1949 AAFC Season

42 regular-season games · 4 playoff teams

Final

Champion

Cleveland Browns

4th Title

Last Title: 1948

Runner-Up

San Francisco 49ers

1st Appearance

Biggest Overachiever

New York Yankees

1.88 wins above expected

8 wins · 6.12 expected wins

Biggest Disappointment

Baltimore Colts (1st)

3.13 wins below expected

1 wins · 4.13 expected wins

Final Standings

Final regular season records. The vsSim column shows actual wins minus the simulation's mean wins - positive values indicate the team overachieved, negative values mean they underperformed.

#	Team	W	L	T	Pct	GB	PF	PA	PD	SimW	vsSim
1	New York Yankees Division	8	4	0	.667	-	196	206	-10	6.12	+1.88
2	Buffalo Bills (1st) Playoffs	5	5	2	.500	2	236	256	-20	5.75	+0.25
3	Baltimore Colts (1st)	1	11	0	.083	7	172	341	-169	4.13	-3.13

#	Team	W	L	T	Pct	GB	PF	PA	PD	SimW	vsSim
1	Cleveland Browns Division	9	1	2	.833	-	339	171	+168	9.78	+0.22
2	San Francisco 49ers Playoffs	9	3	0	.750	1	416	227	+189	8.89	+0.11
3	Chicago Hornets	4	8	0	.333	6	179	268	-89	2.29	+1.71
4	Los Angeles Dons	4	8	0	.333	6	253	322	-69	5.04	-1.04

Playoff Bracket

AAFC Playoffs

Division Round

Cleveland Browns 31

Buffalo Bills (1st) 21

Dec 4

San Francisco 49ers 17

New York Yankees 7

Dec 4

AAFC Championship Game

Cleveland Browns 21

San Francisco 49ers 7

Dec 11

Season Summary

Every team's regular season finish compared against the simulated win totals. Click on any column header to sort. Luck is the team's actual total minus the simulation's mean. Positive values indicate the team outperformed the expected total; negative values indicate the team was unluckier than expected. Percentile represents where their actual result fell in the simulated distribution.

Team	Conference	Elo	Actual	Avg. Wins	Luck	Percentile	Min	5th	Q1	Median	Q3	95th	Max
Cleveland Browns	West	1776	10	9.78	+0.22	94.31%	3	7	9	10	11	12	12
San Francisco 49ers	West	1711	9	8.89	+0.11	71.28%	2	6	8	9	10	11	12
New York Yankees	East	1515	8	6.12	+1.88	96.13%	0	3	5	6	7	8	12
Buffalo Bills (1st)	East	1497	6	5.75	+0.25	91.16%	0	3	4	5	6	8	11
Los Angeles Dons	West	1438	4	5.04	-1.04	44.40%	0	2	4	5	6	7	11
Baltimore Colts (1st)	East	1295	1	4.13	-3.13	4.40%	0	2	3	4	5	6	11
Chicago Hornets	West	1268	4	2.29	+1.71	96.27%	0	0	1	2	3	4	9

Head-to-Head

Cells show each team's record against each opponent with the expected wins from the simulation below Gold-tinted cells indicate the team beat the model's expectations by more than a half-win while navy-tinted cells indicate they fell short by more than a half-win. The first table covers within-division games while the second covers games against teams outside the division.

Beat expectations Fell short Within expectations

Within East

Team	(1st)	(1st)	Yankees
Baltimore Colts (1st)	—	1-1 (0.5 exp.)	0-2 (0.6 exp.)
Buffalo Bills (1st)	1-1 (1.4 exp.)	—	1-1 (0.8 exp.)
New York Yankees	2-0 (1.3 exp.)	1-1 (1.0 exp.)	—

East vs. Outside Teams

Team	Hornets	Browns	Dons	49ers
Baltimore Colts (1st)	0-2 (1.4 exp.)	0-2 (0.2 exp.)	0-2 (0.8 exp.)	0-2 (0.3 exp.)
Buffalo Bills (1st)	1-1 (1.5 exp.)	0-0-2 (0.3 exp.)	1-1 (1.0 exp.)	1-1 (0.4 exp.)
New York Yankees	2-0 (1.5 exp.)	0-2 (0.4 exp.)	2-0 (1.1 exp.)	1-1 (0.5 exp.)

Within West

Team	Hornets	Browns	Dons	49ers
Chicago Hornets	—	0-2 (0.1 exp.)	1-1 (0.5 exp.)	0-2 (0.2 exp.)
Cleveland Browns	2-0 (1.9 exp.)	—	2-0 (1.6 exp.)	1-1 (1.2 exp.)
Los Angeles Dons	1-1 (1.4 exp.)	0-2 (0.3 exp.)	—	0-2 (0.4 exp.)
San Francisco 49ers	2-0 (1.8 exp.)	1-1 (0.7 exp.)	2-0 (1.5 exp.)	—

West vs. Outside Teams

Team	(1st)	(1st)	Yankees
Chicago Hornets	2-0 (0.5 exp.)	1-1 (0.4 exp.)	0-2 (0.4 exp.)
Cleveland Browns	2-0 (1.7 exp.)	0-0-2 (1.6 exp.)	2-0 (1.5 exp.)
Los Angeles Dons	2-0 (1.0 exp.)	1-1 (0.9 exp.)	0-2 (0.8 exp.)
San Francisco 49ers	2-0 (1.6 exp.)	1-1 (1.5 exp.)	1-1 (1.5 exp.)

Scoreline Distribution

Cells represent the percentage of games that ended with a team's points in the row and its opponent's points in the column. Cells below the diagonal are wins (gold), and cells above are losses (blue). Totals along the edges show the marginal percentages for that row or column.

Win Loss Same range

View:

↓ Scored \| Allowed →	0–6	7–13	14–20	21–27	28–34	35–41	42+	Total
0–6	—	1.19%	2.38%	2.38%	1.19%	1.19%	—	8.33%
7–13	1.19%	4.76%	2.38%	1.19%	1.19%	1.19%	3.57%	15.48%
14–20	2.38%	2.38%	11.90%	2.38%	3.57%	2.38%	3.57%	28.57%
21–27	2.38%	1.19%	2.38%	4.76%	—	2.38%	1.19%	14.29%
28–34	1.19%	1.19%	3.57%	—	4.76%	1.19%	2.38%	14.29%
35–41	1.19%	1.19%	2.38%	2.38%	1.19%	—	—	8.33%
42+	—	3.57%	3.57%	1.19%	2.38%	—	—	10.71%
Total	8.33%	15.48%	28.57%	14.29%	14.29%	8.33%	10.71%	100%

Summary Statistics

	Scored	Allowed	Difference
Mean	21.32	21.32	+0.00
SD	13.35	13.35	19.89
CV	0.63	0.63	—
Max	61	61	+47
Min	0	0	-47

Games Played: 42

↓ Scored \| Allowed →	0–6	7–13	14–20	21–27	28–34	35–41	42+	Total
0–6	—	—	—	8.33%	—	—	—	8.33%
7–13	—	—	8.33%	8.33%	8.33%	8.33%	—	33.33%
14–20	—	—	—	8.33%	16.67%	8.33%	8.33%	41.67%
21–27	—	—	—	8.33%	—	—	—	8.33%
28–34	—	—	—	—	—	—	—	—
35–41	—	—	—	—	8.33%	—	—	8.33%
42+	—	—	—	—	—	—	—	—
Total	—	—	8.33%	33.33%	33.33%	16.67%	8.33%	100%

Baltimore Colts (1st) — Summary Statistics

	Scored	Allowed	Difference
Mean	14.33	28.42	-14.08
SD	8.89	8.95	11.11
CV	0.62	0.31	—
Max	35	49	+7
Min	0	17	-32

Games Played: 12

↓ Scored \| Allowed →	0–6	7–13	14–20	21–27	28–34	35–41	42+	Total
0–6	—	—	—	—	—	—	—	—
7–13	8.33%	8.33%	—	—	—	—	8.33%	25.00%
14–20	—	—	33.33%	—	—	—	—	33.33%
21–27	—	—	—	—	—	—	—	—
28–34	—	—	8.33%	—	8.33%	8.33%	8.33%	33.33%
35–41	—	—	8.33%	—	—	—	—	8.33%
42+	—	—	—	—	—	—	—	—
Total	8.33%	8.33%	50.00%	—	8.33%	8.33%	16.67%	100%

Buffalo Bills (1st) — Summary Statistics

	Scored	Allowed	Difference
Mean	19.67	21.33	-1.67
SD	10.03	14.82	16.46
CV	0.51	0.69	—
Max	38	51	+24
Min	7	0	-44

Games Played: 12

↓ Scored \| Allowed →	0–6	7–13	14–20	21–27	28–34	35–41	42+	Total
0–6	—	8.33%	8.33%	—	—	8.33%	—	25.00%
7–13	—	—	8.33%	—	—	—	8.33%	16.67%
14–20	—	8.33%	8.33%	8.33%	—	—	—	25.00%
21–27	—	—	—	8.33%	—	8.33%	8.33%	25.00%
28–34	—	—	—	—	—	—	—	—
35–41	—	8.33%	—	—	—	—	—	8.33%
42+	—	—	—	—	—	—	—	—
Total	—	25.00%	25.00%	16.67%	—	16.67%	16.67%	100%

Chicago Hornets — Summary Statistics

	Scored	Allowed	Difference
Mean	14.92	22.33	-7.42
SD	10.44	13.53	17.45
CV	0.70	0.61	—
Max	35	42	+28
Min	0	7	-35

Games Played: 12

↓ Scored \| Allowed →	0–6	7–13	14–20	21–27	28–34	35–41	42+	Total
0–6	—	—	—	—	—	—	—	—
7–13	—	8.33%	—	—	—	—	—	8.33%
14–20	16.67%	—	—	—	—	—	—	16.67%
21–27	8.33%	—	—	—	—	—	—	8.33%
28–34	8.33%	—	8.33%	—	16.67%	—	8.33%	41.67%
35–41	8.33%	—	—	—	—	—	—	8.33%
42+	—	8.33%	8.33%	—	—	—	—	16.67%
Total	41.67%	16.67%	16.67%	—	16.67%	—	8.33%	100%

Cleveland Browns — Summary Statistics

	Scored	Allowed	Difference
Mean	28.25	14.25	+14.00
SD	14.23	16.54	20.47
CV	0.50	1.16	—
Max	61	56	+47
Min	7	0	-28

Games Played: 12

↓ Scored \| Allowed →	0–6	7–13	14–20	21–27	28–34	35–41	42+	Total
0–6	—	—	—	—	—	—	—	—
7–13	—	8.33%	—	—	—	—	8.33%	16.67%
14–20	—	—	16.67%	—	—	—	16.67%	33.33%
21–27	—	8.33%	8.33%	8.33%	—	8.33%	—	33.33%
28–34	—	—	—	—	—	—	—	—
35–41	—	—	—	—	—	—	—	—
42+	—	—	8.33%	—	8.33%	—	—	16.67%
Total	—	16.67%	33.33%	8.33%	8.33%	8.33%	25.00%	100%

Los Angeles Dons — Summary Statistics

	Scored	Allowed	Difference
Mean	21.08	26.83	-5.75
SD	12.82	16.14	22.51
CV	0.61	0.60	—
Max	49	61	+32
Min	7	10	-47

Games Played: 12

↓ Scored \| Allowed →	0–6	7–13	14–20	21–27	28–34	35–41	42+	Total
0–6	—	—	8.33%	—	8.33%	—	—	16.67%
7–13	—	8.33%	—	—	—	—	—	8.33%
14–20	—	8.33%	25.00%	—	—	8.33%	—	41.67%
21–27	8.33%	—	8.33%	8.33%	—	—	—	25.00%
28–34	—	—	—	—	—	—	—	—
35–41	—	—	—	8.33%	—	—	—	8.33%
42+	—	—	—	—	—	—	—	—
Total	8.33%	16.67%	41.67%	16.67%	8.33%	8.33%	—	100%

New York Yankees — Summary Statistics

	Scored	Allowed	Difference
Mean	16.33	17.17	-0.83
SD	10.05	9.33	14.31
CV	0.62	0.54	—
Max	38	35	+21
Min	0	3	-31

Games Played: 12

↓ Scored \| Allowed →	0–6	7–13	14–20	21–27	28–34	35–41	42+	Total
0–6	—	—	—	8.33%	—	—	—	8.33%
7–13	—	—	—	—	—	—	—	—
14–20	—	—	—	—	8.33%	—	—	8.33%
21–27	—	—	—	—	—	—	—	—
28–34	—	8.33%	8.33%	—	8.33%	—	—	25.00%
35–41	—	—	8.33%	8.33%	—	—	—	16.67%
42+	—	16.67%	8.33%	8.33%	8.33%	—	—	41.67%
Total	—	25.00%	25.00%	25.00%	25.00%	—	—	100%

San Francisco 49ers — Summary Statistics

	Scored	Allowed	Difference
Mean	34.67	18.92	+15.75
SD	14.59	8.43	18.81
CV	0.42	0.45	—
Max	56	30	+44
Min	3	7	-21

Games Played: 12

Wins vs. Points Scored, Allowed, and Differential

Wins plotted against points scored, allowed, and differential. Use the buttons to switch views; hover a team for exact values. The table gives each fit's R² and slope (the change in wins per 10 points).

Fit Metrics

	R²	Slope
Scored	0.53	+0.2
Allowed	0.85	-0.5
Differential	0.85	+0.2

Home-Field Advantage Edge

A measure of how well each team has taken advantage of home-field advantage during the season. For each team, sum the win probabilities for home games and compare against the team's actual performance at home. Repeat for games on the road. Positive values indicate the team has played comparatively better at home than on the road. Negative values indicate the team is not utilizing home field advantage.

Top Overachievers & Disappointments

The teams that deviated the most from the simulated results.

Top Overachievers

#	Team	Actual	Sim	Luck
1	New York Yankees	8	6.12	+1.88
2	Chicago Hornets	4	2.29	+1.71
3	Buffalo Bills (1st)	6	5.75	+0.25
4	Cleveland Browns	10	9.78	+0.22
5	San Francisco 49ers	9	8.89	+0.11

Biggest Disappointments

#	Team	Actual	Sim	Luck
1	Baltimore Colts (1st)	1	4.13	-3.13
2	Los Angeles Dons	4	5.04	-1.04
3	San Francisco 49ers	9	8.89	+0.11
4	Cleveland Browns	10	9.78	+0.22
5	Buffalo Bills (1st)	6	5.75	+0.25

Top Streaks

The most unlikely streaks achieved by teams throughout the season according to the model's probabilities. Calculated by using the pregame win/tie/loss probabilities for all the games in each team's streak.

Most Unlikely Winning Streaks

#	Team	Games	Dates	Probability
1	Chicago Hornets	2	Sep 9 – Sep 16	1 in 28
2	New York Yankees	5	Sep 22 – Oct 30	1 in 25
3	Buffalo Bills (1st)	2	Oct 23 – Nov 6	1 in 6
4	Baltimore Colts (1st)	1	Oct 2 – Oct 2	1 in 4
5	Los Angeles Dons	1	Sep 2 – Sep 2	1 in 2

Most Unlikely Losing Streaks

#	Team	Games	Dates	Probability
1	Baltimore Colts (1st)	6	Oct 16 – Nov 27	1 in 26
2	Los Angeles Dons	4	Sep 9 – Oct 2	1 in 16
3	Buffalo Bills (1st)	3	Oct 2 – Oct 16	1 in 11
4	San Francisco 49ers	2	Oct 23 – Oct 30	1 in 7
5	Chicago Hornets	5	Oct 28 – Nov 24	1 in 3

Finish Position Heatmaps

Cells represent the percentage of the time a team finished in a given position in the simulation.

Team	1	2	3
New York Yankees	51.72%	34.53%	13.75%
Buffalo Bills (1st)	39.15%	41.95%	18.90%
Baltimore Colts (1st)	9.13%	23.52%	67.35%

Team	1	2	3	4
Cleveland Browns	66.37%	32.20%	1.43%	<0.01%
San Francisco 49ers	33.12%	62.52%	4.31%	0.06%
Los Angeles Dons	0.51%	5.18%	83.61%	10.70%
Chicago Hornets	<0.01%	0.10%	10.65%	89.24%

Team	1	2	3	4	5	6	7
Cleveland Browns	64.52%	29.09%	5.02%	1.10%	0.23%	0.03%	<0.01%
San Francisco 49ers	31.95%	51.09%	12.09%	3.58%	1.05%	0.22%	0.02%
New York Yankees	1.90%	9.28%	33.65%	26.71%	17.61%	8.89%	1.97%
Buffalo Bills (1st)	1.08%	6.21%	26.40%	29.00%	22.38%	12.00%	2.94%
Los Angeles Dons	0.45%	3.34%	15.86%	23.68%	27.91%	21.72%	7.04%
Baltimore Colts (1st)	0.10%	0.96%	6.42%	13.78%	24.70%	38.31%	15.73%
Chicago Hornets	<0.01%	0.04%	0.57%	2.14%	6.12%	18.83%	72.29%

Win Totals in Context

How each team's actual results compared to their simulated results, Elo rating, average opponent Elo, and percentile within simulated outcomes? Click a division name in the legend to toggle it on or off.

Playoff Seed Probabilities

Cells represent the percentage of the time a team earned a given playoff seed in the simulation. Teams are sorted by likelihood of earning the top seed. Teams that missed the playoffs more often sit toward the bottom.

Team	1 Seed	2 Seed	3 Seed	4 Seed	Missed Playoffs
Cleveland Browns	64.52%	29.09%	5.02%	1.10%	0.26%
San Francisco 49ers	31.95%	51.09%	12.09%	3.58%	1.29%
New York Yankees	1.90%	9.28%	33.65%	26.71%	28.47%
Buffalo Bills (1st)	1.08%	6.21%	26.40%	29.00%	37.31%
Los Angeles Dons	0.45%	3.34%	15.86%	23.68%	56.67%
Baltimore Colts (1st)	0.10%	0.96%	6.42%	13.78%	78.75%
Chicago Hornets	<0.01%	0.04%	0.57%	2.14%	97.25%

Edges & Scoring

How these are measured

The navy dot is the actual value, the gold line and key are the model's reference where one applies, and the slate ticks are the cutoffs between read labels listed under each metric.

Home Edge: Percentage of games won by the home team - percentage of games won by the away team
No Edge: under 2% · Slight Edge: 2% to 6% · Clear Edge: 6% to 10% · Fortress: 10% and up.
Elo Value: Number of Elo rating points that 1 point is worth. A team this many Elo ratings points better than another would be expected to defeat their opponent by 1 point at a neutral location.
Scoring Tilt: Average home points - average away points per game. The gold line represents the expected home points edge according to the scoring value of a point of Elo and the number of Elo rating points home advantage is worth.
Road-Tilted: under -3.2 · Lean Road: -3.2 to 0 · Lean Home: 0 to 3.2 · Home-Tilted: 3.2 and up.

Home Edge

HomeTieAway

+9.52%

Clear Edge

52.38%4.76%42.86%

Elo Value

Home Edge

22 Elo

0.046 points per Elo point

033.1960

Scoring Tilt

Expected

+3.17 points

Lean Home

-8+1.52+8

Title Race

How these are measured

The navy dot is the actual value, the gold line and key are the model's reference where one applies, and the slate ticks are the cutoffs between read labels listed under each metric.

Title-Race Openness: Effective number of preseason title contenders. Calculated by taking 1 divided by the sum of squared preseason title odds. Higher numbers indicate more parity in the league while 1 indicates that the preseason favorite is a near-lock.
Front-Runner: under 2 · Few Contenders: 2 to 4 · Open Race: 4 to 8 · Wide Open: 8 and up.
Champion Preseason Odds: Preseason probability that the eventual champion would win the title based on the simulated results. Location of the dot marks their rank across all teams, ranging from longshot to favorite.
Preseason Favorite: 1st · Among the Favorites: 2nd · Middle of the Pack: 3rd to 4th · Longshot: 5th or lower.

Title-Race Openness

2.3

Few Contenders

1247

Champion Preseason Odds

56%

Cleveland Browns, 1st of 7

LongshotFavorite

Simulation-Based Surprises

How these are measured

The navy dot is the actual value, the gold line and key are the model's reference where one applies, and the slate ticks are the cutoffs between read labels listed under each metric.

Luck Spread: Average standard deviation of the difference between each team's actual wins total and their simulated average wins total. The gold line is the standard deviation the model expected from random chance alone.
Subdued: under 1.16 · As Expected: 1.16 to 1.6 · Elevated: 1.6 to 2.18 · High Variance: 2.18 and up.
Average Finish Error: Average gap in the rank of the final standings between where each team finished in the standings and where the model projected them to finish.
Pinpoint: under 0.61 · Close: 0.61 to 0.83 · Off Target: 0.83 to 1.08 · Well Off Target: 1.08 and up.
Biggest Overachiever: The team whose record finished in the highest percentile within its own simulated range of outcomes. The gold line indicates where the top team in a league of 7 teams typically lands.
Biggest Underachiever: The team whose record finished in the lowest percentile within its own simulated range of outcomes. The gold line indicates where the bottom team in a league of 7 teams typically lands.
Season Outliers: Number of teams that finished either above the 95th percentile or below the 5th percentile. Even with a well-calibrated model, 10% of teams are expected to land in the extremes of their distributions.
Minimal Outliers: under 0.35 · As Expected: 0.35 to 0.84 · Several Outliers: 0.84 to 1.54 · Many Outliers: 1.54 and up.
Unexpected Playoff Teams: Number of teams that actually made the playoffs but were not in the model's projected field.The gold line represents how many playoff teams the simulation missed on average.
Fewer Than Expected: under 0.5 · As Expected: 0.5 to 0.84 · More Than Expected: 0.84 to 1.35 · Far More Than Expected: 1.35 and up.

Luck Spread

Expected

1.67 wins

Elevated

01.454

Average Finish Error

Expected

0.43

Pinpoint

00.721.5

Biggest Overachiever

Expected 92.86%

96.27%

Chicago Hornets

50100

Biggest Underachiever

Expected

4.40%

Baltimore Colts (1st)

07.14%50

Season Outliers

Expected

3 of 7

Many Outliers

00.77

Unexpected Playoff Teams

Expected

0 of 4

Fewer Than Expected

00.74

Parity

How these are measured

The navy dot is the actual value, the gold line and key are the model's reference where one applies, and the slate ticks are the cutoffs between read labels listed under each metric.

Gini Index: Measures how evenly wins were distributed across the league. Lower scores indicate there was less variability across the actual wins totals .Higher scores are an indication of more imbalance in the league with a few unusually strong or unusually weak teams.
Highly Balanced: under 0.08 · Balanced: 0.08 to 0.15 · Top-Heavy: 0.15 to 0.24 · Concentrated: 0.24 and up.
Noll-Scully: Measures how more times spread out the final standings were in reality compared to standings that were generated by flipping a coin for each game. The gold line at 1 indicates as much variability in the standings as s coin flip. Above it, talent gaps in team composition stretched the standings more than the variability produced by luck alone. Below it, the league was more competitive than coin flips alone would yield.
Compressed: under 0.9 · Coin-Flip Spread: 0.9 to 1.15 · Moderate Separation: 1.15 to 1.45 · Stratified: 1.45 and up.
Interquartile Edge: The probability that the team in the 75th percentile of the league's Elo ratings would defeat the team in the 25th percentile at a neutral site. The higher the probability, the larger the gap between the top teams and bottom teams in the league.
Even: under 58% · Competitive: 58% to 65% · Tilted: 65% to 73% · Lopsided: 73% and up.
Best vs. Worst: The probability that the team with the highest Elo rating would defeat the team with the lowest Elo rating at a neutral site.The higher the probability, the larger the gap between the top teams and bottom teams in the league. The gold line represents how high this probability is expected to be in a league of this size. A blue dot to the right indicates an unusually dominant team or an unusually weak team.
Tight: under 65% · Clear Edge: 65% to 78% · Lopsided: 78% to 88% · No Contest: 88% and up.
Close Games: Actual percentage of games decided by 3 run/points or fewer. The gold line indicates the proportion of close games you would expect after considering the Elo ratings of the involved teams and the scoring value of a single Elo point.
Mostly Decisive: under 25% · Some Drama: 25% to 38% · Often Close: 38% to 50% · Nail-Biters: 50% and up.
Blowouts: Actual percentage of games decided by 17 runs/points or more. The gold line indicates the proportion of blowouts you would expect after considering the Elo ratings of the involved teams and the scoring value of a single Elo point.
Rare: under 10% · Occasional: 10% to 20% · Frequent: 20% to 30% · Routine: 30% and up.

Gini Index

0.29

Concentrated

00.080.150.240.5

Noll-Scully

Coin-flip

1.51

Stratified

01.003

Interquartile Edge

80%

Lopsided

50%58%65%73%100%

Best vs. Worst

Baseline 96%

95%

No Contest

50%100%

Close Games

Expected

26%

Some Drama

0%14%100%

Blowouts

Expected

40%

Routine

0%41%100%

Predictability

How these are measured

The navy dot is the actual value, the gold line and key are the model's reference where one applies, and the slate ticks are the cutoffs between read labels listed under each metric.

Brier Score: How close the pregame win probabilities aligned with the actual game result, averaged over the entire season. Picks that were both confident and correct are rewarded the most, while incorrect predictions and/or uncertain predictions are penalized more. Lower scores are better. 0 indicates every game was perfectly predicted with maximum confidence. For sports with where wins and losses are the only outcomes, Brier scores less than 0.25 indicate the model did better than random predictions. For sports where ties are possible, 0.67 is the cutoff for which the Brier score must be lower to beat random predictions. The lower the Brier score, the easier and more accurately the games were to predict.
Highly Predictable: under 0.18 · Predictable: 0.18 to 0.22 · Hard to Predict: 0.22 to 0.25 · Coin-Flip: 0.25 and up.
Matchup Imbalance: How lopsided the matchups were on paper, calculated by averaging the difference in the win probabilities divided by the sum of the win probabilities. Lower scores indicate more parity in the league. 0 indicates that every game was a 50-50 toss-up between evenly matched teams. 1 means every game pitted a heavy favorite against a huge underdog.
Evenly Matched: under 0.12 · Slight Separation: 0.12 to 0.22 · Wide Gaps: 0.22 to 0.34 · Lopsided: 0.34 and up.
Strangeness: How extreme the actual final standings were compared to what the model expected. A value of 0 would indicate that the simulated results perfectly matched the actual standings. A score of 1 indicates that the actual results were scattered around the projections by exactly the variance the model predicted. (i.e. The projections missed the actual standings by 1 standard deviation on average. Scores larger than 1 mean the season was wilder to forecast with more overperforming and underperforming teams than expected. Scores less than 1 indicate the season was more predictable.
Tighter Than Modeled: under 0.85 · As Expected: 0.85 to 1.15 · Volatile: 1.15 to 1.5 · Chaotic: 1.5 and up.
Repeatability: How closely the order of the final standings aligned with the ranked preseason Elo ratings as calculated by the Spearman rank correlation. Larger values indicate that the preseason Elo ratings were a strong predictor of the team's final rank in the standings while values near 0 mean.
Reshuffled: under 0.3 · Weak Alignment: 0.3 to 0.6 · Strong Alignment: 0.6 to 0.85 · Closely Aligned: 0.85 and up.
Upset Rate: The percentage of the time the underdog won the game in reality. The gold line measures how often the model expected the underdog to win when considering the outcome probabilities. A blue dot to the right of the gold line means upsets were more prevalent than left. A dot to the left indicates that favorites won more often than expected.
Chalk Held: under 30% · As Expected: 30% to 40% · Upset-Prone: 40% to 46% · Bedlam: 46% and up.
Clear Favorite Upset Rate: The percentage of the time the underdog won the game in reality, but only including games with a clear favorite, one at least 60% likely to win once a draw is set aside. This metrics ignores games that could be considered toss-ups. The gold line is how often the model expected these heavy favorites to lose. A dot to the right means the big favorites were upset more than expected; to the left means they took care of business.
Favorites Held: under 22% · As Expected: 22% to 32% · Shaky Favorites: 32% to 42% · Bedlam: 42% and up.

Brier Score

Expected

0.19

Predictable

00.171

Matchup Imbalance

0.51

Lopsided

00.120.220.340.5

Strangeness

Expected

1.50

Chaotic

01.002

Repeatability

0.85

Strong Alignment

00.30.60.851

Upset Rate

Expected

26%

Chalk Held

0%23%50%

Clear Favorite Upset Rate

Expected

24%

As Expected

0%19%50%

Calibration

How these are measured

The navy dot is the actual value, the gold line and key are the model's reference where one applies, and the slate ticks are the cutoffs between read labels listed under each metric.

Probability calibration: An all-in-one chi-square test of the model's probabilities. Games are sorted into bins according to how confident the model was. Within each bin, the predicted number of wins, losses, and ties are compared against the actual counts. The p-value of this test is plotted below. Values above 0.05 indicate that the model's probabilities are well-calibrated for the season.
Clear Misfit: under 0.01 · Misfit: 0.01 to 0.05 · Borderline: 0.05 to 0.1 · Well Calibrated: 0.1 and up.
Calibration slope: Checks whether the spread of the model's probabilities is correct. Each probability is turned into their log-odds. A line is fit that predicts the actual results from the log-odds. The slope of this line is the calibration slope.A slope of 1.00 is perfect, indicating that the model's confidence matches the actual outcomes of the games. Slopes less than 1.00 indicate overconfidence. The model assigned higher probabilities to the favorites than was appropriate given the matchup, causing more losses by favored teams. Slopes greater than 1.00 indicate under-confidence. The model is more uncertain about too many results, assigning them lower probabilities when in reality the favorites should have had higher probabilities.
Overconfident: under 0.85 · Calibrated: 0.85 to 1.15 · Underconfident: 1.15 and up.
Calibration error (ECE): Calibration error (ECE) checks whether the model's probabilities mean what they say. ECE is calculated as the average weighted gap between the model's stated chances and how often the predicted outcome actually occurred. The smaller the ECE, the more confident we are about the model's probabilities. The gold line represents the noise ceiling, which is the amount of error that luck can produce on its own even if the probabilities are perfectly calibrated. Values below the noise ceiling indicate that the model's error is no larger than chance alone would produce. Values above the noice ceiling point to a genuine calibration issue since the error is larger than luck could explain.
Well Within Noise: under 0.11 · Within Noise: 0.11 to 0.22 · Above Noise: 0.22 to 0.44 · Well Above Noise: 0.44 and up.

Probability calibration

0.80

Well Calibrated

0.010.050.11

Calibration slope

Ideal

0.88

Calibrated

0.51.001.5

Calibration error (ECE)

Noise ceiling

0.134

Within Noise

00.2200.5

Season Trends

How each metric evolved across the season - Elo rating, actual wins, simulated final wins, playoff probability, and division-title probability - day by day. Select a division to see all five charts for its teams.

Elo Through the Playoffs

How each playoff team's Elo rating evolved as the postseason unfolded. Elo Progression traces each team's game-by-game Elo rating through their playoff run. Net Elo Change summarizes the difference in Elo rating between the beginning and end of the playoffs for each team.

Stochastic Playoff Outcomes

How we would have expected the postseason to play out at the beginning of the season according to the simulation. The table summarizes each team's chances of advancing to each round. Individual matchup heat maps for each round are displayed using the subsequent buttons. The top percentage in each cell represents each team's winning percentage against the corresponding opponent. The bottom percentage represents how often that specific matchup occurred during that round in the simulation.

Team	Made Playoffs	Won Championship Game
Cleveland Browns	85.13%	55.97%
San Francisco 49ers	77.75%	35.69%
New York Yankees	16.20%	4.03%
Buffalo Bills (1st)	12.84%	2.96%
Los Angeles Dons	6.44%	1.18%
Baltimore Colts (1st)	1.49%	0.15%
Chicago Hornets	0.15%	0.01%

Loser → ↓ Winner	Baltimore Colts (1st)	Buffalo Bills (1st)	Chicago Hornets	Cleveland Browns	Los Angeles Dons	New York Yankees	San Francisco 49ers
Baltimore Colts (1st)		26.5%0.08%	50.0%<0.01%	7.7%0.75%	19.2%0.03%	24.4%0.13%	7.6%0.50%
Buffalo Bills (1st)	73.5%0.08%		60.0%<0.01%	16.5%6.79%	56.5%0.34%	46.0%1.17%	23.6%4.45%
Chicago Hornets	50.0%<0.01%	40.0%<0.01%		1.6%0.06%	66.7%<0.01%	8.3%0.01%	8.8%0.07%
Cleveland Browns	92.3%0.75%	83.5%6.79%	98.4%0.06%		86.8%3.32%	81.7%9.01%	60.3%65.20%
Los Angeles Dons	80.8%0.03%	43.5%0.34%	33.3%<0.01%	13.2%3.32%		36.8%0.55%	16.7%2.20%
New York Yankees	75.6%0.13%	54.0%1.17%	91.7%0.01%	18.3%9.01%	63.2%0.55%		24.2%5.33%
San Francisco 49ers	92.4%0.50%	76.4%4.45%	91.2%0.07%	39.7%65.20%	83.3%2.20%	75.8%5.33%

Actual Bracket Simulation

Team	Won Championship Game	Actual Outcome
Cleveland Browns	57.54%	Won Championship Game
San Francisco 49ers	33.57%	Eliminated in Championship Game

Loser → ↓ Winner	Buffalo Bills (1st)	Cleveland Browns	New York Yankees	San Francisco 49ers
Buffalo Bills (1st)			43.0%3.05%	22.5%11.21%
Cleveland Browns			81.8%18.28%	63.1%67.45%
New York Yankees	57.0%3.05%	18.2%18.28%
San Francisco 49ers	77.5%11.21%	36.9%67.45%

Most-Likely Championship Paths

For each playoff team, what was the most likely path they had to the championship across all simulations? Tiles represent the opponent they faced and defeated the most often in each round.

Cleveland Browns 57.54% chance to win

Championship Game

vs. San Francisco 49ers

Matchup

74.00%

Win Prob

63.12%

San Francisco 49ers 33.57% chance to win

Championship Game

vs. Cleveland Browns

Matchup

74.10%

Win Prob

36.88%

New York Yankees 5.06% chance to win

Championship Game

vs. Cleveland Browns

Matchup

65.67%

Win Prob

18.19%

Buffalo Bills (1st) 3.83% chance to win

Championship Game

vs. San Francisco 49ers

Matchup

65.77%

Win Prob

22.46%

Regular Season Games

Summary of every regular-season game played this season.

Filter by Team:

Date	Opponent	Score	Pre Elo	Opp Elo	Win %	Loss %	Elo Δ	Record
1949-08-28	@ San Francisco 49ers	L 17-31	1462.94	1673.87	18.44%	77.59%	-9.31	0-1
1949-09-02	@ Los Angeles Dons	L 17-49	1453.63	1434.40	45.02%	49.03%	-34.26	0-2
1949-09-11	@ Cleveland Browns	L 0-21	1419.37	1745.44	10.70%	86.68%	-6.49	0-3
1949-09-16	Chicago Hornets	L 7-35	1412.88	1243.40	73.40%	22.13%	-50.92	0-4
1949-09-25	Cleveland Browns	L 20-28	1361.96	1758.01	10.51%	86.91%	-3.93	0-5
1949-10-02	@ Buffalo Bills (1st)	W 35-28	1358.03	1504.50	24.39%	70.87%	+24.63	1-5
1949-10-16	New York Yankees	L 21-24	1382.66	1493.77	36.26%	58.04%	-8.52	1-6
1949-10-23	Chicago Hornets	L 7-17	1374.14	1274.22	65.30%	29.46%	-27.24	1-7
1949-10-30	@ New York Yankees	L 14-21	1346.90	1545.70	19.47%	76.42%	-6.96	1-8
1949-11-06	San Francisco 49ers	L 10-28	1339.94	1677.03	14.00%	82.77%	-7.93	1-9
1949-11-20	Los Angeles Dons	L 10-21	1332.01	1426.69	38.43%	55.77%	-17.26	1-10
1949-11-27	Buffalo Bills (1st)	L 14-38	1314.75	1477.20	29.90%	64.81%	-19.92	1-11
1949-08-26	@ Chicago Hornets	L 14-17	1501.52	1215.24	78.43%	17.71%	-17.73	0-1
1949-09-05	Cleveland Browns	T 28-28	1483.79	1747.27	19.62%	76.25%	+1.83	0-1
1949-09-11	New York Yankees	L 14-17	1485.62	1464.77	54.73%	39.44%	-12.61	0-2
1949-09-25	San Francisco 49ers	W 28-17	1473.01	1699.35	23.04%	72.37%	+31.49	1-2
1949-10-02	Baltimore Colts (1st)	L 28-35	1504.50	1358.03	70.87%	24.39%	-24.63	1-3
1949-10-09	@ Los Angeles Dons	L 28-42	1479.87	1424.81	50.17%	43.90%	-25.09	1-4
1949-10-16	@ San Francisco 49ers	L 7-51	1454.78	1713.80	14.79%	81.84%	-13.13	1-5
1949-10-23	Los Angeles Dons	W 17-14	1441.65	1433.15	52.99%	41.13%	+9.62	2-5
1949-11-06	@ New York Yankees	W 17-14	1451.27	1552.65	29.29%	65.48%	+14.97	3-5
1949-11-13	@ Cleveland Browns	T 7-7	1466.24	1757.96	12.66%	84.35%	+2.31	3-5
1949-11-20	Chicago Hornets	W 10-0	1468.55	1278.63	75.53%	20.25%	+8.65	4-5
1949-11-27	@ Baltimore Colts (1st)	W 38-14	1477.20	1314.75	64.81%	29.90%	+19.92	5-5
1949-08-26	Buffalo Bills (1st)	W 17-14	1215.24	1501.52	17.71%	78.43%	+17.73	1-0
1949-09-04	@ San Francisco 49ers	L 7-42	1232.97	1683.17	5.66%	92.82%	-4.35	1-1
1949-09-09	@ Los Angeles Dons	W 23-21	1228.62	1468.66	16.15%	80.24%	+14.78	2-1
1949-09-16	@ Baltimore Colts (1st)	W 35-7	1243.40	1412.88	22.13%	73.40%	+50.92	3-1
1949-09-30	San Francisco 49ers	L 24-42	1294.32	1667.85	11.75%	85.44%	-6.62	3-2
1949-10-07	New York Yankees	L 24-38	1287.70	1480.29	26.52%	68.51%	-13.48	3-3
1949-10-23	@ Baltimore Colts (1st)	W 17-7	1274.22	1374.14	29.46%	65.30%	+27.25	4-3
1949-10-28	Los Angeles Dons	L 14-24	1301.47	1423.52	34.85%	59.53%	-14.96	4-4
1949-11-06	@ Cleveland Browns	L 2-35	1286.51	1754.11	5.16%	93.44%	-3.84	4-5
1949-11-13	@ New York Yankees	L 10-14	1282.67	1537.69	15.07%	81.51%	-4.04	4-6
1949-11-20	@ Buffalo Bills (1st)	L 0-10	1278.63	1468.55	20.25%	75.53%	-8.65	4-7
1949-11-24	@ Cleveland Browns	L 6-14	1269.98	1773.99	4.24%	94.58%	-1.55	4-8
1949-09-05	@ Buffalo Bills (1st)	T 28-28	1747.27	1483.79	76.25%	19.62%	-1.83	0-0
1949-09-11	Baltimore Colts (1st)	W 21-0	1745.44	1419.37	86.68%	10.70%	+6.49	1-0
1949-09-18	New York Yankees	W 14-3	1751.93	1477.39	83.07%	13.74%	+6.08	2-0
1949-09-25	@ Baltimore Colts (1st)	W 28-20	1758.01	1361.96	86.91%	10.51%	+3.94	3-0
1949-10-02	Los Angeles Dons	W 42-7	1761.95	1433.07	86.86%	10.56%	+8.26	4-0
1949-10-09	@ San Francisco 49ers	L 28-56	1770.21	1674.47	55.92%	38.29%	-39.34	4-1
1949-10-14	@ Los Angeles Dons	W 61-14	1730.87	1449.90	77.94%	18.14%	+16.76	5-1
1949-10-30	San Francisco 49ers	W 30-28	1747.63	1683.52	60.66%	33.78%	+6.48	6-1
1949-11-06	Chicago Hornets	W 35-2	1754.11	1286.51	93.44%	5.16%	+3.85	7-1
1949-11-13	Buffalo Bills (1st)	T 7-7	1757.96	1466.24	84.35%	12.66%	-2.32	7-1
1949-11-20	@ New York Yankees	W 31-0	1755.64	1541.72	70.99%	24.28%	+18.35	8-1
1949-11-24	Chicago Hornets	W 14-6	1773.99	1269.98	94.58%	4.24%	+1.55	9-1
1949-09-02	Baltimore Colts (1st)	W 49-17	1434.40	1453.63	49.03%	45.02%	+34.26	1-0
1949-09-09	Chicago Hornets	L 21-23	1468.66	1228.62	80.24%	16.15%	-14.78	1-1
1949-09-18	@ San Francisco 49ers	L 14-42	1453.88	1687.52	16.64%	79.68%	-11.83	1-2
1949-09-22	@ New York Yankees	L 7-10	1442.05	1471.30	38.31%	55.90%	-8.98	1-3
1949-10-02	@ Cleveland Browns	L 7-42	1433.07	1761.95	10.56%	86.86%	-8.26	1-4
1949-10-09	Buffalo Bills (1st)	W 42-28	1424.81	1479.87	43.90%	50.17%	+25.09	2-4
1949-10-14	Cleveland Browns	L 14-61	1449.90	1730.87	18.14%	77.94%	-16.75	2-5
1949-10-23	@ Buffalo Bills (1st)	L 14-17	1433.15	1441.65	41.13%	52.99%	-9.63	2-6
1949-10-28	@ Chicago Hornets	W 24-14	1423.52	1301.47	59.53%	34.85%	+14.96	3-6
1949-11-13	San Francisco 49ers	L 24-41	1438.48	1684.96	21.13%	74.52%	-11.79	3-7
1949-11-20	@ Baltimore Colts (1st)	W 21-10	1426.69	1332.01	55.77%	38.43%	+17.26	4-7
1949-11-24	New York Yankees	L 16-17	1443.95	1523.38	40.51%	53.63%	-5.47	4-8
1949-09-11	@ Buffalo Bills (1st)	W 17-14	1464.77	1485.62	39.44%	54.73%	+12.62	1-0
1949-09-18	@ Cleveland Browns	L 3-14	1477.39	1751.93	13.74%	83.07%	-6.09	1-1
1949-09-22	Los Angeles Dons	W 10-7	1471.30	1442.05	55.90%	38.31%	+8.99	2-1
1949-10-07	@ Chicago Hornets	W 38-24	1480.29	1287.70	68.51%	26.52%	+13.48	3-1
1949-10-16	@ Baltimore Colts (1st)	W 24-21	1493.77	1382.66	58.04%	36.26%	+8.52	4-1
1949-10-23	San Francisco 49ers	W 24-3	1502.29	1726.93	23.21%	72.18%	+43.41	5-1
1949-10-30	Baltimore Colts (1st)	W 21-14	1545.70	1346.90	76.42%	19.47%	+6.95	6-1
1949-11-06	Buffalo Bills (1st)	L 14-17	1552.65	1451.27	65.48%	29.29%	-14.96	6-2
1949-11-13	Chicago Hornets	W 14-10	1537.69	1282.67	81.51%	15.07%	+4.03	7-2
1949-11-20	Cleveland Browns	L 0-31	1541.72	1755.64	24.28%	70.99%	-18.34	7-3
1949-11-24	@ Los Angeles Dons	W 17-16	1523.38	1443.95	53.63%	40.51%	+5.47	8-3
1949-11-27	@ San Francisco 49ers	L 14-35	1528.85	1696.75	22.28%	73.23%	-13.82	8-4
1949-08-28	Baltimore Colts (1st)	W 31-17	1673.87	1462.94	77.59%	18.44%	+9.30	1-0
1949-09-04	Chicago Hornets	W 42-7	1683.17	1232.97	92.82%	5.66%	+4.35	2-0
1949-09-18	Los Angeles Dons	W 42-14	1687.52	1453.88	79.68%	16.64%	+11.83	3-0
1949-09-25	@ Buffalo Bills (1st)	L 17-28	1699.35	1473.01	72.37%	23.04%	-31.50	3-1
1949-09-30	@ Chicago Hornets	W 42-24	1667.85	1294.32	85.44%	11.75%	+6.62	4-1
1949-10-09	Cleveland Browns	W 56-28	1674.47	1770.21	38.29%	55.92%	+39.33	5-1
1949-10-16	Buffalo Bills (1st)	W 51-7	1713.80	1454.78	81.84%	14.79%	+13.13	6-1
1949-10-23	@ New York Yankees	L 3-24	1726.93	1502.29	72.18%	23.21%	-43.41	6-2
1949-10-30	@ Cleveland Browns	L 28-30	1683.52	1747.63	33.78%	60.66%	-6.49	6-3
1949-11-06	@ Baltimore Colts (1st)	W 28-10	1677.03	1339.94	82.77%	14.00%	+7.93	7-3
1949-11-13	@ Los Angeles Dons	W 41-24	1684.96	1438.48	74.52%	21.13%	+11.79	8-3
1949-11-27	New York Yankees	W 35-14	1696.75	1528.85	73.23%	22.28%	+13.83	9-3

Playoff Games

Every playoff game from the selected team's perspective.

Date	Opponent	Score	Pre Elo	Opp Elo	Win %	Loss %	Elo Δ	Record
1949-12-04	@ Cleveland Browns	L 21-31	1497.12	1775.54	14.26%	85.74%	-5.70	0-1
1949-12-04	Buffalo Bills (1st)	W 31-21	1775.54	1497.12	85.74%	14.26%	+5.69	1-0
1949-12-11	San Francisco 49ers	W 21-7	1781.23	1719.01	63.40%	36.60%	+17.28	2-0
1949-12-04	@ San Francisco 49ers	L 7-17	1515.03	1710.58	21.14%	78.86%	-8.44	0-1
1949-12-04	New York Yankees	W 17-7	1710.58	1515.03	78.86%	21.14%	+8.43	1-0
1949-12-11	@ Cleveland Browns	L 7-21	1719.01	1781.23	36.60%	63.40%	-17.28	1-1

Biggest Upsets

The 25 biggest upsets of the seasons, ranked by lowest pregame win probability. An asterisk (*) after the date indicates a playoff game.

#	Date	Underdog Win %	Winning Team			Losing Team
#	Date	Underdog Win %	Team	Elo	Score	Team	Elo	Score
1	1949-09-09	16.15%	Chicago Hornets	1228.62	23	@ Los Angeles Dons	1468.66	21
2	1949-08-26	17.71%	@ Chicago Hornets	1215.24	17	Buffalo Bills (1st)	1501.52	14
3	1949-09-16	22.13%	Chicago Hornets	1243.40	35	@ Baltimore Colts (1st)	1412.88	7
4	1949-09-25	23.04%	@ Buffalo Bills (1st)	1473.01	28	San Francisco 49ers	1699.35	17
5	1949-10-23	23.21%	@ New York Yankees	1502.29	24	San Francisco 49ers	1726.93	3
6	1949-10-02	24.39%	Baltimore Colts (1st)	1358.03	35	@ Buffalo Bills (1st)	1504.50	28
7	1949-11-06	29.29%	Buffalo Bills (1st)	1451.27	17	@ New York Yankees	1552.65	14
8	1949-10-23	29.46%	Chicago Hornets	1274.22	17	@ Baltimore Colts (1st)	1374.14	7
9	1949-10-09	38.29%	@ San Francisco 49ers	1674.47	56	Cleveland Browns	1770.21	28
10	1949-09-11	39.44%	New York Yankees	1464.77	17	@ Buffalo Bills (1st)	1485.62	14
11	1949-10-09	43.90%	@ Los Angeles Dons	1424.81	42	Buffalo Bills (1st)	1479.87	28

Biggest Elo Changes

The 25 games that resulted in the largest shift in Elo rating. An asterisk (*) after the date indicates a playoff game.

#	Date	Elo Δ	Winning Team				Losing Team
#	Date	Elo Δ	Team	Score	Elo	Win %	Team	Score	Elo	Win %
1	1949-09-16	50.92	Chicago Hornets	35	1243.40	22.13%	@ Baltimore Colts (1st)	7	1412.88	73.40%
2	1949-10-23	43.41	@ New York Yankees	24	1502.29	23.21%	San Francisco 49ers	3	1726.93	72.18%
3	1949-10-09	39.34	@ San Francisco 49ers	56	1674.47	38.29%	Cleveland Browns	28	1770.21	55.92%
4	1949-09-02	34.26	@ Los Angeles Dons	49	1434.40	49.03%	Baltimore Colts (1st)	17	1453.63	45.02%
5	1949-09-25	31.50	@ Buffalo Bills (1st)	28	1473.01	23.04%	San Francisco 49ers	17	1699.35	72.37%
6	1949-10-23	27.25	Chicago Hornets	17	1274.22	29.46%	@ Baltimore Colts (1st)	7	1374.14	65.30%
7	1949-10-09	25.09	@ Los Angeles Dons	42	1424.81	43.90%	Buffalo Bills (1st)	28	1479.87	50.17%
8	1949-10-02	24.63	Baltimore Colts (1st)	35	1358.03	24.39%	@ Buffalo Bills (1st)	28	1504.50	70.87%
9	1949-11-27	19.92	Buffalo Bills (1st)	38	1477.20	64.81%	@ Baltimore Colts (1st)	14	1314.75	29.90%
10	1949-11-20	18.35	Cleveland Browns	31	1755.64	70.99%	@ New York Yankees	0	1541.72	24.28%
11	1949-08-26	17.73	@ Chicago Hornets	17	1215.24	17.71%	Buffalo Bills (1st)	14	1501.52	78.43%
12	1949-12-11 *	17.28	@ Cleveland Browns	21	1781.23	63.40%	San Francisco 49ers	7	1719.01	36.60%
13	1949-11-20	17.26	Los Angeles Dons	21	1426.69	55.77%	@ Baltimore Colts (1st)	10	1332.01	38.43%
14	1949-10-14	16.76	Cleveland Browns	61	1730.87	77.94%	@ Los Angeles Dons	14	1449.90	18.14%
15	1949-11-06	14.97	Buffalo Bills (1st)	17	1451.27	29.29%	@ New York Yankees	14	1552.65	65.48%
16	1949-10-28	14.96	Los Angeles Dons	24	1423.52	59.53%	@ Chicago Hornets	14	1301.47	34.85%
17	1949-09-09	14.78	Chicago Hornets	23	1228.62	16.15%	@ Los Angeles Dons	21	1468.66	80.24%
18	1949-11-27	13.83	@ San Francisco 49ers	35	1696.75	73.23%	New York Yankees	14	1528.85	22.28%
19	1949-10-07	13.48	New York Yankees	38	1480.29	68.51%	@ Chicago Hornets	24	1287.70	26.52%
20	1949-10-16	13.13	@ San Francisco 49ers	51	1713.80	81.84%	Buffalo Bills (1st)	7	1454.78	14.79%
21	1949-09-11	12.62	New York Yankees	17	1464.77	39.44%	@ Buffalo Bills (1st)	14	1485.62	54.73%
22	1949-09-18	11.83	@ San Francisco 49ers	42	1687.52	79.68%	Los Angeles Dons	14	1453.88	16.64%
23	1949-11-13	11.79	San Francisco 49ers	41	1684.96	74.52%	@ Los Angeles Dons	24	1438.48	21.13%
24	1949-10-23	9.63	@ Buffalo Bills (1st)	17	1441.65	52.99%	Los Angeles Dons	14	1433.15	41.13%
25	1949-08-28	9.31	@ San Francisco 49ers	31	1673.87	77.59%	Baltimore Colts (1st)	17	1462.94	18.44%