Category Combat Databases

Aces at Kursk should be out in early July

According to Pen & Sword, the printers should be delivering Aces at Kursk next Friday (the 5th of July) to their warehouse, and so the stock should be booked in the week commencing 8th July, all being well.

Right now, Amazon UK is showing its release date as 30 Jan. 2024.  Amazon US is showing the release date as 25 July 2024. Waiting for this to be updated but I gather the UK release date is on or shortly after 8 July 2024. U.S. release date will be later (don’t know how much later). 

Hunting Falcon is also in process and will be released this summer.

Sorry for the delays, these are things not under my control.

Also see:

Aces at Kursk – Chapter Listing – The Dupuy Institute

Aces at Kursk – Summation – The Dupuy Institute



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 ( and Analysis for Force Ratios using the Campaign Data Base (CaDB) – continued | Mystics & Statistics ( and Analysis of Force Ratios using the Campaign Data Base (CaDB) – second continuation | Mystics & Statistics ( and Analysis of Force Ratios using the Campaign Data Base (CaDB) – third continuation | Mystics & Statistics (  It is a part of a briefing on forces ratios I will be giving at HADSS in UK: Schedule for HADSS 2024 | Mystics & Statistics ( and at HAAC near DC: Next Revised Schedule for the Third Historical Analysis Annual Conference (HAAC), 8 – 10 October 2024 | Mystics & Statistics (

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.


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 ( and Analysis for Force Ratios using the Campaign Data Base (CaDB) – continued | Mystics & Statistics ( and Analysis of Force Ratios using the Campaign Data Base (CaDB) – second continuation | Mystics & Statistics ( It is a part of a briefing on forces ratios I will be giving at HADSS in UK: Schedule for HADSS 2024 | Mystics & Statistics ( and at HAAC near DC: Next Revised Schedule for the Third Historical Analysis Annual Conference (HAAC), 8 – 10 October 2024 | Mystics & Statistics (

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.

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 ( and Analysis for Force Ratios using the Campaign Data Base (CaDB) – continued | Mystics & Statistics ( It is a part of a briefing on forces ratios I will be giving at HADSS in UK: Schedule for HADSS 2024 | Mystics & Statistics ( and at HAAC near DC: Next Revised Schedule for the Third Historical Analysis Annual Conference (HAAC), 8 – 10 October 2024 | Mystics & Statistics (

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 (

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




* 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.

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 ( 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 ( 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).


The 3-to-1 rule and the War in Ukraine

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 ( and The 3-to-1 Rule in Histories | Mystics & Statistics ( and The 3-to-1 Rule in Recent History Books | Mystics & Statistics (

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:


0.55 TO 1.01-TO-1.00…………ATTACK FAILS………………………….100……………………………………5

1.15 TO 1.88-TO-1.00…………ATTACK USUALLY SUCCEEDS………21…………………………………..48

1.95 TO 2.56-TO-1.00…………ATTACK USUALLY SUCCEEDS………10…………………………………..21

2.71 TO 1.00 AND HIGHER….ATTACK ADVANCES……………………..0…………………………………..42


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 ( and Force Ratios at Kharkov and Kursk, 1943 | Mystics & Statistics ( and Force Ratios in the Arab-Israeli Wars (1956-1973) | Mystics & Statistics (

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 (

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 ( 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 ( 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 (, 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.

Let’s talk about artillery shells

Now, when we first did the validation database the Ardennes Campaign Simulation Data Base, one of the fields we had to fill in for each division, and corps, and army was on the tons of ammunition used each day by four types.

This was because the combat models that were supposed to be validated using this database were used in part to determine the number of shells needed for a predicted upcoming war. Back in 1987, when we started this database, it was a war in Europe versus the Soviet Union and the Warsaw Pact.

Now, my history with the Concepts Analysis Agency (CAA), later renamed the Center for Army Analysis (still CAA), goes back to 1973, when it was founded in Bethesda, MD. I was in my junior year in high school, my mother had just been promoted to a school principal and my father had just finished his three-year assignment in the Pentagon. My mother did not want to move again, so, my father found another assignment in the DC area. This was with the newly forming CAA in 1973. He had just happened to have finished a master degree in Systems Analysis from USC, so was nominally qualified.

My father was working over at manpower in the Pentagon, under Col. John Brinkerhoff. They all reported to General Donn Starry (who I did have the pleasure of meeting). Those two transferred together over the CAA, with Col. (Dr.) John Brinkerhoff taking over a division with my father as his assistant. I therefore started hearing stories about CAA combat models in 1973 based upon my father’s hands-on experience. One of the stories he told was that the model tended to fire the longest-range weapons first as units were closing. This made the 8″ Howitzer very valuable. In fact, so valuable, that the best wargaming strategy was build an army of 8″ Howitzers and destroy the Warsaw Pact before they could ever get into engagement range. Obviously, there were a couple of flaws in that wargame.

But, the suite of models, some of which are still in use today, was used to determine the ammunition requirements for the U.S. Army. Therefore, a validation database needed to address these issues. The same fields also existed the Kursk Data Base (1993-1996), which ended up never being used to validate a combat model. It was used to create a big-ass book.

Anyhow, CAA combat models did determine our ammunition requirements until the end of the cold war (22 or 25 or 26 December 1991 when the Soviet Union fell). They were also used to determine the requirements for the 1991 Gulf War. According to the story I heard in a meeting, CAA provided the Army general staff with the requirements for the Gulf War. The general staff doubled the figures CAA gave and then we stacked every dock in the Gulf with ammunition. Luckily none of Hussian’s missiles hit those docks. At the end of the war, it turns out we shipped at least ten times the ammunition we needed. As this was old dumb munitions dating back to World War II, it was cheaper to destroy them there then ship them back, which is what we did. Don’t have a count of what was destroyed in the Gulf, but guessing it was millions of rounds. 

After that, I do not know what OSD PA&E or CAA or the U.S. Army did to determine ammunition requirements. We no longer had a neatly canned scenario like the Fulda Gap. We no longer had a clear enemy. How much ammunition is needed is driven by both the combat model used (which tends to “run hot”) and more significantly, the scenarios used. If all the scenarios used a four-day combat scenario (like the Gulf War) then one will end up with very different needs then if one is planning for a 90-day or 180-day war (or three-year war in the case of Ukraine). I have no idea what scenarios were used, and it is probably classified. But, the end result, is that our production of ammunition over the decades since 1991 has dropped considerably while a lot of our reserves were destroyed in the Gulf.

This, of course, harkens back to a complaint I have made over the years, which is that we tend to focus on the missions and wars we think are most likely now, and not the entire spectrum of wars and conflicts that we can see are possible if one looks wider and deeper into history. Clearly, we were not ready for extended war in Ukraine, and this is not the first time in recent times we have not been properly prepared for certain conflicts. I do discuss this issue in America’s Modern Wars. 

P.S. The West is underestimating Ukraine’s artillery needs – Defense One

Measuring Unit Effectiveness in Italy

We are in discussion over revisiting the measurement of combat effectiveness of select units in Italy 1943-1945. This was done by Trevor Dupuy in Numbers, Predictions and Wars (1977) by division using the QJM (Quantified Judgment Model) and was done in aggregate by me in War by Numbers (2017) using simply comparative statistics. If you feel lifeless reading blogs like this, you can rest for a bit through sites such as 홈카지노.

For a little background on page 115 of Understanding War is a chart of German, UK and U.S. units in the Italian Campaign and their CEVs (Combat Effectiveness Values). Their values range from 0.60 to 1.49. The German Hermann Goering Division is the highest rated division at 1.49. This is based upon five engagements. The German 3rd PzGrD was rated 1.17 based upon 17 engagements and 15th PzGrD was rated 1.12 based upon 11 engagements. This was done using the QJM.
    For reference, I would recommend reading the following four books:
1. Understanding War
2. War by Numbers
3. Attrition (optional)
4. Numbers, Predictions and War (optional)
There are two ways to measure combat effectiveness. 1) Do a model run and compared the results of the model run to historical data. This requires 1) a historically validated combat model (there are very few), and 2) confidence in the model. 2) The other option is to do a statistical comparison of a large number of engagements. This is what I did in Chapters 5, 6 and 7 of War by Numbers.
One can measure combat effectiveness by three means: 1) Casualty effectiveness, 2) special effectiveness (distance opposed advance) or 3) Mission effectiveness. This is all discussed in Trevor Dupuy’s work and in War by Numbers.
To date, the only people I am aware of who have published their analysis of combat effectiveness is Trevor Dupuy, me (Chris Lawrence) and Niklas Zetterling. See: CEV Calculations in Italy, 1943 | Mystics & Statistics ( and his book Normandy 1944 (recently revised and republished). There is also a six-volume quantitative effort related to Operation Barbarossa by Nigel Askey, which I have never looked at. Everyone else has ignored quantifying this issue, although there are no shortage of people claiming units are good, bad or elite. How they determine this is judgment (and it is often uncertain as to what the basis is for this judgment).
Now, the original work on this was done by Trevor Dupuy in the late 1970s based upon his data collection and the QJM. Since that time the model has been updated to the TNDM. The engagements used for the QJM validation were then simplified (especially in weapons counts) and assembled into the LWDB (Land Warfare Data Base). The LWDB had around 70 engagements from the Italian Campaign. Since that time we have created the DuWar series of databases which includes the DLEDB (Division-Level Engagement Data Base). See: The History of the DuWar Data Bases | Mystics & Statistics ( We have doubled the number of Italian Campaign engagements to around 140.
There are a total of 141 Italian Campaign division-level engagements in the DLEDB. The first 140 engagements cover from September 1943 to early June 1944. There is almost 12 months of war not covered and not all units in the first part of the campaign are covered. With all the various nationalities involved (i.e German, Italian, U.S., UK, Free French, Moroccan, New Zealand, South African, Poland, Indian, Canadian, Brazilian, Greek, etc.), the Italian Campaign is a fertile field for this work. We are looking at stepping back into this. 
Units involved in engagements in the DELDB:
3rd PzGrD: 25 cases
15th PzGrD: 39 cases
16th PzD: 7 cases
26th PzD: 8 cases
29 PzGrD: 6 cases
65th ID: 5 cases
94th ID: 8 cases
305th ID: 4 cases
362nd ID: 3 cases
715th ID: 2 cases
4th Para D: 3 cases
HG PzGrD: 26 cases
LXXVI Pz Corps: 4 cases
12th Para Rgt: 1 case
1st AD: 3 cases
3rd ID: 19 cases
34th ID: 15 cases
36th ID: 12 cases
45th ID: 20 cases
85th ID: 7 cases
88th ID: 4 cases
509th PIB: 1 case
1st SSF: 1 case
7th AD: 6 cases
1st ID: 9 cases
5th ID: 2 cases
46th ID: 18 cases
56th ID: 24 cases

Battlefield Tour of the Ardennes

Jay Karamales, the co-author of Against the Panzers and of the soon-to-be released Hunting Falcon, did record a video of his tour of the Ardennes in 1993. They are posted to YouTube. I just found out about it. So, the links to his YouTube videos are here:

Day 1, England to La Gleize (

Day 2, 3rd AD and Kauffman (

Day 2, Chateau Froid Cour and December 1944 Museum (

Day 2, Dom Bütgenbach (

Day 3, Peiper’s Route, Scheid to Stavelot (