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24 June 2022

Experimental Wargaming at the Tactical Level: An Example

Jim Rohrer

Examples of wargaming at the tactical level are scarce in the military literature and army manuals (Hodge, 2012). Courses of action are tested at the strategic and operational level using a paradigm based on a three-legged stool for “What If” analysis: computer simulation, experimentation, and wargaming (Alberts & Hayes, 2002). The legs of the stool represent different approaches to What If analysis that are useful in different situations. Unfortunately, this paradigm might become limiting as the legs turn into silos. The purpose of this paper is to demonstrate that tactical wargaming is feasible by crossing the barriers between simulation, wargaming and experimentation. Fair warning: this demonstration involves dice despite objections to their use in military wargaming (Guyer, Rovzar, & Sprang, 2021).

The Scenario

Kämärä was the first battle of the Finnish Civil War (Wikipedia, Downloaded June 21, 2022). In the Russian and Finnish civil wars, the soviets were called Reds and their opponents were called Whites. An army of 500 Finnish Whites was driven out of Vyborg in Karelia on January 25, 1918. They crossed Vyborg Bay on the ice and camped on an island. They were headed toward White-controlled territory so their next stop was the village of Säiniö. They drove Reds out of the railway station but a train filled with Russian sailors arrived and the Whites were forced to retreat. This was January 26. Revolution was declared by the Reds in Helsinki that same evening. On January 27, the Whites captured the village of Kämärä where there was another railway station. Finding a telegram saying a large shipment of weapons intended for the Red Army would come through from Petrograd on January 28, Colonel Adolf Aminoff detached sixty soldiers to ambush and disrupt the shipment. He did not use his entire force because he judged capturing the weapons was not realistic. Two trains arrived, one with the weapons and one with 400 Red soldiers led by Finnish Reds based in Petrograd. The Whites were able to derail the locomotive but the Reds set up their machine guns and drove them away. The Whites escaped on skis despite being targeted by artillery fire.

Historians give the victory to the Reds. The Whites were driven away. Twenty percent of the ambushers were killed. On the other hand, the mission objectives were accomplished (ambush and disrupt the shipment). Using the entire force as the denominator, the casualty rate was lower for the Whites than for the Reds (18/500 vs 30/500).

This historical battle raises an interesting question: Should Colonel Aminoff have made a serious attempt to capture or destroy the weapons? The forces were of equal size. The Reds could be attacked quickly before they set up heavy weapons and artillery.

Order of Battle, Rules, Mission Objectives and Positions

In this simulation, I gave the Whites eight infantry platoons (divided into two units, one north and one south) and one cavalry stand. I was not able to learn the combination of arms available to Col. Aminoff but assumed they did not have artillery or a crew-served MG because they escaped Vyborg across ice and also because they were driven away from Säiniö by a train load of sailors. At Kämärä, the Reds had a train filled with weapons including artillery but, realistically, they would not have been able to use them all in the battle, so I gave them one crew-served machine gun unit, one artillery unit, and seven infantry platoons.

A perfect reflection of the actual order of battle is not necessary for this test. Instead, the balance between the two armies should be approximately correct. Since both armies had about 500 soldiers, each was given about the same number of platoons. However, the Whites struck first and the Reds would have to assume firing positions, so I gave the Reds one less infantry platoon. On the other hand, the Reds were assumed to be able to position one artillery unit and one MG unit after the first round. The net effect was eight bases for the Whites, seven for the Reds and the beginning but nine in the second round, for an average of eight bases for the Reds across the two rounds.

The rules of play were a loose combination of those suggested by Neil Thomas (Thomas, 2005) and those used in Two-Hour Wargames (Teixeira, 2020). All actions were determined by rolling one six-sided die. I assumed the Reds would not be able to set up their MG or the artillery until the second round.

The White mission was to scatter the Reds and delay the train. The Reds sought to protect the weapons on the train by driving away the Whites.

When the battle began, the train was derailed and both sides are assumed to be behind cover (see Picture 1). The train itself provided cover for the Reds. The Whites were holding the cavalry in reserve. Part of the Whites were on the north side of the train and part were on the south. Some of the Red platoons fired north and some fired south.

Picture 1. Mockup of the battle using miniatures: Four White infantry platoons were set up south of the train along with the cavalry. Four more were north of the train. The Reds fired north with three platoons (one is hidden by the train) and south with four platoons. Red artillery and MG would be added in Round two.

The Experiment

The hypothesis tested here was that the casualty ratio would be significantly different for the Whites than the Reds if the Whites attacked with their entire force and began withdrawing at the beginning of the second round. The casualty ratio was computed as the number of platoons lost by the Whites minus the number lost by the Reds divided by eight. (The whites had eight platoons and the Reds had eight when averaged over the two rounds.) Microsoft Excel was used for the statistical analysis.

In this set of replays, Whites began withdrawing at the beginning of round two. This permitted each Red unit to fire at a retreating unit one time. When the Red turn began (the second part of Round two), each Red unit fired, the White target withdrew further, then the Red unit fired again. The artillery and the MG were used in Round two. The net effect of these parameters was that White was vulnerable to Red shooting as they were withdrawing and not shooting back. This gave the Reds more opportunities to hit the Whites than the Whites had to hit the Reds.

The result after ten rounds is shown in Table 1 and Figure 1. Whites experienced more casualties than Reds six out of ten times. The mean difference was .29, favoring the Reds. P is the probability that white and red losses were truly different and the differences were not due to chance. The probability that the difference is due to chance is less than 2 percent. We can be over 97% confident that the difference is real. More iterations would have been necessary if the difference was less dramatic.




Table 1. White and Red Losses (P<.012)

Round

Whites

Reds

Ratioa

1

3

6

-0.375

2

3

3

0

3

6

1

0.625

4

6

2

0.5

5

5

0

0.625

6

2

2

0

7

7

2

0.625

8

5

1

0.5

9

3

0

0.375

10

1

1

0


a Casualty Ratio = (White - Red)/8


Conclusions

The results of this experiment support Colonel Aminoff’s decision to detail a detachment of sixty soldiers to attack the munitions train instead of using his entire force. However, the study has two limitations that should be considered. First, the results are dependent on the assumptions made about the order of battle and the rules. Second, the experiment was conducted by a single investigator. As always, replication of the experiment by other investigators would increase confidence in the findings.

Alberts and Hayes divided approaches to “What If” studies as being computer simulations, experimentation or wargames (Alberts & Hayes, 2002). They recommended development of extended experimentation campaigns instead of relying on isolated experiments. While development of computer simulations for testing What If questions has much appeal, this has not worked out well in practice for the military. Problems include the extended time frame required to develop a complete set of conditional probabilities for inclusion the model, low return on investment, lack of confidence on the part of senior officers about the potential for quantification and uncertainties arising from the “fog of war.” Computer simulation might be more useful at the strategic and operational levels than for tactical questions such as the one addressed in this report (Hofmann & Lehman, 2007).

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