I know not everyone is familiar with moneyline betting.  Taking a team on the moneyline means you are wagering on a team to win the game outright.  The money lines are adjusted based on who is more likely to win the game (based on the point spread).

Let’s use an example. A 4-point favorite in NCAA basketball might be listed at -204 via the money line.  This means that you would need to wager \$204 to profit \$100 on the favorite.

On the flip side, an underdog of 4 points would be listed at +166. This means a wager of \$100 on the under would pay you \$166 if they won the game outright.

## True Money Line: How to use our College Basketball Spread to Moneyline Converter

The chart below plots what the true money line on a game should be based on the posted spread. This was found looking at data on over 20,000 college basketball games and finding out how often the favorite or underdog wins outright at that number (see the table on expected win percentage below for even more detail).  What this gives us is what the true money line of a game is given a fair market (e.g. no juice applied by the sportsbook).

Using this data, you should be able to identify when your book has a money line that isn’t properly priced based on historical results. It is obviously possible for these probabilities to change year to year, but with over 1,500 games sampled at each common line, we are confident that our true money line pricing is accurate. Once you get to less common spreads, of course, you have a smaller sample and the numbers won’t be as reliable, but the main goal here is to identify market inefficiencies on the money line on common point spreads.

Another way to use this to your advantage is when picking upsets in the tournament.  You won’t always see the lower seed viewed as the favorite.  Sometimes Vegas sees “the underdog” in the committees’ eyes as the team more likely to advance.  I definitely use this trick for my own NCAA bracket predictions.

## Spread to Expected Win %

The table below uses historical data to calculate the true win percentage and money line at each spread. The numbers represent pricing based on a fair market, meaning there would be no advantage to the books. Depending on both the spread and the book you use, a books pricing will incorporate an edge to the money line price.  For example, we show a -3 point favorite with a true, fair market money line of -159 and a +3 point dog at +159. In a real-lift situation, the pricing will be more like +130 on the dog and -150 on the favorite. In this case we see some advantage to taking a -3 favorite on the money line at -150 with a true money line value at that number listed at -159.

The fewer games you have at a line, the less accurate the data will be, so we’ve excluded spreads without at least 100 occurrences in our sample. Also note that the higher the money line, the more of an advantage the book applies. In our first example, the book used a 20 cent difference between the favorite and dog price, at a higher spread like -12.5 you are going to see a much bigger difference, like -1100 on the favorite and +650 on the underdog (a 450 cent difference). Using this example, there is no advantage to taking the money line as the built-in advantage for the book is too great.

LineGamesWinsLossesFav Win %Dog Win %Fav MLDog ML
-11993103595851.93%48.07%-108+108
-1.52039108895153.36%46.64%-114+114
-22196122097655.56%44.44%-125+125
-2.52278131196757.55%42.45%-136+136
-32151132282961.46%38.54%-159+159
-3.52200137482662.45%37.55%-166+166
-42071132374863.88%36.12%-177+177
-4.52096138970766.27%33.73%-196+196
-51836124059667.54%32.46%-208+208
-5.51990138260869.45%30.55%-227+227
-61727123549271.51%28.49%-251+251
-6.51773128648772.53%27.47%-264+264
-71620121640475.06%24.94%-301+301
-7.51690131237877.63%22.37%-347+347
-81457112133676.94%23.06%-334+334
-8.51428117725182.42%17.58%-469+469
-91285103824780.78%19.22%-420+420
-9.51205101818784.48%15.52%-544+544
-10112893819083.16%16.84%-494+494
-10.5105389615785.09%14.91%-571+571
-1191879612286.71%13.29%-652+652
-11.592580711887.24%12.76%-684+684
-1283673510187.92%12.08%-728+728
-12.58007158589.38%10.63%-841+841
-137897008988.72%11.28%-787+787
-13.57126516191.43%8.57%-1067+1067
-146656125392.03%7.97%-1155+1155
-14.56315993294.93%5.07%-1872+1872
-155315022994.54%5.46%-1731+1731
-15.54644481696.55%3.45%-2800+2800
-164384231596.58%3.42%-2820+2820
-16.54203952594.05%5.95%-1580+1580
-173653461994.79%5.21%-1821+1821
-17.53543411396.33%3.67%-2623+2623
-18279270996.77%3.23%-3000+3000
-18.5300294698.00%2.00%-4900+4900
-19239235498.33%1.67%-5875+5875
-19.5238235398.74%1.26%-7833+7833
-20189185497.88%2.12%-4625+4625
-20.5201196597.51%2.49%-3920+3920
-21183178597.27%2.73%-3560+3560
-21.5170165597.06%2.94%-3300+3300
-22140137397.86%2.14%-4567+4567
-22.5145144199.31%0.69%-14400+14400
-23123122199.19%0.81%-12200+12200
-23.5111110199.10%0.90%-11000+11000
-24113112199.12%0.88%-11200+11200
-24.5110108298.18%1.82%-5400+5400

I don’t think this data is skewed by teams covering more often at a given line either.  This shows just wins and losses.  If there are enough games in the sample, it should give you the true winning percentage predicted by the sports books.