibious and river crossings) x (day/night) x (factor based upon daily fatigue) = Number of casualties

* Different for attacker (.04) and defender (.06)

The special conditions mentioned in Numbers, Predictions, and War are not accounted for here, although it is possible to insert them, if required.

All these tables have been revised and refined from Numbers, Predictions, and War.

In Numbers, Predictions and War, the highest multiplier for size was 2.0, and this was for forces of less than 5,000 men. From 5,000 to 10,000 is 1.5 and from 10,000 to 20,000 is 1.0. This formulation certainly fit the data to which the model was validated.

The TNDM has the following table for values below 15,000 men (which is 1.0):

The highest percent losses the attacker can suffer in a force of greater than 15,000 men in one day is “over” 100%. If one leaves out three large multipliers for special conditions—surprise, amphibious assault, and CEV—then the maximum percent losses is 18%. The multiplier for complete surprise is 2.5 (although this degraded by historical period), 2.00 for amphibious attack across a beach, and 1.5 for enemy having a noticeable superior CEVs In the case of the defender, leaving out these three factors, the maximum percent casualties is 21.6% a day.

This means at force strengths of less than 2,000 it would be possible for units to suffer 100% losses without adding in conditions like surprise.

The following TNDM tables have been modified from the originals in Numbers, Predictions, and War to include a casualty factor, among other updates (numbers in quotes refer to tables in the TNDM, the others refer to tables in Numbers, Predictions, and War):

Table 1/”2”: Terrain Factors
Table 2/“3″: Weather Factors
Table 3/“4″: Season Factors
Table 5/”6″: Posture Factors
Table 6/“9″: Shoreline Vulnerability
Table 9/”11″: Surprise

The following tables have also been modified from the original QJM as outlined in Numbers, Predictions, and War:

Table “1”: OLl’s
Table “13”: Advance Rates
Table “16”: Opposition Factor
Table “17”: Strength/Size Attrition Factors
Table “20”: Maximum Depth Factor

The following tables have remained the same:

Table 4/“5”: Effects of Air Superiority
Table 7/“12”: Morale Factors
Table 8/“19”: Mission Accomplishment
Table “14″: Road Quality Factors
Table “15”: River or Stream Factor

The following new tables have been added:

Table “7”: Qualitative Significance of Quantity
Table “8”: Weapons Sophistication
Table “10”: Fatigue Factors
Table “18”: Velocity Factor
Table “20”: Maximum Depth Factor

The following tables has been deleted and the effect subsumed into another table:

unnumbered: Mission Factor
unnumbered: Minefield Factors

As far as I can tell, Table “20”: Maximum Depth Factor has a very limited impact on the model outcomes. Table “1”: OLIs, has no impact on model outcomes

I have developed a bad habit, if I want to understand or know something about the TNDM, to grab my copy of Numbers, Predictions, and War for reference. As shown by these attrition calculations, the TNDM has developed enough from its original form that the book is no longer a good description of it. The TNDM has added in an additional level of sophistication that was not in the QJM.

The TNDM does not have any procedure for calculating combat from before 1900. In fact, the TNDM is not intended to be used in its current form for any combat before WWII.

Charles Hawkins passed away

I just heard that Charles Hawkins, or Chuck Hawkins, passed away September 13, 2019 in Ninilchik Alaska. He was born in 1946.

Chuck Hawkins joined Trevor Dupuy’s Data Memory Systems Inc. (DMSI) as a vice-president in 1988. He was a former army captain who fought in Vietnam with a strong interest in analysis of combat. He came into the organization while it was at its peak but was about to crash due to the deep budget cuts that occurred at the end of the Cold War. He struggled on with the collapsing DMSI until around 1992 and closed it down. He then continued work in the industry with a number of efforts, eventually becoming an expert on the North Korea. He spent some time at their border, which always produced a great slide show.

He also worked briefly with me in 1993 on the report I did on Federally Funded Research and Development Centers (FFRDCs) for the Congressional Office of Technology Assessment (OTA). A copy is here:

https://digital.library.unt.edu/ark:/67531/metadc39765/m1/1/

He was an active participant at The Military Conflict Institute (TMCI) and was still involved in North Korean affairs.

There are two interview videos of him on Youtube: (1) Chuck Hawkins Pt. 1 – YouTube and (1) Chuck Hawkins – Part 2 – YouTube

Summation of Human Factors and Force Ratio posts

The following five posts make up our discussion of the impact of Human Factors on Force Ratios.

Force Ratios at Kharkov and Kursk, 1943

Force Ratios in the Arab-Israeli Wars (1956-1973)

Measuring Human Factors based upon Casualty Effectiveness

Measuring Human Factors based on Casualty Effectiveness in Italy 1943-1944

The Performance of Armies in Italy, 1943-44

As a result of a comment by Tom from Cornwall, we ended up adding three posts to this discussion that looked at terrain and amphibious operations and river crossings in Italy:

German attacks in Italy by Terrain (1943-44)

Amphibious and River Crossing attacks in Italy 1943-44

Amphibious and River Crossing Engagements in the Italian Campaign 1943-44

The previous posts on this discussion on force ratios are presented here. These were the posts examining the erroneous interpretation of the three-to-one rule as presented in Army FM 6-0 and other publications:

Summation of Force Ratio Posts

We are going to end this discussion for now. There is some additional data from the European Theater of Operations (ETO) and Ardennes that we have assembled, but it presents a confusing picture. This is discussed in depth in War by Numbers (pages 32-48).

I am assembling these discussions on force ratios and terrain into the opening chapters for a follow-on book to War by Numbers.

Kuznetsov on Fire

[Photo deleted at the request of AFP]

Just noted this article:

https://news.yahoo.com/russias-only-aircraft-carrier-fire-port-news-agencies-100747109.html

This is Russia’s only carrier. It is in dock in Siberia undergoing refitting. It is supposed to be done in 2021…but this is doubtful. The Russian fleet is still extremely limited in capability.

We have written about this before.

Lives Of The Russian (And Ex-Russian) Aircraft Carriers

The Admiral Kuznetsov Adventure

Russian Fleet Strength

Our count of carriers throughout the world in 2016 is given in this post:

Chinese Carriers

2016 count:

  • U.S. 19 carriers
  • U.S. Allies: 14 carriers
  • Neutrals: 5 carriers (India, Brazil, Egypt, Thailand)
  • Potentially hostile: 2 carriers (China, Russia)
  • Total: 40 carriers

 

The Performance of Armies in Italy, 1943-44

 

Polish Sherman III after battle on Gothic Line, Italy, September 1944

Having looked at casualty exchanges from my book War by Numbers and in the previous post, it is clear that there are notable differences between the German and Soviet armies, and between the Israeli and Arab armies. These differences show up in the force ratio tables, in the percent of wins, and in the casualty exchange ratios. As shown above, there is also a difference between the German and the U.S. and UK armies in Italy 1943-44, but this difference is no where to the same degree. These differences show up in the casualty exchange ratios. They also will show up in the force ratio comparisons that follow.

The Italian Campaign is an untapped goldmine for research into human factors. In addition to German, American and British armies, there were Brazilian, Canadian, French, French Algerian, French Moroccan, Greek, Indian, Italian, New Zealander, Polish, and South African forces there, among others like the Jewish brigade. There was also an African-American Division and a Japanese-American battalion and regiment actively engaged in this theater. Also the German records are much better than they were in the second half of 1944. So, the primary source data these engagements are built from are better than the engagements from the ETO.

We have 137 engagements from the Italian Campaign. There are 136 from 9 September to 4 June 1944 and one from13-17 September 1944. Of those, 70 consisted of the Americans attacking, 49 consisted of armed forces of the United Kingdom in the offense, and 18 consisted of the Germans attacks, often limited and local counterattacks (eight attacks against the United States and ten attacks against the UK). So, let us compare these based upon force ratios.

American Army attacking the German Army, Italy 1943-44

(70 cases in the complete data set, 62 cases in the culled data set)

 

Force Ratio……………Percent Attacker Wins………………..Number of Cases

1.22 to 1.49……………………….42%………………………………………..26

    Culled…………………………………48…………………………………………21[1]

1.50 to 1.95………………………..43………………………………………….30

    Culled…………………………………48…………………………………………27[2]

2.02 to 2.23………………………100…………………………………………..4

2.58 to 2.96………………………..71…………………………………………..7

3.04…………………………………100…………………………………………..1

Gap in data

4.11 to 4.25………………………100……………………………………………2

 

There were seven cases of engagements coded as “limited attacks” and one case of “other”. These eight cases are excluded in the table above on those lines in italics.

Needless to say, this is a fairly good performance by the American Army, with them winning more than 40% the attacks below two-to-one and pretty winning most of them (86%) at odds above two-to-one.

 

British Army attacking the German Army, Italy 1943-44

(49 cases in the complete data set, 39 cases in the culled data set)

 

Force Ratio………………..Percent Attacker Wins………………..Number of Cases

0.85………………………………….0%……………………………………………….1

1.17 to 1.41………………………60…………………………………………………5

1.50 to 1.69………………………33…………………………………………………3

2.01 to 2.49………………………50……………………………………………….12

    Culled………………………………..86…………………………………………………7[3]

2.77……………………………….100………………………………………………….1

3.18 to 3.49………………………30………………………………………………..10

    Culled……………………………….43…………………………………………………7[4]

3.50 to 3.73……………………..80…………………………………………………..5

4.23 to 4.99……………………..42…………………………………………………12

    Culled………………………………50…………………………………………………10[5]

 

There were five cases of limited action and five cases of limited attack. These ten cases are excluded in the table above on those lines in italics.

This again shows the difference in performance between the American Army and the British Army. This is always an uncomfortable comparison, as this author is somewhat of an anglophile with a grandfather from Liverpool; but data is data. In this case they won 44% of the time at attacks below two-to-one, which is similar to what the U.S. Army did. But then, they only won only 63% of the time at odds above two-to-one (using the culled data set). This could just be statistical anomaly as we are only looking at 30 cases, but is does support the results we are seeing from the casualty data.

What is interesting is the mix of attacks. For the American Army 77% of the attacks were at odds below two-to-one, for the British Army only 23% of the attacks were at odds below two-to-one (using the culled data sets). While these 99 cases do not include every engagement in the Italian Campaign at that time, they include many of the major and significant ones. They are probably a good representation. This does probably reflect a little reality here, in that the British tended to be more conservative on the attack then the Americans. This is also demonstrated by the British lower average loss per engagement.[7]

The reverse, which is when the Germans are attacking, does not provide a clear picture.

German Army attacking the American and British Army, Italy 1943-44 – complete data set (18 cases)

Force Ratio…………………..Percent Attacker Wins…………………Number of Cases

0.72 to 0.84………………………….0%………………………………………………7

1.17 to 1.48………………………..50…………………………………………………6

1.89…………………………………….0…………………………………………………1

2.16 to 2.20………………………..50…………………………………………………2

Gap in data

3.12 to 3.24………………………..50…………………………………………………2

 

The Germans only win in 28% of the cases here. They win in 13% of the engagements versus the U.S. (8 cases) and 40% of the engagements the UK (10 cases). Still, at low odds attacks (1.17 to 1.48-to-1) they are winning 50% of the time. They are conducting 78% of their attacks at odds below two-to-one.

In the end, the analysis here is limited by the number of cases. It is hard to draw any definitive conclusions from only 18 cases of attacks. Clearly the analysis would benefit with a more exhaustive collection of engagements from the Italian Campaign. This would require a significant investment of time (and money).[8]

Regiment de Trois-Rivieres tanks entering the ruins of Regabuto, August 4th, 1943. Source: http://www.sfu.ca/tracesofthepast/wwii_html/it.htm

————————–

[1] There were four limited attacks that resulted in three defender wins and a draw. There was one “other” that was an attacker win.

[2] There three limited attacks that resulted in two defender wins and a draw.

[3] There were four “limited actions” that were defender wins and one “limited attack” that was a defender win.

[4] There as one “limited action” that was a defender win and two “limited attacks” that were defender wins.

[5] There were two “limited attacks” that were defender wins.

[6] The author’s grandfather was born in Liverpool and raised in Liverpool, England and Ryls, Wales. He served in the British merchant marine during World War I and afterwards was part of the British intervention at Murmansk Russia in 1918-1919. See the blog post:

Murmansk

[7] See War by Numbers, pages 25-27. The data shows that for the Americans in those 36 cases where their attack was successful they suffered an average of 353 casualties per engagement. For the 34 American attacks that were not successful they suffered an average of 351 casualties per engagement. For the UK, in the 23 cases where their attack was successful, the UK suffered an average of 213 casualties per engagement. Of the 26 cases where the UK attacks were not successful, they suffered an average of 137 casualties per engagement.

[8] Curt Johnson, the vice-president of HERO, estimated that it took an average of three man-days to create an engagement. He was involved in developing the original database that included about half of the 137 Italian Campaign engagements. My estimation parameter, including the primary source research required to conduct this is more like six days. Regardless, this would mean that just to create this 137 case database took an estimated 411 to 822 man-days, or 1.6 to 3.3 man-years of effort. Therefore, to expand this data set to a more useful number of engagements is going to take several years of effort.