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A few weeks ago I reviewed Corner Lot with Tom Lehmann. Tom asked abot the $2 raises. One of the reasons, asides from accelerating the cashflow management challenge, is that $2 raises greatly increases the rate of subsequent $1-off events1, or if you wish, Power Grid moments2. Tom ever so gently suggested that the $2 raises were an unjustified complexity as such $1-off moments were in fact something of a false decision 3.
After some thought I’ve concluded that he’s quite right, and yet not. The core notion is of the $1-off decision is that at the time of (fund) allocation a player is able to reasonably predict that spending $1 more or less now will control whether or not they’ll be $1-off for a later item. Tom is right, that’s a tall order and in the case of Corner Lot or Power Grid, or any sufficiently dynamic system, this is bogus. In Corner Lot such an estimation requires predicting not only the cards in the future markers, but the exact results of player bids – certainly not a reasonable question at the $1 precision level. The players simply have no way to predict that accurately. Instead the $1-off moments are effectively random events which simply happen to the players, randomly specifying that a given player does or does not have enough money for something. At this level the $1-off events, and their creation, are clearly uninteresting and the decision at the point the $1-off event was incepted (when the money was allocated) doesn’t really exist.
But that is not the whole story. When a $1-off event occurs, the subject player must decide how to respond and, if necessary, to recover. There are frequently real decisions at this point: The player can’t afford what they need or want, so how to marshal their capital to still support their victory? There’s usually a real decision there and that’s where the decision is. The decision isn’t at the time the $1-off event is created, not at its inception, but rather the decision is post-facto in the recovery from the random event. Additionally, this clearly identifies the real design question: Is the additional rules complexity of requiring a minimum $2 raise justified by the additional interesting decisions created by recovering from the higher rate of $1-off events? I’m tempted to say it is, but I’m clearly also biased. Hey play-testers, what do you think?
One of the other results of the conversation with Tom is that I’m going to be forking Corner Lot. I’m pleased with the current game and enjoy playing it, but auctions are out of fashion with the German publishers and the required componentry (chips, markers etc) make the more attractive lower price points difficult to realise. As a result I’m going to fork the design and create a different game, one still based on the same reservation bidding concept, but with considerable less arithmetic and with no explicit auctions (ie no round-robin auctions to resolve multi-bid cards). I’ve no idea on the game yet, or much idea about the theme (Ariel Seoane has suggested musical group bookings for a concert), but I’m working on it. Currently the numbers are just not working out…
Eddie Robbin’s Baltimore & Ohio is the latest member of the Historic Railroads System and is part of the Winsome Games’ 2009 Essen Collection. It is a particularly trenchant perfect and certain information game all about timing, timing, and well, timing. In broader character, Baltimore & Ohio is Rimsky Korsakov‘s Flight of the Bumble Bee: full of little surges and races, layers upon layers of them, never relenting, always rushing, all of the races critical and requiring full attention and an endless delicate dedication to the dance.
Baltimore & Ohio has been described as the Historic Railroads System meets the 18xx, and there’s some truth to the claim. Functionally it is clearly a member of the Historic railroads System with a hex-map, track abstracted to putting a cube in a hex on the map, companies with shares, company dividends a function of company cubes in cities, etc. Architecturally Baltimore & Ohio is a child of 1825 Unit 1 (and 1825 Unit 2 and 1825 Unit 3) with a glaring focus on (1825-style) portfolio management and timing (owning the right shares at the right times) rather than 1830-style market manipulation. Spiritually, and yes the parentage is this complex, Baltimore & Ohio is the direct descendant of Lokomotive Werks1 with all of that game’s extra-ordinary attention to exacting cashflow, turn order, and timing – just carried forward into a larger and less relenting game2. Of the three, Lokomotive Werks has the dominant genes, shortly followed by 1825.
The game itself consists of stock rounds alternating with a pair of operating rounds. Initially 6 companies are available (B&O, B&M, C&O, NYC, NYNH&H & PRR). Later in the game 4 more companies become available (Erie, IC, Nickel Plate & Wabash). During stock rounds players acquire shares and manipulate the stock market. During operating rounds companies operate and may generate dividends for their shareholders. The game ends at the end of a set of operating rounds in which the highest level train is purchased (common), or when a share price reaches $375 (unlikely). The winner is the player with the largest net worth (portfolio value plus cash). There are few surprises here.
The rest of the model model is mostly familiar but does have surprises:
The board is rife with layers of short and long (timing) races. The number of companies allowed to connect to a given city is equal to the size of the largest train purchased by any company, thus there are races to get to more desirable cities first, locking other companies out. As city-capacity increases immediately when a new level of train is bought (and track is built after train purchasing), there are also races to be in position to buy the next size train and then immediately fill the newly accessible more-valuable cities. There are also races for special locations on the board with dividend-increasing coal tokens. As companies operate in descending order of stock value, stock rounds easily become positional dances attempting to force advantageous relative operating orders for specific companies so as to get them the good cities, good trains, good coal tokens etc4 before some other company does5.
Similarly, as there is such an advantage to being marginally lower in cash at the start of a stock round (to get first dibs on the best shares), there is often a muscular struggle in the operating rounds to run companies to pay as much as possible while having the controlling player end up with $1 less than the other players so as to secure the better turn order in the upcoming stock round.
This latter turn-order positioning is made more complex by the difficulty of increasing company stock values. There is a strong incentive to run companies for less than their maximum dividends so as to ensure stock-price increases by reserving future dividend increases by counting not-as-good cities for a dividend and then swapping in better cities in future dividends6. Getting the dividend sub-reporting for continued stock-value increases combined with maximising personal cash while also securing good turn order positioning can be difficult.
Those are not the only timing layers. There are yet more at different layers and levels, all open to inspection and manipulation. One trick is to hide cash in increased share value which would otherwise affect the player’s turn order. As companies are incrementally capitalised as their shares are bought, and all shares sell for the current stock value, there is not only a race for good operating order, but for various combinations of good turn order positions, operating order positions, good board positions/access, etc. For instance, the right new company floated at the right time, with the right par and thus the right capitalisation, and thus the right operating order (even after player-market assault), can pay great dividends while preserving the player’s turn order position, and be ripe to be dumped immediately in the next stock round, capitalising either buying all the best shares or floating a new company with the right par and the…etc.
As another example, there are also timing games that can be played with trains. In one of our games the NYNH&H, a very small company that can only reach 5 cities, already owned two 3-trains and had enough money in its treasury to buy an additional 5-train. Of course that gave it a total train capacity of 11 when it only connected 5 cities, but no matter. It then withheld its dividends and in the next operating round sold its 5-train to the bank7 and used that money along with its remaining treasury to buy the last 5-train, thus selling a 5-train to buy a 5-train and accelerating the end of the game while also leaving an opponent’s company unable to afford the larger train it needed and thus forcing it to withhold dividends yet again. Similar little timing games around the trains exist through-out the game.
All the little races and plethora of timing games, with every detail counting, sum to a larger fight to control the pace of the game and thus the length of the game. However rather than game-length being the defining centre of the game as it is in Wabash Cannonball, it is more an emergent and less directly-controlled property formed by the amalgam of all the little races. Due to capital concentration, ability to control the game’s development speed and thus length with lower player counts is greatly reduced. For the same reasons, the importance of game-length control, and the ability to affect it, also tends to increase as player-count increases.
Baltimore & Ohio scales across player counts similarly to the 18xx. As player-count decreases, control increases and the timing games may be played with ever-increasing finesse. As player count increases, capital is diluted across players, and control not only decreases but shared-incentives becomes more important and a whole new layer of emergently collusive timing games become possible. At the higher player counts the patterns start to stylistically resemble 6-player 1830’s, and at the lower player-counts, to likewise resemble 3-player 1830, complete with not only the different pacings, but the different values of different companies at the different player counts. The result is that 3 players plays very differently from 4 players, which in turn plays very differently from 5 players (I’ve not tried 6 players yet).
Expect your first session of Baltimore & Ohio to take between 4 and 5 hours, possibly a little more. With experience that play-time can be shortened down to around 150 minutes, but it will require both skill and discipline as with that increased skill comes greater ability to predict, control and thus play with the many many layers of timing in the game, pushing the game back up toward 4-5 hours. Perhaps surprisingly it is easier to push play-time down with increased player-counts, as with more players timing-control also decreases, making a great many of the more subtle and time-consuming timing games unviable.
I’d never expected to describe Lokomotive Werks as more relenting! ↩
As in most of the 18xx, 3-trains are the best trains in the game. ↩
Most of our games have spent more time in stock rounds than operating rounds. ↩
Destroying stock values all the while! ↩
This is considerably easier with some companies than others. ↩
Companies may sell their trains to the bank (and out of the game) for a marginal value. ↩
The following python script calculates the probabilities of a given cube on a row being produced by the end of a given round in a game of Age of Steam:
The results:
Players: 3
Round 1: Row 1 - 0.421296 Row 2 - 0.074074 Row 3 - 0.004630
Round 2: Row 1 - 0.665102 Row 2 - 0.263224 Row 3 - 0.062286
Round 3: Row 1 - 0.806193 Row 2 - 0.457341 Row 3 - 0.178260
Round 4: Row 1 - 0.887843 Row 2 - 0.618667 Row 3 - 0.322574
Round 5: Row 1 - 0.935095 Row 2 - 0.740378 Row 3 - 0.467775
Round 6: Row 1 - 0.962439 Row 2 - 0.827219 Row 3 - 0.597346
Round 7: Row 1 - 0.978263 Row 2 - 0.886969 Row 3 - 0.704381
Round 8: Row 1 - 0.987421 Row 2 - 0.927041 Row 3 - 0.788168
Round 9: Row 1 - 0.992720 Row 2 - 0.953411 Row 3 - 0.851205
Players: 4
Round 1: Row 1 - 0.517747 Row 2 - 0.131944 Row 3 - 0.016204
Round 2: Row 1 - 0.767432 Row 2 - 0.395323 Row 3 - 0.134847
Round 3: Row 1 - 0.887843 Row 2 - 0.618667 Row 3 - 0.322574
Round 4: Row 1 - 0.945912 Row 2 - 0.772831 Row 3 - 0.513209
Round 5: Row 1 - 0.973916 Row 2 - 0.869580 Row 3 - 0.671341
Round 6: Row 1 - 0.987421 Row 2 - 0.927041 Row 3 - 0.788168
Round 7: Row 1 - 0.993934 Row 2 - 0.959962 Row 3 - 0.868240
Players: 5
Round 1: Row 1 - 0.598122 Row 2 - 0.196245 Row 3 - 0.035494
Round 2: Row 1 - 0.838494 Row 2 - 0.515483 Row 3 - 0.224773
Round 3: Row 1 - 0.935095 Row 2 - 0.740378 Row 3 - 0.467775
Round 4: Row 1 - 0.973916 Row 2 - 0.869580 Row 3 - 0.671341
Round 5: Row 1 - 0.989517 Row 2 - 0.937104 Row 3 - 0.811313
Round 6: Row 1 - 0.995787 Row 2 - 0.970511 Row 3 - 0.897210
Players: 6
Round 1: Row 1 - 0.665102 Row 2 - 0.263224 Row 3 - 0.062286
Round 2: Row 1 - 0.887843 Row 2 - 0.618667 Row 3 - 0.322574
Round 3: Row 1 - 0.962439 Row 2 - 0.827219 Row 3 - 0.597346
Round 4: Row 1 - 0.987421 Row 2 - 0.927041 Row 3 - 0.788168
Round 5: Row 1 - 0.995787 Row 2 - 0.970511 Row 3 - 0.897210
No accommodations have been made for maps with different numbers of rounds per player count, or the insta-production rules used on most of my maps. Enjoy.