1. Sports Scheduling An Assessment of Various Approaches to Solving the n-Round Robin Tournament Noren De La Rosa Mallory Ratajewski

2. Introduction Scheduling tournaments in a sports league Focusing on Round Robin Tournaments – Single Round Robin Tournament (SRRT): each team meets every other team once – Double Round Robin Tournament (DRRT): each team meets every other team twice Economic impact: quality of schedule affects the revenue of the sports team

3. What is the best schedule? Home-away pattern – Balance between number of home and away games – Prefer alternating home away pattern Any deviation is considered a break Minimizing Distance Travelled Other factors: – Availability of stadium – Preferences to increase revenues – Top team and bottom team constraints – Geographical constraints

4. Main Considerations Minimizing number of breaks – Used when teams return home after each away game instead of travelling to another away game – Alternating patterns usually preferred – Considers the fans – Ensures regular earnings from home games Minimizing distance travelled – Used when teams travel to multiple away games without returning home – Huge savings can be obtained

5. Minimizing Number of Breaks Graph theoretical approaches – 1-factorization: partitioning the games into n-1 slots, each node will be incident to exactly one edge in each 1-factor Practical applications: constrained minimum break problem – Decomposition approach – Combinatorial design, IP, enumeration techniques – See Nemhauser and Trick – Constraint programming approaches; see Henz

6. Minimizing Distance Travelled Similar to a travelling salesman problem Problem is too large to solve using IP in a reasonable amount of time Various heuristics used instead The travelling tournament problem proposed by Easton, Nemhauser, and Trick

7. The Travelling Tournament Problem Double round robin tournament to be played by n teams over (2n-2) periods or weeks, where each team plays every period Objective: minimize distance travelled by each team Additional Constraints: – Maximum “road trip” of three games – Maximum “home stand” of three games – Repeater rule

8. TTP Solution Approaches What Methods Can We Use to Solve the TTP? – Integer programming – Constraint programming – Hybrid approaches involving heuristics

9. A Tiling Approach for Fast Implementation of the TTP Model the road trips as “tiles” Each tile will contain “blocks”, which represent individual games – (i.e. – a road trip with 3 opponents is considered as one tile, with 3 blocks) Three phase approach: – Phase I – Tile Creation – Phase II – Tile Placement – Phase III – Block Placement

10. TTP Tiling Algorithm Create a set of tiles for each team. These tiles are placed in a grid of n rows representing teams and (2n-2) columns representing weeks As tiles are placed, other cells of the grid are filled in to keep the schedule consistent When there are no tiles remaining, they are broken into their component blocks If not all the blocks can be placed  block placement is backtracked to find additional solutions If all blocks can be placed  a solution is generated

11. TTP Tiling Algorithm Scheduling grid and tiles for Team 1 & Team 2

12. A Demonstrative Example PrincetonHarvardYaleDartmouthBrownColumbia Princeton06356785144 Harvard6307299127 Yale5670328522 Dartmouth782932011534 Brown519185115085 Columbia44272234850

13. Create Tiles Phase I: Tile Creation Find the MST from Prim’s algorithm C P B Y H D Y H D B P

14. Phase II: Tile Placement 12345678910 Princeton Harvard Yale Dartmouth Brown ColumbiaYHD PB

15. Phase III: Block Placement All remaining unplaced tiles are broken into individual blocks These blocks are placed into the scheduling grid Backtracking is used when blocks do not lead to a solution

16. Conclusions Sports scheduling has huge economic implications for the sports industry Optimal solutions that consider the many constraints are time consuming Hybrid solutions involving heuristics are close to optimality and require less time Many opportunities for further research, particularly involving hybrid approaches

17. References A. Bar-Noy, D. Moody, A Tiling Approach for Fast Implementation of the Travelling Tournament Problem, PATAT (2006) 351-358. K. Easton, G. Nemhauser, M. Trick, Solving the Travelling Tournament Problem: A Combined Integer Programming and Constraint Programming Approach, PATAT (2002) 100-109. M. Henz, T. Muller, S. Thiel, Global Constraints for Round Robin Tournament Scheduling, European Journal of Operational Research 153 (2004) 92-101. R. V. Rasmussen, M. A. Trick, Round Robin Scheduling – A Survey, European Journal of Operational Research 188 (2008) 617-636.