Simulating Partial Round-Robin Tournaments
Tom Keith, 2013
When running a partial round-robin tournament, what is the best way to match up players in each round? I created computer simulation to find out.

Partial Round-Robin Tournaments

A popular format for backgammon tournaments is the partial round-robin.

A full round-robin sees every player play every other player in the tournament. If there are n players in a tournament, a full round-robin needs n − 1 rounds to complete. This many rounds is not practical if you have more than about 10 players, so many tournaments opt to use some sort of "partial" round-robin.

A partial round-robin might have anywhere from 5 to 15 rounds, depending on the time available.

Termination Methods

There are several methods you can use shorten a round-robin tournament. We will look at two:

A truncated round-robin is good when you want to rank all participants from first to last. This method also maximizes the amount of play for everyone.

An elimination round-robin is good when the primary goal is to find an overall winner of the tournament, perhaps to award a trophy or cash prize. The advantage of this method is that only players who still have a chance of winning continue to play. (There are no "meaningless" matches.)

Matching Up Players

When running a partial round-robin, an important question is how to match up players in each round — who plays who? There are two common pairing methods:

Tournament Effectiveness

Is one pairing method better than the other?

To answer that question we first have to figure out what we mean by "better." One definition of better is how good the tournament is at separating the wheat from the chaff.

In my compter simulation each player has a different skill level. One player is the strongest and, on average, will win more often than any other player. There is a lot of luck in backgammon, and just because you are the strongest player doesn't mean you will win the tournament. But, over the long term, you should win tournaments more often than weaker players. And that's what we mean by tournament effectiveness.

If there are n players in the tournament, the average player wins about 1/n of the time. You would expect the strongest player to do much better than this. How much better depends partly on how the tournament is set up. If the strongest player wins more often under one format than he does under another format, we say that the first tournament format is more "effective."

A Simulation

I wrote a computer simulation to find out which pairing method was more effective. The simulation works as follows.

There are 64 imaginary players, each with a different skill level. To implement the different skill levels, I ranked the players from 1 to 64. Let D be the difference in rank between two players. When two players play each other, the higher ranked player wins with a probability of 0.50 + (0.0025 × D) and the lower ranked player wins with probability of 0.50 − (0.0025 × D).

So, for example, suppose Player #1 (the best player in the tournament) plays Player #64 (the worst player). The difference in rank is D = 63. The favorite in this match-up will win 50 + (0.25 × D) percent of the time, or 65.75%. The underdog will win only 34.25% of the time.

I ran the tournaments using various setups. For each setup, I ran the simulation 1,000,000 times and tabulated how often each player won. In particular, I wanted to see how often Player #1 won to determine how effective that tournament setup was.

Swiss versus Random Pairing in a Truncated Round-Robin

In a truncated round-robin tournament, nobody gets eliminated; everyone continues to play for k rounds. The winner of the tournament is the player with the most wins. (If two or more players are tied, the winner is chosen at random among the tied players. At least that's how it worked in my simulation; in a real tournament you might have some kind of tie-breaker.)

I simulated a truncated round-robin tournament with k = 6, 9, 12, and 15 rounds. Each tournament was run twice — once with players paired at random, and once with players paired using Swiss pairing. The tournament was run 1,000,000 times and results were tabulated to see how often each player #1 through #64 ended up the tournament winner.

An average player should expect to win the tournament 1/64 of the time, or about 1.56%. Player #1 (the strongest player) should do substantially better than this. And Player #64 (the weakest player) should do substantially worse.

The tables below summarize the results. From the tables, you can see that in a 6-round tournament with random pairing, Player #1 wins about 3.047% of the time (almost twice what you'd expect for an average player). In a 6-round tournament with Swiss pairing, Player #1 does even better. He wins 3.286% of the time. This is a significant difference. Strong players are definitely favored by Swiss-style pairing.

In a truncated round-robin tournament,
top players do better when Swiss pairing is used.

The color coding in the tables shows which pairing style you'd prefer based on how high ranked you are as a player. Green is the higher probability of winning. In a 6-round tournament, the top 23 players do better with Swiss pairing than they do with random pairing. (The fact that the colors alternate back and forth between Players #23 and #26 is simply a reflection of the small random variations you'd expect in the simulation results. If I had done more simulations, these variations could have been reduced.)

Longer tournaments favor the better players too. With random pairing, the top player won 3.047% of the time in a 6-round tournament, 3.5% of the time in a 9-round tournament, 3.877% of the time in a 12-round touranament, and 4.235% of the time in a 15-round tournament. With Swiss pairing, the top player won 3.286% of the time in a 6-round tournament, 3.673% of the time in a 9-round tournament, 4.063% of the time in a 12-round tournament, and 4.424% of the time in a 15-round tournament.

As the top player wins more, it leaves less equity for the other players. In a 6-round tournament, the top 28 players showed positive equity (won more than 1/64 = .015625 of the time). In a 9-round tournament, only the top 27 players showed positive equity. In a 12-round tournament, only the top 26 players showed positive equity. And in a 15-round tournament, only the top 25 players showed positive equity.

6 Rounds

Plr P(win)
Random Swiss
1 .03047 .03286
2 .02963 .03167
3 .02923 .03109
4 .02809 .03030
5 .02763 .02932
6 .02719 .02872
7 .02632 .02784
8 .02593 .02717
9 .02522 .02691
10 .02468 .02573
11 .02404 .02540
12 .02334 .02463
13 .02310 .02388
14 .02249 .02326
15 .02178 .02247
16 .02142 .02204
17 .02066 .02164
18 .02039 .02098
19 .01990 .02077
20 .01923 .01991
21 .01906 .01916
22 .01850 .01869
23 .01810 .01831
24 .01778 .01763
25 .01717 .01739
26 .01689 .01662
27 .01657 .01625
28 .01593 .01573
29 .01559 .01528
30 .01508 .01499
31 .01482 .01441
32 .01425 .01422
33 .01402 .01337
34 .01368 .01317
35 .01361 .01292
36 .01317 .01253
37 .01270 .01212
38 .01255 .01174
39 .01227 .01124
40 .01169 .01105
41 .01157 .01081
42 .01123 .01040
43 .01082 .01018
44 .01080 .01010
45 .01023 .00956
46 .01014 .00928
47 .00987 .00904
48 .00964 .00878
49 .00934 .00838
50 .00901 .00836
51 .00886 .00805
52 .00867 .00775
53 .00829 .00759
54 .00803 .00736
55 .00784 .00710
56 .00753 .00679
57 .00751 .00654
58 .00717 .00662
59 .00703 .00608
60 .00691 .00595
61 .00661 .00575
62 .00634 .00554
63 .00629 .00537
64 .00609 .00521
9 Rounds

Plr P(win)
Random Swiss
1 .03500 .03673
2 .03366 .03584
3 .03301 .03497
4 .03185 .03318
5 .03095 .03222
6 .03026 .03143
7 .02931 .03033
8 .02849 .02966
9 .02772 .02903
10 .02697 .02782
11 .02662 .02703
12 .02533 .02609
13 .02450 .02568
14 .02396 .02435
15 .02311 .02367
16 .02251 .02286
17 .02186 .02243
18 .02110 .02161
19 .02050 .02102
20 .02005 .01983
21 .01948 .01936
22 .01903 .01864
23 .01824 .01851
24 .01748 .01774
25 .01722 .01711
26 .01681 .01648
27 .01612 .01613
28 .01557 .01536
29 .01533 .01461
30 .01454 .01450
31 .01430 .01398
32 .01374 .01350
33 .01346 .01274
34 .01291 .01257
35 .01261 .01211
36 .01202 .01157
37 .01177 .01148
38 .01130 .01089
39 .01105 .01045
40 .01050 .01009
41 .01041 .00993
42 .00999 .00953
43 .00938 .00906
44 .00930 .00872
45 .00894 .00828
46 .00852 .00811
47 .00835 .00793
48 .00810 .00752
49 .00785 .00719
50 .00760 .00707
51 .00735 .00677
52 .00708 .00640
53 .00674 .00619
54 .00649 .00585
55 .00634 .00564
56 .00602 .00546
57 .00585 .00510
58 .00549 .00514
59 .00551 .00492
60 .00529 .00471
61 .00512 .00459
62 .00485 .00422
63 .00476 .00412
64 .00444 .00398
12 Rounds

Plr P(win)
Random Swiss
1 .03877 .04063
2 .03750 .03918
3 .03606 .03800
4 .03490 .03665
5 .03420 .03549
6 .03307 .03418
7 .03165 .03283
8 .03079 .03192
9 .02991 .03075
10 .02843 .02971
11 .02777 .02846
12 .02710 .02749
13 .02603 .02660
14 .02474 .02568
15 .02462 .02490
16 .02354 .02400
17 .02256 .02275
18 .02180 .02188
19 .02094 .02145
20 .02009 .02060
21 .01928 .01994
22 .01903 .01900
23 .01820 .01813
24 .01766 .01759
25 .01701 .01691
26 .01629 .01609
27 .01561 .01565
28 .01534 .01495
29 .01463 .01441
30 .01426 .01381
31 .01371 .01317
32 .01301 .01264
33 .01269 .01221
34 .01192 .01148
35 .01165 .01143
36 .01127 .01076
37 .01081 .01034
38 .01039 .00994
39 .01001 .00937
40 .00964 .00899
41 .00927 .00869
42 .00867 .00828
43 .00851 .00805
44 .00839 .00759
45 .00770 .00726
46 .00745 .00691
47 .00725 .00661
48 .00701 .00647
49 .00670 .00608
50 .00654 .00581
51 .00617 .00556
52 .00587 .00541
53 .00549 .00518
54 .00543 .00471
55 .00515 .00443
56 .00490 .00444
57 .00483 .00418
58 .00455 .00401
59 .00426 .00376
60 .00415 .00370
61 .00406 .00339
62 .00373 .00340
63 .00357 .00310
64 .00348 .00299
15 Rounds

Plr P(win)
Random Swiss
1 .04235 .04424
2 .04039 .04279
3 .03914 .04118
4 .03784 .03925
5 .03648 .03803
6 .03502 .03652
7 .03399 .03542
8 .03262 .03364
9 .03160 .03254
10 .02987 .03131
11 .02899 .02969
12 .02798 .02905
13 .02700 .02740
14 .02595 .02640
15 .02505 .02550
16 .02393 .02428
17 .02313 .02322
18 .02227 .02208
19 .02124 .02129
20 .02050 .02062
21 .01983 .01975
22 .01873 .01901
23 .01807 .01802
24 .01751 .01733
25 .01668 .01633
26 .01619 .01561
27 .01550 .01496
28 .01474 .01446
29 .01397 .01371
30 .01355 .01317
31 .01290 .01255
32 .01255 .01200
33 .01182 .01143
34 .01149 .01095
35 .01083 .01035
36 .01051 .00995
37 .00994 .00933
38 .00973 .00892
39 .00902 .00858
40 .00875 .00815
41 .00853 .00785
42 .00800 .00751
43 .00772 .00712
44 .00719 .00679
45 .00697 .00655
46 .00657 .00607
47 .00624 .00577
48 .00614 .00556
49 .00575 .00518
50 .00549 .00485
51 .00518 .00480
52 .00506 .00446
53 .00472 .00420
54 .00448 .00396
55 .00437 .00378
56 .00400 .00360
57 .00385 .00347
58 .00373 .00325
59 .00347 .00316
60 .00333 .00295
61 .00307 .00272
62 .00299 .00256
63 .00286 .00245
64 .00263 .00234

Swiss versus Random Pairing in an Elimination Round-Robin

In an elimination round-robin tournament, players continue to play until they have lost a specified number of matches. For example, players might continue playing until they have lost three times.

I simulated an elimination round-robin tournament with 1, 2, 3, and 4 losses. Each tournament was run twice — once with players matched at random, and once with players matched using the Swiss pairing. The tournament was run 1,000,000 times and the results tabulated to see how often each player #1 through #64 was the last to survive. The tables below summarize the results.

A single knockout round-robin tournament is the same as straight elimination tournament and always takes 6 rounds. A double knockout round-robin takes about 9.862 rounds to find a winner. A triple knockout round-robin takes about 12.935 rounds. And a quadruple knockout round-robin takes about 15.844 rounds.

The surprising thing about these tables is that there is no advantage to tournament effectiveness of using Swiss pairing rather than random pairing. The strongest players do equally well with either system.

In an elimination round-robin tournament,
there is no difference in tournament effectiveness
between Swiss pairing and random pairing.

There is, however, one advantage to Swiss pairing. The average length of the tournament is slightly less with Swiss than with random pairing. For example, in a 3-loss tournament, random pairing takes 12.94 rounds on average to finish and Swiss pairing takes only 12.63 rounds on average to finish.

But as a practical matter this difference is not very significant when you consider the extra work required to run a Swiss tournament. In fact it's likely the time saved by doing a simple random draw outweighs the time savings for Swiss suggested by the simulation.

1 Loss

(6.000 rounds rand)
(6.000 rounds Swiss)

Plr P(win)
Random Swiss
1 .03276 .03264
2 .03176 .03163
3 .03102 .03098
4 .03027 .03006
5 .02947 .02965
6 .02862 .02880
7 .02789 .02791
8 .02740 .02704
9 .02654 .02650
10 .02590 .02611
11 .02532 .02514
12 .02450 .02455
13 .02405 .02381
14 .02319 .02331
15 .02272 .02248
16 .02207 .02194
17 .02137 .02182
18 .02060 .02099
19 .02057 .02022
20 .01990 .01970
21 .01927 .01920
22 .01883 .01879
23 .01811 .01816
24 .01772 .01776
25 .01737 .01727
26 .01682 .01675
27 .01615 .01632
28 .01582 .01597
29 .01538 .01561
30 .01473 .01505
31 .01423 .01452
32 .01420 .01400
33 .01381 .01356
34 .01344 .01341
35 .01308 .01290
36 .01254 .01251
37 .01223 .01221
38 .01184 .01190
39 .01154 .01149
40 .01097 .01117
41 .01062 .01069
42 .01047 .01037
43 .01008 .01035
44 .00971 .00991
45 .00980 .00953
46 .00933 .00934
47 .00918 .00915
48 .00870 .00873
49 .00839 .00854
50 .00838 .00836
51 .00800 .00797
52 .00780 .00778
53 .00743 .00742
54 .00735 .00720
55 .00705 .00700
56 .00673 .00690
57 .00666 .00659
58 .00633 .00644
59 .00614 .00608
60 .00592 .00590
61 .00571 .00572
62 .00564 .00561
63 .00535 .00535
64 .00523 .00525
2 Losses

(9.862 rounds rand)
(9.841 rounds Swiss)

Plr P(win)
Random Swiss
1 .03732 .03685
2 .03591 .03563
3 .03521 .03447
4 .03383 .03385
5 .03307 .03286
6 .03199 .03140
7 .03069 .03022
8 .03008 .02982
9 .02896 .02872
10 .02786 .02798
11 .02740 .02686
12 .02646 .02633
13 .02567 .02547
14 .02456 .02422
15 .02413 .02361
16 .02326 .02302
17 .02216 .02246
18 .02162 .02162
19 .02081 .02076
20 .02013 .01999
21 .01939 .01945
22 .01883 .01877
23 .01817 .01814
24 .01776 .01765
25 .01675 .01698
26 .01648 .01658
27 .01577 .01604
28 .01534 .01525
29 .01488 .01481
30 .01417 .01437
31 .01391 .01368
32 .01325 .01338
33 .01291 .01308
34 .01237 .01244
35 .01194 .01194
36 .01136 .01165
37 .01104 .01139
38 .01069 .01090
39 .01027 .01050
40 .01015 .01003
41 .00940 .00974
42 .00938 .00941
43 .00896 .00919
44 .00861 .00864
45 .00837 .00844
46 .00799 .00809
47 .00768 .00775
48 .00735 .00742
49 .00713 .00725
50 .00700 .00697
51 .00659 .00661
52 .00637 .00670
53 .00596 .00630
54 .00575 .00602
55 .00556 .00574
56 .00539 .00556
57 .00524 .00536
58 .00498 .00517
59 .00467 .00489
60 .00460 .00476
61 .00440 .00445
62 .00427 .00422
63 .00400 .00409
64 .00380 .00404
3 Losses

(12.935 rounds rand)
(12.634 rounds Swiss)

Plr P(win)
Random Swiss
1 .04083 .04163
2 .03988 .04020
3 .03824 .03867
4 .03693 .03679
5 .03565 .03601
6 .03422 .03476
7 .03317 .03324
8 .03156 .03222
9 .03075 .03101
10 .02932 .02975
11 .02871 .02850
12 .02782 .02798
13 .02654 .02667
14 .02559 .02572
15 .02481 .02481
16 .02370 .02363
17 .02298 .02291
18 .02210 .02223
19 .02137 .02134
20 .02043 .02048
21 .01972 .01957
22 .01885 .01871
23 .01800 .01802
24 .01741 .01746
25 .01686 .01656
26 .01613 .01612
27 .01576 .01532
28 .01497 .01461
29 .01431 .01415
30 .01395 .01362
31 .01333 .01339
32 .01260 .01249
33 .01217 .01206
34 .01163 .01146
35 .01094 .01115
36 .01082 .01040
37 .01030 .01029
38 .00980 .00950
39 .00950 .00932
40 .00909 .00895
41 .00867 .00861
42 .00829 .00835
43 .00799 .00777
44 .00764 .00766
45 .00707 .00719
46 .00691 .00698
47 .00675 .00658
48 .00642 .00637
49 .00592 .00594
50 .00563 .00579
51 .00560 .00557
52 .00528 .00521
53 .00512 .00498
54 .00482 .00476
55 .00457 .00440
56 .00434 .00432
57 .00409 .00397
58 .00402 .00399
59 .00382 .00383
60 .00364 .00344
61 .00339 .00347
62 .00319 .00314
63 .00312 .00302
64 .00301 .00294
4 Losses

(15.844 rounds rand)
(15.568 rounds Swiss)

Plr P(win)
Random Swiss
1 .04422 .04437
2 .04259 .04253
3 .04108 .04134
4 .03901 .03947
5 .03794 .03798
6 .03632 .03629
7 .03508 .03480
8 .03356 .03366
9 .03211 .03224
10 .03115 .03100
11 .02988 .03009
12 .02892 .02857
13 .02743 .02749
14 .02641 .02657
15 .02498 .02548
16 .02406 .02410
17 .02338 .02318
18 .02242 .02235
19 .02151 .02115
20 .02033 .02038
21 .01976 .01942
22 .01868 .01862
23 .01778 .01811
24 .01718 .01740
25 .01637 .01645
26 .01594 .01561
27 .01503 .01487
28 .01429 .01439
29 .01376 .01372
30 .01314 .01318
31 .01281 .01258
32 .01211 .01216
33 .01157 .01150
34 .01092 .01082
35 .01057 .01055
36 .00996 .00993
37 .00966 .00972
38 .00912 .00907
39 .00866 .00863
40 .00837 .00819
41 .00789 .00797
42 .00755 .00750
43 .00708 .00702
44 .00680 .00678
45 .00640 .00643
46 .00613 .00605
47 .00595 .00583
48 .00552 .00550
49 .00526 .00529
50 .00497 .00489
51 .00469 .00493
52 .00448 .00449
53 .00421 .00438
54 .00402 .00409
55 .00399 .00388
56 .00365 .00370
57 .00348 .00343
58 .00327 .00337
59 .00317 .00305
60 .00297 .00297
61 .00291 .00282
62 .00264 .00276
63 .00254 .00254
64 .00237 .00236

Summary

In a truncated round-robin tournament, the strongest players do better when Swiss pairing is used.

In an elimination round-robin tournament, the strongest players do equally well regardless of whether random pairing or Swiss pairing is used.

More articles by Tom Keith

More articles on tournaments

Backgammon Galore