Pete's Hand Crafted Classic NCAA Football Teams for the Fourth Street Software Football Game

Excel Utility Screenshot

Excel Screenshot-click here to enlarge

Stacks Screenshot

Stacks-click here to enlarge

Stacks_pc Screenshot

Stacks_pc-click here to enlarge

Introduction

The genesis of this project can be traced to the mid 1970’s when a friend first received SI’s College football game marketed by Avalon Hill Game Company. This game was later renamed, Bowl Bound. My friends and I played countless games of Bowl Bound and it’s companion Paydirt. Years later, as the early 1990’s gave us the PC, my yearnings for a PC version of Bowl Bound increased. However, the choices for a good college based PC game have been very slim. I have been looking for a PC game that combined an open game engine with creatable/editable players to fill the gap for years. Games such as Micro League Sports Assoc., Lance Hafner’s 3in1, Action PC, and S-O-M have all failed on at least one test. Although it is a game tailored for Pro Football, 4th Street Software’s game has the most promise. Although many of the initial teams were selected from Team Set 1 of Bowl Bound, this project is not an attempt to translate the Bowl Bound game into 4th Street’s product. Some mathematical studies of the Bowl Bound team charts have been done, however. One drawback to the design of the Bowl Bound charts, is that certain plays are just never going to get called (Screens mostly) and some are just going to get overused (Draws mostly). This project is keenly aware of balancing the play selection and attempting to deliver the “flavor” of the teams first and players second. Strat-O-Matic is a leader in these types of games and was surely the first choice, but the lack of a player creator has disallowed its use in pursuit of this project. Furthermore, SOM has some issues with play balance due to the card design of the “right/wrong” system and the corresponding unbalanced strength of passes over runs. 4th Street Software’s game is essentially and simply a matchup of an offensive player and a defensive player. Each play in a formation has 20 chances to call upon an offensive player (the line might be 5, the QB 5, the RB 5, the blocking back 2, etc) and call upon a defensive zone. If the defensive zone is empty, then the offensive player wins the matchup and consults his play results. If not, then the better player has a better chance of influencing the outcome. Usually it is 50-50 (like SOM) but can be 60-40, 70-30, etc.

Research

I’m fortunate to be in close proximity to the LA Amateur Athletic Foundation’s Sports Library, where a myriad of archived information is available. Furthermore, much info is available on the internet and many times the universities have been kind with providing info. Countless books concerning figures of the era have been read. Letterwinner listings, as well as, TV listings were utilized to flush out many of the rosters. Fellow gamers such as Fred Bobberts, and John “Bama Rox” are also greatly appreciated for their contributions. Phil Key, an Arkansas fan, was also instrumental. The NCAA record books were used to obtain the total and average stats for each season. The project was divided into groupings of three-year seasons upon observation of the statistical trends and the need to limit the amount of test “seed” leagues. Therefore, a team from the 1967 season was compared to the three-year stats from the 1965,1966,1967 grouping. Additionally, all teams have had their boxscores compiled for supplemental statistical info. If a team had finished in the NCAA top ten in certain categories, then those stats could be utilized also. Often times, many of the team stats did not include bowl games or the individual totals. If this information has not been deciphered, it has been estimated. Many of the team and individual stats were obtained from Strat-O-Matic’s mid 70’s college football game and estimates from Hafner’s college game. Furthermore, Hafner’s game has many estimated stats that are of use for an overall team statistical flavor. On the player cards that have been created in MS Excel, the actual stats are listed. If an estimation was needed, that figure will be underlined. Furthermore, the projected stats are based on the team tallying 1000 plays from scrimmage, which includes runs, sacks and pass attempts. Please note: the NCAA tallies a quarterback’s scrambles and sacks to the rushing totals.

Testing

Testing is the absolute most important part to me in this project and the reason I did not use Strat-O-Matic. There simply is no way to run enough scenarios to test the realism/accuracy of the teams using the SOM system. A team’s strength of schedule will be an important part of the testing. Each team’s won/loss record and points scored and points allowed have been tabulated. Additionally, all of their opponent’s records have also been tabulated for use in the team creation/play-test phase of the project. This, it is hoped, will add to the accuracy of the team based on their strength of schedule and quality of their opponents as well as their opponents, opponents. At last count, the seed league took 79 separate subsets of edits and thousands of tests to yield the correct NCAA stats. The individual teams were then tested against a selection of teams from the seed league that best matched their strength of schedule. The player ratings are largely anecdotal from various readings and listings. For the most part, the team accuracy was first and foremost while player accuracy was secondary. However, certain skill position players have had a great deal of effort placed on their statistical accuracy. 300-1800 game seasons were run numerous times to fine-tune the ratings and stats. This may be reduced in the future to provide a quicker turnaround.

Process

The 1970 NFL season of 4th Street Software’s PC Pro Football game served as the seed season for the project. The player/card files were analyzed to decipher the design of the game. Some liberties were taken with the design in order to reflect a more accurate college product. The major departure from the original design is the penalty system, which by design forces higher rated players to commit more penalties. In some instances, lower and higher ratings are used on certain players to address such issues as turnovers and penalties and even injuries. The initial seasons of the project are the 1965, 1966 and 1967 seasons. The 1970 NFL seed file was edited for both coaching and player results until 5 autoplayed seasons resulted in a near match of the targeted NCAA stats. For example, the Pros had about a 5% higher completion percentage, so numerous edits were required to drop that down to NCAA levels. The auto-played team stats from this modified file were recorded and each team within can serve as a possible opponent in the playtest phase for the individual teams of the project. Play testing involved creating a schedule of opponents that best matched the winning percentage and level of points scored and allowed. After the rosters were created, numerous play tests were run to check for statistical accuracy of both the coaching tendencies and the statistical outcomes. Players and coaches were continually edited until the stats showed near perfect accuracy.

A Final Word on Accuracy

During the course of testing, it became apparent that certain teams would not achieve their won-loss records or their points for and allowed based on their team stats. Most of the players, that had significant contributions, have been carded to achieve accurate results, but in the end, a balance of team and player “flavor” was realized. If the gamer uses realistic tendencies and strategies, then the results will be uncompromisingly accurate, far more accurate than any other game has obtained. I say this confidently because all games produced for commerce have to protect the bottom line, and therefore cannot run the number of tests needed to ensure the best final product. It is simply not cost effective for them. I do not have these constraints.

Closing

I hope any and all will find great enjoyment with this project and feel free to give constructive feedback. Finally, special thanks to Bryan Aldrich, whose unique and simple game made this project possible.

Pete Emrich 6/11/2004